Competitive intelligence relies on paying attention, even before using any tools.

The analyst who notices only visible activity will produce a busy report and miss half the market.

“It is a capital mistake to theorize before you have all the evidence. It biases the judgment.” – Sherlock Holmes

New products attract the eye. New hires look important. And new campaigns give us something concrete to capture.

But noticing what’s missing is harder.

• The web page hass gone

• A familiar speaker no longer appears at the annual conference

• A partner directory suddenly has fewer names. Real partner directory, unlike those on Crayon

• A product manager changes role, and nobody replaces them

• A sales representative stops mentioning an offer that remains on the website

Each event might seem too minor to mention, but together they can signal a major change.

Attention becomes habit

What you decide to track shapes how you think.

A tracker looking at launches trains the analyst mind to subconsciously see expansion. One built around mentions trains you to see things like publicity. A report built around competitors’ claims trains you to discuss the story competitors chose to publish.

The omission becomes invisible because no field exists for it.

This affects senior decisions.

Leaders receive a steady stream of activity and assume the market is expanding in every direction. They see more features, more announcements and more partnerships.

They rarely see offers receiving less money, customer groups being abandoned, or capabilities losing internal support.

The result is a busy but incomplete picture.

Curiosity needs a negative space.

Good analysts ask what happened.

Great analysts also ask what should have happened but didn’t.

• A company promised quarterly releases. Two quarters pass.

• A chief executive said a region was central to growth. Local hiring stops.

• Product page remains live. New customers cannot buy the product.

• A partner programme celebrates recruitment. Existing partners begin leaving.

These aren’t answers—they’re prompts for further investigation.

The discipline lies in resisting the first explanation.

Silence might mean retreat, delay, legal caution, a private sale, internal issues, or just a change in communication. The goal is to figure out which explanation fits the bigger picture.

Your method reveals your bias.

Every single collection plan will contain an opinion about what matters.

Most teams hide that opinion inside templates and software settings.

They track what the system can capture.

They report what can be counted.

And they discuss what produces a neat comparison.

You rarely see a competitor’s declining commitment as a clear metric. Instead, it shows up as small inconsistencies that need judgment.

That’s why it’s easy to overlook. Especially if you are not watching and listening.

The analyst must create room for awkward evidence. Add a regular review of missing activity, broken patterns and absent voices. Ask sales teams what competitors no longer offer. Ask customers what has become harder to buy. And ask partners where support has weakened.

Intelligence gets better when your team spots these changes before the market.

A Question to Consider

Which important conclusion in your latest competitor report exists because your collection method ignored evidence that was absent, removed or difficult to count?

Practical Advice

Choose one major competitor and compare its current product, people and partner footprint with the position twelve months ago. List what disappeared before discussing what appeared.

We are Octopus. The Global People-Powered Competitive Intelligence Agency.

Outsmart your competition. Make the unknown known. Octopus helps you gain clarity in complex markets. With clients and tentacles around the world, we deliver sharp, actionable competitive intelligence through a blend of deep primary (HUMINT) and secondary research. If you’re looking to make smarter decisions, beat the competition, and reduce uncertainty, we’re the partner you want on your side.

https://www.octopusintelligence.com/competitive-analysis-thinking-what-are-you-training-yourself-not-to-notice/

Below is a framework, based on intelligence analyst methods, designed to help you use competitive intelligence that actually guides your decisions.

If you’re wondering what process to use to turn competitive data into reliable intelligence for strategy, this article outlines the full 20-step framework that professional intelligence analysts use, tailored for business.

The $3M Decision Built on an Assumption Nobody Checked in 2023

A SaaS platform was ready to invest $3M into building enterprise security features.

They reasoned that competitor X was discounting aggressively. They thought they were clearly losing market share. So if they built enterprise security while they were struggling, they would capture the enterprise segment before they recovered.

Someone asked, “How do you know they’re discounting because they’re losing market share?”

“Our sales team says prospects are getting lower quotes from them.”

“That’s what you’ve heard. Is that what’s actually happening?”

We used a structured intelligence analysis. In just three weeks, everything looked different.

What they knew: Competitor X was offering lower prices to certain prospects.

What they thought they knew: Competitor X was losing market share and discounting out of desperation.

What they didn’t know: Whether the discounting was across-the-board or targeted. Whether market share was actually declining. Whether the discounting was desperate or strategic.

What they needed to know: The actual reason behind the pricing changes before committing $3M.

The reality:

Competitor X was not losing market share. They were intentionally gaining ground in one segment: mid-market healthcare, where they had just launched a HIPAA-compliant product. The so-called discounting was actually introductory pricing for healthcare customers only. Their total pricing stayed the same.

They weren’t struggling. They were executing a planned vertical expansion funded by a quiet $20M credit facility.

The SaaS company was close to spending $3M on enterprise security features to take advantage of a weakness that wasn’t real. They were acting on an assumption from their sales team that wasn’t backed by enough information.

One unchecked assumption nearly cost them $3M. Meanwhile, the real competitive threat, vertical expansion into healthcare, was missed entirely.

Why Most Competitive Intelligence Is Just Organised Guessing

At Octopus Intelligence, we are a UK and US-based competitive intelligence agency founded by former British military intelligence analysts. For twenty years, we have worked with companies like Mercedes, Samsung, and European governments.

Here’s what we’ve learned: Most companies confuse data collection with intelligence analysis.

They gather competitive information. They organise it. They present it. They call it intelligence.

That isn’t intelligence. It’s organised data with no real analysis.

Agencies like MI6 and the CIA don’t operate this way. They use disciplined thinking to separate facts from assumptions, test ideas against evidence that might prove them wrong, consider possible deception, and rate their confidence in their conclusions.

The difference matters. Data collection tells you what’s happening. Intelligence analysis tells you what it means, how confident you should be, and what you should do about it.

Most competitive intelligence programs skip analysis altogether. They collect information, write reports, and miss the real insights.

Intelligence Thinking Framework

Here’s the structured analytical process that’s adapted from professional intelligence methodology for competitive strategy and our own experience:

Step 1: Define the Intelligence Question

Not “tell us about competitors.” Not “what’s happening in the market.”

A specific question tied to a specific decision.

“Should we invest $3M in enterprise security features based on Competitor X’s apparent pricing weakness?”

“Should we enter healthcare vertical given competitive dynamics?”

“Is Competitor Y’s growth sustainable or will they face financial pressure in 12 months?”

If your question is vague, your intelligence will be vague too. If your question is specific, you’ll get intelligence you can act on.

Most competitive intelligence fails during the initial stages of any project. Teams collect information broadly rather than drilling down on specific things. They write reports that answer questions nobody’s asking. All while ignoring questions that actually drive decisions.

Step 2: Establish What You Actually Know

Only write down the facts supported by the reliable evidence you have found.

Dont say “Competitor X is struggling.” That’s just interpretation.

Rather, “Competitor X offered three prospects in our pipeline lower prices than their published pricing in Q2.” That’s a fact, assuming your sales team reported accurately.

Not “The market is shifting to cloud.” That’s too broad a claim.

Look to be evidence-based, like “Four of our last six lost deals went to cloud-native competitors. Customer interviews in three of those deals cited cloud architecture as deciding factor.”

Listing only what you really know, with evidence to back it up, can be eye-opening. Much of what’s called knowledge is actually assumption, hearsay, or repeated interpretation that starts to feel true.

Step 3: Examine How You Know It

Every piece of information has a source. Sources have different reliability levels.

First-hand evidence: You tested the competitor’s product yourself. You saw their pricing page. You attended their conference presentation.

Documentary evidence: Published financial and competitive intelligence reports. Press releases. Patent filings. Job postings.

Corroborated information: Multiple independent sources saying the same thing.

Inferred information: You’ve concluded from indirect evidence.

Claimed information: Someone told you, but you haven’t verified it.

Most competitive ‘knowledge’ fits into these last two groups. Sales teams share what prospects tell them (claimed), and analysts draw conclusions from incomplete data (inferred).

Neither type of information is useless, but neither should be treated as fact.

A sales rep says: “Prospect told me Competitor X offered 40% discount.” That’s claimed information from a single source with potential motivation to exaggerate (prospect may have been using rival pricing as leverage).

Before you build strategy on that claim, ask: How do we know this? What’s the source? How reliable is that source? Is this corroborated?

Step 4: Identify What You Think You Know

This is the most dangerous category.

Information being treated as fact but actually containing assumptions, interpretation, or weak sourcing.

Example: “Competitor X is losing market share.”

Do you actually know this? Or did someone say it in a meeting six months ago and it’s been repeated until it became accepted truth?

Check: What evidence supports this claim? Is the evidence current? Is it from reliable sources? Could it be interpreted differently?

Most strategic mistakes come from this group: things the organisation thinks it knows but can’t prove, and assumptions that become accepted as facts just by being repeated.

We force every project team at Octopus Intelligence to complete five sentences before starting substantial research:

• We know… (verified facts with identified sources);

• We think we know… (information treated as fact but not fully verified);

• We don’t know… (explicit intelligence gaps);

• We need to know… (gaps that would change the decision);

• We would change our assessment if… (disconfirming evidence we should look for)

That last sentence is the most important analytical habit in competitive intelligence. It makes you decide what would prove you wrong before you start searching for evidence that supports your view.

Step 5: Map What You Don’t Know

Explicitly list your intelligence gaps.

Most companies skip this step. They focus on what they’ve gathered and present it as complete. But often, the gaps are more valuable than another page of data.

Example gaps:

“We don’t know Competitor X’s actual churn rate” “We don’t know whether their discounting is company-wide or segment-specific” “We don’t know their current burn rate or runway” “We don’t know what their product roadmap prioritises for next 12 months”

Listing gaps does two things: It prevents false confidence in your analysis. It identifies where further collection would be most valuable.

Step 6: Prioritise What You Need to Know

Not every unknown weighs equally.

Some gaps could change your decision completely. Others are interesting but irrelevant.

Priority Intelligence Requirements (PIRs) are the gaps that would actually change what you do.

“We need to know whether Competitor X’s discounting is segment-specific or company-wide” — this directly affects whether we interpret it as a strategic move or desperation.

“We need to know Competitor X’s employee count” — nice to know but probably won’t change our decision.

Focus your efforts on PIRs. Don’t spend time or resources on questions that won’t affect your strategy.

Step 7: Surface Your Assumptions

Write down every assumption you can think of.

Like that, you assume Competitor X is discounting because they’re losing market share.

You assume the enterprise segment values security features above all else.

You assume our product is technically superior.

Or market growth will continue at current rates.

Now ask: What happens to our strategy if each assumption is wrong?

If the strategy collapses when one assumption fails, that assumption is a critical vulnerability. It needs to be tested, not assumed.

Most strategies rely on five to ten untested assumptions. When strategies fail, it’s often because one of these assumptions was wrong. Companies that test their assumptions before investing come out ahead. Those that find out after spending $3M pay a high price.

Step 8: Develop Competing Hypotheses

Don’t fall in love with your first explanation.

Develop multiple plausible explanations for the evidence you’re seeing.

Competitor X is offering lower prices. But why?

• H1: They’re losing market share and discounting to retain customers. A sign of desperation.

• H2: They’re deliberately buying market share in a specific segment. A strategic investment.

• H3: They’ve reduced costs through new technology and are passing savings to customers. They have improved their finances.

• H4: The discounting is limited to specific customer segments or deal sizes. Is it targeted pricing?

• H5: They’re preparing for acquisition and need growth metrics. Creating a story.

Each hypothesis leads to a completely different strategic response.

If H1 is true: Attack aggressively while they’re weak. If H2 is true: Defend your segment, don’t chase theirs. If H3 is true: Investigate their cost reduction and determine if you’re at a structural disadvantage. If H4 is true: Understand which segments they’re targeting and why. If H5 is true: Prepare for a well-funded acquirer entering your market.

The same evidence can lead to five different explanations and five different strategies. Most companies pick H1 because it feels safest. They assume the competitor is weak and decide to attack, without checking if that’s actually true.

Step 9: Test Each Hypothesis Against Evidence

For each hypothesis, ask: What evidence would we expect to see if this hypothesis were true?

If H1 (losing market share) is true, we’d expect:

• Declining customer count (check their case studies, logos, references)

• Employee departures (check LinkedIn)

• Reduced marketing spend (check SimilarWeb, ad tracking)

• Defensive positioning in marketing (check messaging changes)

If H2 (buying market share) is true, we’d expect:

• Discounting in specific segments only (check across deal types)

• New capabilities targeting those segments (check product releases)

• Hiring in those segments (check job postings)

• Maintained investment elsewhere (no broad cost cutting)

Now look for evidence that contradicts each hypothesis, not just evidence that supports it.

If you find evidence that contradicts H1 (they’re actually hiring aggressively and investing heavily), H1 becomes less likely regardless of how much confirming evidence exists.

The hypothesis with the least disconfirming evidence is most likely correct.

This is called Analysis of Competing Hypotheses (ACH), the same method CIA analysts use to evaluate threats. It works for competitive intelligence because it helps you avoid confirmation bias.

Step 10: Search for Collection Bias

Are the sources available to you distorting the picture?

Your sales team sees competitor pricing (but only in deals they’re in). Your customers see competitor products (but only the features they evaluate). Public financial reports show revenue (but not segment breakdown). Former employees know internal dynamics (but their information is dated). Industry analysts report trends (but from their analytical framework).

Each source only sees part of the picture. No single source sees everything.

If your intelligence comes primarily from sales team reports, you’re seeing the competitive landscape through a sales lens. You might miss product development shifts, business alliances, or market approach changes that don’t show up in sales conversations.

Using a variety of sources helps reduce collection bias. When several independent sources with different viewpoints agree, your confidence in the conclusion grows.

Step 11: Consider Deception

Could someone be deliberately misleading you?

Competitors don’t just compete on products and pricing. They compete on information.

A competitor announcing “AI is central to our strategy” might be:

• Genuinely investing in AI.

• Trying to scare you into expensive AI investments

• Positioning for fundraising (AI narrative attracts capital)

• Distracting from their actual strategic moves

Public statements are meant for strategy, not for sharing real intelligence. Keep that in mind when you evaluate them.

We add a sixth sentence to our analytical framework specifically for competitive intelligence:

If we were the competitor, what would we want our rivals to believe?

This question introduces deception awareness into the analysis. It asks: Is the competitor’s public behaviour designed to make us react in a specific way?

If Competitor X wants you to believe they’re struggling (so you get complacent), discounting might be a deliberate signal rather than desperation.

If Competitor X wants you to believe they’re pivoting to enterprise (so you defend enterprise while they attack SMB), their announcements might be misdirection.

Most competitive intelligence treats competitor communications as fact. But that isn’t real intelligence; it’s just reading press releases.

Step 12: Define What Would Change Your Mind

This is the most powerful analytical discipline.

Before you conclude, define: What evidence would cause us to revise this assessment?

“We assess Competitor X is struggling. We would revise this assessment if: they raise new funding, hire aggressively, launch new products, or win deals in segments we expected them to lose.”

If you can’t explain what would make you change your mind, your conclusion is just a belief, not a real intelligence assessment. Beliefs don’t change with evidence. Intelligence assessments do.

Step 13: Red Team Your Conclusion

Give someone the job of attacking your prevailing conclusion.

Not to agree. Not to be constructive. To find every reason your assessment might be completely wrong.

“We think Competitor X is struggling because they’re discounting.”

The red team response was that three alternative explanations exist.

“Their discounting is sector specific and not company-wide. They have just hired 15 engineers and their LinkedIn posts show confidence. Not desperation. The sales team reporting discounts. But they be listening to exaggerated claims from prospects using competitive pricing as leverage.”

Red teaming can feel uncomfortable because it challenges the story everyone believes. That’s exactly why it’s so valuable.

Step 14: Adopt the Competitor’s Perspective

Ask: If I were this competitor, what would I be trying to achieve?

What constraints are they facing? What do they know that we don’t? What would be the rational move from their perspective?

Most companies analyse competitors from their own perspective. “We think they’re struggling because we’d be struggling if we did what they’re doing.”

But they’re not you. They have varied constraints, different information, different objectives.

A VC-backed competitor burning cash isn’t struggling. They’re executing a strategy where growth matters more than profitability. From their perspective, discounting to buy market share might be perfectly rational because growth rate determines their next funding round.

If you judge their strategy based on your own finances, you might misunderstand what they’re really doing.

Step 15: Develop Alternative Futures

Intelligence shouldn’t produce a single prediction. It should develop multiple plausible scenarios.

Most likely

Competitor continues current strategy for 12-18 months.

Optimistic

Competitor faces financial pressure and retreats from our segment.

Pessimistic

Competitor’s strategy succeeds, and they capture significant market share.

Disruptive

Competitor gets acquired by a larger player with more resources.

Each scenario needs a different strategy. If you plan for one outcome but something else happens, that’s how companies get caught off guard.

Step 16: Set Up Indicators and Warnings

For each scenario, determine what you’d expect to see beforehand.

If a competitor is succeeding

Increased hiring. Growing customer references—expanded marketing. Conference presence increasing.

If a competitor is struggling

Executive departures. Hiring freeze. Product stagnation. Customer complaints increasing. Marketing going quiet.

If a competitor is preparing for acquisition

Leadership meetings with potential acquirers. Strategic positioning changes. Growth acceleration regardless of profitability. PR narrative shifting to “market leader” positioning.

Review these indicators every week. When you notice them, you’ll know which scenario is unfolding before others do.

Step 17: Assess Source Reliability Separately from Information Credibility

A normally excellent source can deliver incorrect information. An unknown source can occasionally provide something accurate.

Ask both questions:

“How reliable is this source generally?” (track record, access, motivation) “How credible is this particular piece of information?” (consistency with other evidence, plausibility, corroboration)

A trusted former employee may be offering outdated information. A reliable source, potentially stale information. A prospect may tell you about accurate competitor pricing. That’s unknown reliability, but verifiable information.

Don’t trust information just because you know the source. Don’t dismiss information just because the source is unfamiliar.

Step 18: Distinguish Fact from Analytical Judgement

Your intelligence products should make clear the difference between:

We know

Facts with reliable evidence.

We assess

Analytical conclusions based on evidence and reasoning.

We believe

Judgements with limited evidence but supported by logic.

We don’t know

Acknowledged holes in understanding.

Most competitive intelligence presents everything with the same confidence level. “Competitor X is struggling and will face financial pressure by Q3” reads as fact when it’s actually analytical judgement based on limited evidence.

Being clear about these differences helps you avoid confusing uncertain opinions with facts.

Step 19: Assign Confidence Levels

Every conclusion needs to have a confidence indicator like this:

High confidence

• Multiple independent sources

• Strong corroborating evidence, and

• Hypothesis that has survived disconfirmation testing

Moderate confidence

• Some supporting evidence

• Limited disconfirmation testing, or

• Evidence from few sources

Low confidence

• Limited evidence

• Significant gaps, or

• Evidence that could support multiple hypotheses

“We assess with moderate confidence that Competitor X’s discounting is segment-specific rather than company-wide, based on pricing data from four deals and two customer interviews.”

Confidence levels encourage honesty. They prevent analysts from presenting uncertain conclusions as facts and help decision-makers decide how much to trust each assessment.

Step 20: Answer “So What?” and “What Next?”

Intelligence becomes useful only when connected to a decision.

So what

What does this assessment mean for our strategy? What opportunities or threats does it create?

What next

What action should we consider? What additional intelligence should we collect? What indicators should we monitor?

If your intelligence doesn’t answer ‘so what’ and ‘what next,’ it’s just an academic exercise, not a useful business tool.

The Intelligence Thinking Cycle

At Octopus Intelligence, we compress this into a repeatable analytical sequence:

This cycle never really ends. You don’t do it just once. As new evidence appears, repeat the process, update your assessments, adjust your confidence, and rethink your strategy.

Most companies do competitive intelligence as a project. Collect data. Write a report. File it.

Intelligence is a process, not a one-time product. If you don’t keep it going, your conclusions will soon be out of date.

Why This Matters More Than Most Companies Realise

The difference between data collection and intelligence analysis is the difference between:

“Competitor X is discounting” (data)

and

“We assess with moderate confidence that Competitor X’s discounting is limited to healthcare segment, driven by strategic vertical expansion funded by $20M credit facility, and represents deliberate market share investment rather than desperation. If correct, their pricing will stabilise within 6-9 months and they’ll have established healthcare positioning we’ll find difficult to challenge. We would revise this assessment if we see company-wide discounting, executive departures, or reduced product investment.” (intelligence)

The first tells you what’s happening. The second explains what it means, how confident you should be, what actions to take, and what could change the situation.

That’s the difference between guessing and knowing, between reacting and planning, and between wasting $3M on the wrong move or investing where it matters most.

What to Do This Week

Before your next decision, complete these sentences:

1. We know… (verified facts only)

2. We think we know… (assumptions treated as facts)

3. We don’t know… (explicit gaps)

4. We need to know… (gaps that would change the decision)

5. We would change our assessment if… (disconfirming evidence)

6. If we were the competitor, what would we want our rivals to believe? (deception awareness)

This exercise takes just 30 minutes. It will show you how much of your competitive “knowledge” is really just assumption, interpretation, or repetition.

At Octopus Intelligence, we apply the full intelligence thinking cycle to every competitive analysis we conduct.

We’re a UK, Dubai and US-based competitive intelligence agency built by former British military intelligence analysts serving companies like yours.

We don’t collect data and call it intelligence. We apply structured analytical methodology that separates facts from assumptions, tests hypotheses against disconfirming evidence, considers deception, and assigns confidence levels to every conclusion.

We help you make decisions based on assessed intelligence, not organised guessing.

Get in touch. Tell us about a competitive decision you’re facing.

We’ll apply the intelligence thinking cycle and show you the difference between what you know, what you think you know, and what you need to know before committing resources.

The gap between what you know, what you think you know, and what you need to know is where the big mistakes happen. Life-threatening mistakes for some intelligence analysts.

https://www.octopusintelligence.com/intelligence-thinking-cycle/

If you send your CI insights to strategy teams instead of the managers who make next week’s decisions, you’re making a report for reference, not a tool people can use.

The Window is Closing

When your quarterly competitive report finally reaches senior leaders, competitors have already changed, your sales team has modified on their own, and the market has moved. You’re just documenting the past instead of giving real intelligence.

Competitive results are only valuable for a few weeks. If a competitor hires your top channel partner’s account manager, that matters now, not in a quarterly report. If a rival starts offering net-60 payment terms in your main region, people need to know immediately.

Feed the Front Line First

Sales directors know which deals are currently at risk or going to be. Arguably, the sales Executives may even have a better idea if they aren’t scared of losing their jobs for saying so. Product managers know which features customers are demanding. Regional managers notice when competitor reps visit accounts they’ve managed for years.

These teams don’t want to long and boring slide decks. They want and need clear answers to questions like, “

• Why is Competitor X suddenly winning in manufacturing? or

• What’s behind their aggressive pricing in the Northeast?

Give them a brief, evidence-based answer within a day.

Build for Decisions, Not Just To be Lost In the Archives

Don’t waste your time on detailed competitor profiles that will be unread. Why not focus on questions that lead to real decisions? Things like should we match their pricing? Can they deliver what they guarantee? Where are they vulnerable right now?

Track which insights led to action and which were ignored. If no one changed their behavior after your last five reports, you may be answering the wrong questions or sharing information too late.

Talk to your internal customers every month. Ask sales what competitive intelligence could have changed their approach last quarter. Ask product teams what they wish they’d known six months ago.

Most CI teams measure outputs, like reports produced or competitors tracked. The best teams focus on outcomes, such as deals won, threats avoided, and new opportunities found.

Where Competitive Advantage Lives Now

You might be watching your competitors lose instead of win because you’re measuring the wrong things, and the real competition has already changed.

Most competitive intelligence teams focus on what competitors make visible, like features, pricing, marketing claims, and product launches. These are easy to spot but matter less now. The real advantage is often in areas your CI team isn’t tracking.

To explain my approach, I’ll use a method intelligence analysts have trusted for years: Analysis of Competing Hypotheses. List every possible reason for where competitive advantage is being built, then test the evidence for each. The explanation left after ruling out the others is the one to act on.

Why this matters now

Over twenty years or so ago, competitive advantage came from new features and strong marketing stories. Customers had less information. They had fewer choices. Now, competitors can see what you’ve built in days. Any feature advantage only lasts a few weeks.

So the main question has changed. If competitive advantage isn’t about features, price, or marketing anymore, where is it coming from? There are four possible areas, but most CI teams focus on just one.

The four futures

One

The first idea is that competitive advantage comes from speed.

The faster you build and adapt, the more likely you are to win. If a competitor releases features in two weeks and you take eight, they’ll probably lead the market. Watch product speed, engineering hires, and development pace. These are clear signs of an advantage.

Two

The second idea is that competitive advantage comes from knowing your customers and using advanced models.

The company that understands its customers best and can predict their behaviour will win, even if their product isn’t the best. It’s about knowing which customers matter and why.

Three

The third idea is that competitive advantage comes from strong operations and lower costs.

If a competitor can attract, serve, and keep customers for less because their costs are lower, they will win even if your features are similar. They can offer lower prices and still make a profit.

Four

The fourth idea is that competitive advantage comes from making it hard for customers to leave.

If a company builds deep integrations and becomes essential to a customer’s operations, they keep that relationship long-term. Being hard to replace matters more than speed.

Testing the evidence

Pick a competitor you’re actually losing deals to—not only the loudest one, but the one taking your customers.

Compare their product roadmap to how fast they move. Does quicker execution lead to more market share? Often, it doesn’t. Many fast competitors still struggle to grow. Moving quickly matters less than moving in the right direction.

Next, look at their customer retention and growth. Do their existing customers grow faster than yours? This connects to all four ideas. High retention and growth suggest strong data and lock-in. They know their customers well and have built systems that are hard to leave.

Check their costs and hiring compared to revenue. If they’re hiring more sales, customer success, and finance staff than engineers, they’re concentrating on growth over efficiency. If they hire more engineers, they’re building a leaner operation. A cheaper model works better when the market is shrinking, while a growth model fits when there’s plenty of investment.

Test switching costs by talking to your customers who stayed with them after thinking about using you. Ask directly: how hard would it be for them to leave? If they say, “very hard, we have built everything around their platform,” that competitor has lock-in. If they say, “we could leave if we wanted to,” they have a different advantage.

Also think about credibility and dependability. Does your competitor have a reputation that makes customers feel safe choosing them? Or are they always competing on features and price to stand out?

What the evidence reveals

When you compare competitors this way, you’ll notice a pattern. The winners aren’t always the fastest or cheapest. They’re the ones who offer something customers can’t easily replace.

Speed matters when you’re finding product-market fit. After that, it’s just expected. Efficiency is key when the market is tough and budgets are tight. But making it hard for customers to leave and being deeply integrated with them always matters.

Most intelligence teams focus on execution and pricing because those are easy to track. And it’s what the decision-makers are asking for. Not necessarily what they need to know, but hey? They often miss competitors who quietly make it expensive for customers to leave, using customer success, data systems, and integrations.

The competitor taking your market share isn’t the one releasing features fastest. It’s the one that keeps customers from leaving.

The signal to watch

Stop focusing on how fast competitors move. Start tracking how much their customers are growing within their accounts.

Look for competitors who keep adding new uses for their platform, making it harder for customers to leave. Watch if they’re building deeper integrations with your customers’ systems or hiring more customer success staff to keep clients loyal.

If your customer says, “we use them for X, but now they also handle Y and Z, and it would be a nightmare to replace them,” that competitor has already won, no matter what their product roadmap shows.

Your real advantage isn’t building faster or cheaper. It’s creating something your customer won’t leave, even if another option is quicker or costs less.

Don’t just pay attention to your competitors’ announcements. Focus on how they make it hard for customers to leave.

https://www.octopusintelligence.com/competitive-intelligence-reports-no-one-reads/

The Assumption That Breaks Scenario Planning

Most organisations treat scenario production as the deliverable. Build the scenarios, present the scenarios, job complete.

That assumption is where value is lost. A scenario is really a hypothesis about how things might unfold. If you do not attach a way to test strategies it, it is just an opinion, no matter how carefully you built it.

The goal of scenario planning is not just to describe possible futures. It is to help your organisation act faster as the future unfolds. This only works if you have already defined what ‘starting to happen’ actually looks like.

Why This Matters More Than It Used To

Planning cycles have not kept up with how quickly markets change. While annual strategies stay the same, things like competitor pricing, supply deals, regulations, and customer behaviour keep shifting.

If an organisation reviews its scenarios only once a year, it is always 12 months behind. A competitor who notices a change in the second month gets a ten-month head start.

The problem is not a lack of analysis. It is a lack of monitoring. Most companies can analyse, but they lack the means to track what is happening.

What Weak Scenario Practice Looks Like

You can spot a scenario exercise that will not make a difference by looking for four signs.

The scenarios do not have any indicators. Each future is only described as a story. No one has said what early evidence would indicate if a scenario were starting to unfold.

The indicators cannot be observed. When there are indicators, they are things like ‘competitor becomes more aggressive’ or ‘customer sentiment shifts.’ No one can actually collect these. They are just conclusions pretending to be signals.

There are no thresholds. Without them, indicators lead to endless debate. For example, three competitor price cuts in a quarter mean something specific. ‘Price pressure’ by itself means nothing.

No one is responsible for making the decision. When a scenario happens, everyone agrees it has happened, but then they start discussing who should act and what to do. That conversation should have taken place during the workshop, not during a crisis.

What Stronger Practice Looks Like

Good scenario work flips the focus. Spend less time on detailed stories and much more on figuring out how to detect each scenario early. There is a simple test for an indicator: Could a skilled researcher, with just the indicator written down and no extra information, tell if it has happened? If not, it is not a real indicator.

Good indicators are usually about actions, not statements. What a company does costs them something. What they say does not.

Think about the difference in practice. If a competitor says they plan to enter your market, that is talk. But if they open a facility in your area, hire sales staff who know your industry, apply for the right permits, and set up distribution, those are real actions. The second set is costly to fake, while the first costs nothing. Hiring data is especially useful because job ads are public, dated, specific, and written by people who need to describe the job clearly. A series of job postings reveals which skills a company is building before those skills appear in the market.

Grounding This in Real Market Behaviour

Take the move to electric vehicles in the UK. From 2020 onwards, an automotive supplier running scenarios about the speed of that transition had a choice about what to monitor.

The weak version tracked commentary about electrification, which was abundant, contradictory and free. The stronger version tracked committed actions with dates attached. Manufacturer announcements of specific plant conversions. Battery facility planning applications. Regulatory milestones, including the UK Government’s ZEV mandate, which set out required percentages of zero-emission vehicle sales by manufacturer by year. Charging infrastructure connection approvals. Supplier contract awards.

These actions are easy to see, have dates, and can be counted. They also changed over time, which is important. Suppliers who watched capital commitments rather than opinions saw the direction and speed of change, had concrete evidence, and were able to adjust their investments based on facts, not feelings.

We assess, based on the pattern of what is monitorable, that capital commitment indicators lead public commentary by a meaningful margin in most industrial transitions. That is a judgement rather than a verified measurement, and we would state it as such to a client.

Building the Indicator Layer

Follow these steps in order.

For each scenario, ask what would be true at the very beginning, not when the scenario is fully happening. What would be true in the first ten per cent? Early indicators can be unclear, and that is fine. But they must be observable.

Turn each indicator into a question you can collect data on. Write it as a concise instruction a researcher could use right away. For example, ‘Has Competitor B applied for planning permission at any UK site in the last six months?’ is something you can check. ‘Is Competitor B expanding?’ is not.

Set a threshold for each indicator. Decide how many times something must happen, and over what period, before it counts. The threshold does not have to be perfect, but everyone should agree on it ahead of time, so you are not debating it under Identify the decision and who will make it. For each threshold, write down what the organisation will do when it is crossed and who has the authority to act. This step is often missed, but it is what makes the rest of the work matter.

Set a regular review schedule and stick to it. Review monthly for fast-changing markets and quarterly for slower ones. Keep the review short and focus on one question: Which indicators have changed?

Keep track of indicators that have not changed. If you have been watching closely and see no movement, that is still useful information. If a scenario’s indicators remain flat for four quarters, downgrade it and allocate your analysis resources in other areas.

Risks and Limitations

Indicator-based monitoring has real weaknesses, and you should be aware of them before you commit to this approach.

Competitors who know what you are watching can try to manipulate indicators. They can intentionally change hiring patterns, patent filings, or public statements. That is why you should use several different types of evidence, not just one.

Thresholds can give a false sense of certainty. When a threshold is crossed, it means you should investigate, not that you have a definite answer. If your organisation treats every indicator movement as proof, you risk acting on noise.

Indicator sets become outdated. Markets change, competitors act differently, and an indicator that worked two years ago might not matter now. Review your indicator set every year, separate from your regular monitoring.

Some changes really do happen without early public signs. Monitoring indicators helps reduce surprises, but it cannot eliminate them entirely. Anyone who says otherwise is not being honest.

Where Octopus Intelligence Fits

Octopus Intelligence is a competitive and market intelligence agency founded by former British military intelligence analysts, offering competitive intelligence services to B2B organisations across SaaS and technology, manufacturing, financial services, healthcare, private equity and the MENA region.

Our background is especially useful for solving the indicator problem. Setting indicators, planning how to collect them, and deciding on thresholds are core intelligence skills, not just strategy consulting techniques. Most scenario exercises miss these steps. This organisation is two ways on this. We build the indicator layer beneath existing scenarios, converting narrative futures into collection requirements with thresholds and owners. And we run the collection itself, including primary research that finds evidence not available in public sources, so the monitoring does not fall on a strategy team that lacks capacity for it.

This difference is important. Desk research finds information that is already published. Primary research uncovers what people in the market know but have not written down. Early indicators are often found through primary research.

Closing Argument

The real value of scenario planning is not in the scenarios themselves. It is in the speed advantage you get by spotting which scenario is happening before your competitors do.

That advantage comes entirely from having good indicators. If you build scenarios missing them, you have just spent two days making a document that describes uncertainty yet does not help reduce it.

Look at your last scenario exercise. Look for indicators. If there are none, or if no one outside the room could collect them, the exercise is not finished yet.

Frequently Asked Questions

What are scenario planning indicators?

Scenario planning indicators are observable events or measurements that show a particular scenario is beginning to occur. Each indicator must be specific enough that a researcher could verify whether it has occurred. Good indicators track committed actions, such as recruitment, capital investment, or regulatory filings, rather than statements of intent.

Why does scenario planning fail in most companies?

Scenario planning most often fails because the exercise ends when the scenarios are written. Without indicators attached to each scenario, nobody can tell which future is arriving until it has already arrived. The analysis is usually sound, and the detection layer is usually missing.

How many indicators should each scenario have?

Between three and six per scenario works for most organisations. Fewer than three leaves you dependent on a single type of evidence that a competitor could exploit. More than six creates a monitoring load that strategy teams abandon within two quarters.

What is the difference between an early warning indicator and a KPI?

A KPI measures your own performance and looks backwards. An early warning indicator measures external change and looks forward. Organisations frequently monitor internal KPIs closely and external indicators only marginally, which is why competitive shifts register late.

How often should scenario indicators be reviewed?

Monthly in fast-moving markets such as software and consumer technology, quarterly in slower industrial and regulated markets. The review should focus on which indicators have moved and whether any threshold has been crossed, not on rewriting the scenarios.

Can we do indicator monitoring in-house?

Many organisations can handle the publicly available portion, including hiring data, regulatory filings and company announcements. The difficulty is sustaining it alongside operational work and reaching evidence that is not published anywhere. That second category usually requires primary research.

What does Octopus Intelligence do?

Octopus Intelligence is a competitive intelligence agency founded by former British military intelligence analysts. We provide competitor analysis, market intelligence, B2B mystery shopping, and primary research for B2B organisations, using human sources alongside open-source material to answer questions that desk research cannot.

When should a company bring in external intelligence support for scenario work?

Bring in support when your scenarios exist, but nothing is being monitored against them, when the indicators you need concern private companies that publish little, or when internal monitoring has been attempted and lapsed. External support also helps where the assessment needs to be independent of the team that built the plan.

Which industries does Octopus Intelligence support?

We work with B2B organisations across SaaS and technology, manufacturing, financial services, healthcare, private equity, and corporate development in the UK, the United States, and the MENA region.

How do you monitor a competitor that publishes almost nothing?

Private companies leave behind observable traces even when they publish little, including recruitment activity, planning and regulatory applications, partner and distributor arrangements and supplier relationships. Primary research with people who deal with that competitor commercially fills the remaining gaps. This is a substantial part of the work we do.

We are Octopus. The Global People-Powered Competitive Intelligence Agency.

Outsmart your competition. Make the unknown known. Octopus helps you gain clarity in complex markets. With clients and tentacles around the world, we deliver sharp, actionable competitive intelligence through a blend of deep primary (HUMINT) and secondary research. If you’re looking to make smarter decisions, beat the competition, and reduce uncertainty, we’re the partner you want on your side.

https://www.octopusintelligence.com/scenario-planning-indicators-the-missing-half-of-every-scenario-exercise/

The Competitor “Threat” That Didn’t Exist

In 2024, we spoke with a SaaS company that was sure its main competitor had a complex plan to move upmarket and steal its enterprise deals.

Here’s what they “knew”:

• The competitor hired three enterprise sales reps.

• Competitor launched “enterprise-grade security features”.

• The competitor won three enterprise deals in Q2.

• The competitor announced enterprise partnerships.

The story made sense. Their strategy seemed clear. The threat looked obvious.

But that wasn’t what was really happening.

Instead of just looking for patterns in surface evidence, we used a structured analysis. We listed out different possible explanations:

Hypothesis A

The competitor is executing a serious enterprise strategy to displace us.

Hypothesis B

The competitor is testing the enterprise market with limited commitment.

Hypothesis C

The competitor is chasing vanity wins and enterprise partnerships without a sustainable business model.

Hypothesis D

The competitor had one customer request and oversold it as an enterprise strategy.

Download a ACH template here.

Next, we gathered evidence for each hypothesis. Rather than looking for proof of what we already believed, we searched for evidence that could show each hypothesis was wrong.

We found that the three enterprise sales reps hadn’t closed any deals yet. Two of the three enterprise wins actually came from the existing sales team. The so-called “enterprise-grade security” was just a new name for features they already had. The partnerships were non-exclusive and weren’t bringing in customers. Most importantly, there was no hiring in customer success, implementation, or enterprise support, all of which are needed to serve enterprise customers well.

When we used structured analysis instead of relying on confirmation bias, we revised our hypothesis. The competitor wasn’t really following an enterprise strategy. They were just testing it with minimal commitment because their main business was under pressure to grow. This was the most likely explanation based on all the evidence.

Once we used structured analysis, the idea of a “sophisticated threat” faded away.

My client was preparing to defend against an enterprise threat that didn’t exist. In the process, they missed the real problem that their own growth was slowing for the same reasons the competitor was venturing into new markets.

What is ACH (And Why Most Companies Get It Wrong)

Analysis of Competing Hypotheses is a methodical process for evaluating evidence and lessening bias in your analysis.

At Octopus Intelligence, we’re a competitive intelligence agency based in the UK, Dubai and the US, founded by former British military intelligence analysts. ACH is at the core of our work because in military intelligence, being wrong about threats isn’t an option.

Here’s how ACH works:

Standard Analysis (What Most Companies Do)

1. Develop a hypothesis you believe in

2. Look for evidence supporting it.

3. Present that evidence as analysis.

4. Conclude that your hypothesis is correct.

The problem is confirmation bias. You tend to notice what you expect, see unclear evidence as supporting your own view, and often ignore other possible explanations.

Analysis of Competing Hypotheses (ACH)

1. Develop multiple hypotheses, including ones you don’t believe in

2. For each piece of evidence, ask: Does this support Hypothesis A, B, C, or D?

3. More importantly, does this evidence disconfirm any hypothesis?

4. Evaluate which hypotheses have the least disconfirming evidence.

5. Finish with the hypothesis that best explains all the evidence, not just confirming evidence.

This change matters. ACH pushes you to look for evidence that could disprove your preferred hypothesis, not just evidence that supports it.

Why ACH Reveals What’s Really Happening

Most competitive intelligence efforts fail because they rely on confirmation bias.

You see competitor hiring and assume it confirms your hypothesis about their strategy. You see them winning deals and assume it confirms your fears about their positioning. And you build a narrative and find evidence supporting it.

ACH requires a different approach: ask what evidence would disprove this hypothesis? What would I need to see to make this hypothesis less likely?

When you ask these questions honestly, your original story often doesn’t hold up.

Example of the “Aggressive Pricing” Hypothesis

Hypothesis: “Competitor is winning deals through aggressive pricing”

Confirming evidence:

• The competitor announced lower pricing.

• You lost three deals to them at a lower price point.

• The sales team reports they’re heavily discounting.

This evidence seems to confirm the hypothesis, and you may decide you need to match their pricing.

But ACH makes you ask different questions. What evidence would go against the aggressive pricing hypothesis?

• High prices in specific segments could indicate that selective pricing, rather than aggressive across-the-board pricing, is being used.

• Customers switching away despite lower pricing suggests price isn’t the winning factor.

• Competitor not discounting beyond what’s economically sustainable probably means pricing discipline, not aggression)

• A win rate that doesn’t improve despite price cuts could suggest that price wasn’t the limiting factor.

When you consider these disconfirming questions, you start to see a different picture. Perhaps the competitor is only discounting in markets where they have a cost advantage. Maybe they’re losing customers they discounted to because those customers aren’t good fits. Maybe they’re only winning when they also have other advantages besides price.

A different hypothesis is that the competitor is using selective pricing in specific segments where they have a cost advantage, rather than pursuing aggressive, across-the-board price competition. This leads you to adopt a new strategy: focus on the segments where you are strong and avoid a price war.

How to Apply ACH to Competitive Intelligence

Step 1: Identify the Core Question

Not: “What are competitors doing?” But, “What is actually happening in our market and why is it happening?”

Specific questions ACH works best for:

• Why is this competitor growing faster than others?

• What’s driving the market shift we’re seeing?

• Will this competitor sustain their advantage, or is it temporary?

• What’s the real reason we’re losing these specific deals?

• Is this market trend structural or cyclical?

Step 2: Develop Competing Hypotheses

Generate 3-5 hypotheses that could explain the evidence you’re observing. Include:

• Your preferred hypothesis (what you believe)

• Opposite hypothesis (what would contradict your belief)

• Alternative hypotheses (other explanations that fit some evidence)

• Null hypothesis (nothing significant is happening, it’s noise)

Why is Competitor X winning enterprise deals?

It could be hypothesis A

They’ve built genuinely superior enterprise capabilities.

Hypothesis B

They’re chasing vanity wins without sustainable economics.

Hypothesis C

Enterprise buyers are just testing alternatives; they’re not switching in the long term.

Hypothesis D

They have one enterprise customer with an outsized influence, driving referrals.

Step 3: Gather Evidence for Each Hypothesis

For each piece of evidence, determine which hypothesis it supports or disconfirms.

Don’t just ask, “Does this support my preferred hypothesis?” Try to ask which hypothesis does this best explain?

Example evidence:

• Competitor hired three enterprise sales reps → Supports A and B (both need sales team)

• Competitor’s enterprise customers not renewing → Disconfirms A, supports B

• Competitor’s enterprise deals all came from one customer referral → Supports D.

• Competitor’s enterprise team is remote-based without on-site support capacity → Disconfirms A (suggests lack of commitment)

Step 4: Identify Disconfirming Evidence

This is the key step that most analyses overlook.

For each hypothesis, ask what evidence would prove this hypothesis wrong?

Then follow up by asking if we have that evidence to back this up?

If you have disconfirming evidence, the hypothesis is less likely to be correct.

Step 5: Evaluate Hypotheses Against Disconfirming Evidence

Don’t judge hypotheses by how much supporting evidence they have.

Instead, judge them by how little disconfirming evidence there is.

The hypothesis with the least disconfirming evidence is probably the right one.

Example final assessment:

Hypothesis A: 3 pieces of disconfirming evidence = unlikely
Hypothesis B: 1 piece of disconfirming evidence = more likely
Hypothesis C: 0 pieces of disconfirming evidence but weak confirming evidence = possible
Hypothesis D: 2 pieces of disconfirming evidence = unlikely

So, hypothesis B is most likely because it has the least disconfirming evidence and enough support.

Real Examples of ACH Revealing Truth

A fintech company was convinced that a well-funded competitor was ready to become the market leader.

Hypothesis A (preferred)

“Competitor is building genuine competitive advantage and will become market leader”

Hypothesis B:

“Competitor is burning cash unsustainably and will hit financial problems”

Hypothesis C:

“Competitor and we will coexist in different segments”

Evidence analysis

Confirming A

Large funding round, impressive brand, good press coverage, winning some enterprise deals

Disconfirming A

Customer acquisition cost is 3x higher than ours; unit economics are worsening; customer churn exceeds new customer acquisition; burning $50M annually with no path to profitability.

When you weigh disconfirming evidence, Hypothesis B becomes more likely.

Follow-up question

How long can this continue?

Evidence: 18 months of remaining runway at current burn rate.

Conclusion

The competitor will likely face financial pressure in 12-18 months.

Result and actions

Don’t panic about their growth. Instead, prepare for when their growth slows and they need to change strategy. In the end, the competitor faced a cash crisis in month 14, laid off 40% of its team, and shifted its focus to profitability. The company that used ACH was ready and grew its deals by 200%.

Common Mistakes in Applying ACH

Straw Man Hypotheses

You set up alternative hypotheses that are obviously wrong, so your preferred hypothesis looks good.

The wrong hypothesis is that the competitor has no strategy and is just doing things randomly.

A better hypothesis is that the competitor has a focused strategy. An alternative hypothesis should be realistic, not far-fetched. Hypotheses need to be plausible, not ridiculous.

Confirmation Bias in Evidence Gathering

You look for evidence supporting your preferred hypothesis, but skip seeking disconfirming evidence.

Fix this by actively searching for evidence that would disconfirm each hypothesis. Asking what I would have to see that would prove this hypothesis wrong? Then conduct that search intentionally.

Weighting All Evidence Equally

Some evidence is stronger than others. Weak evidence shouldn’t count as much as strong evidence.

For example, weak evidence is that the competitor announces a strategy (they might be bluffing)
There is strong evidence that the competitor is actually hiring and product development corresponds to the announced strategy (they’re committing resources)

Give more importance to evidence from strong, reliable sources.

Ignoring Absence of Evidence

What’s not happening can be as important as what is happening.

Example:

A hypothesis that the competitor is serious about the enterprise market.

Disconfirming evidence is that they haven’t hired an enterprise customer success team, an enterprise support infrastructure, or implementation specialists.

If the expected support infrastructure is missing, that’s strong evidence against the hypothesis.

Changing Hypotheses Mid-Analysis

You start with one set of hypotheses, then when analysis doesn’t support your preferred hypothesis, you create new hypotheses.

So decide on your hypotheses before you start gathering evidence. Only change them if the evidence clearly doesn’t fit any of your original ideas.

The ACH Framework for Competitive Intelligence

Here’s the structured ACH Framework process

Question Definition (Week 1)

Define the specific question you’re trying to answer:

• Why is Competitor X winning in this segment?

• What’s driving the market shift we’re observing?

• Will this competitive threat sustain or fade?

• What’s going to happen in our market in the next 18 months?

Hypothesis Development (Week 1)

Generate 3-5 competing hypotheses. Include your preferred hypothesis and opposing hypotheses.

Write down what each hypothesis would predict if it were true.

Evidence Gathering (Weeks 2-3)

For each hypothesis, what evidence would support it and what evidence would disconfirm it?

• Collect 15-20 customer interviews.

• Do some Competitor product analysis.

• Read market research and analyst reports.

• Look at financial and operational indicators.

• Analyse hiring and partnership patterns

• Maybe do some win-loss analysis.

Evidence Analysis (Week 4)

For each piece of evidence, isolate and understand which hypothesis it supports. And which hypothesis does it disconfirm and determine how strong this evidence is? Then create a matrix detailing the hypotheses, evidence, and disconfirming power.

Hypothesis Evaluation (Week 4)

Score each hypothesis on disconfirming evidence:

• How many pieces of disconfirming evidence does each hypothesis have?

• How strong is the disconfirming evidence?

The hypothesis with the least disconfirming evidence is most likely true.

Conclusions and Actions (Week 5)

• What is most likely happening based on evidence analysis?

• What should we do differently based on this conclusion?

• What evidence would we need to see that would change this conclusion?

Set up a system to track that evidence going forward.

Why ACH Is Essential for MENA Markets

Octopus Intelligence expanded into MENA through our Dubai office because regional markets are more prone to unexamined hypotheses than Western markets.

MENA companies commonly operate with implicit hypotheses about:

• How will Western competition enter regional markets?

• What regulatory changes will happen

• How local customers will respond to new products

• What pricing approaches will work

These hypotheses are often wrong because they rely on Western patterns that don’t correspond to local contexts.

ACH forces examination of regional assumptions:

MENA-Specific Hypothesis Testing:

Question: “Will Western SaaS companies dominate MENA markets?”

Hypothesis A (assumed true): “Western companies will replicate Western success in MENA”

Hypothesis B: “MENA customers have different needs that require local solutions”

And hypothesis C: “Regional regulatory and data sovereignty requirements create barriers Western companies can’t easily overcome”

When you gather disconfirming evidence for Hypothesis A:

• Data localisation requirements: Western companies don’t prioritise

• Customer choices for regional companies with local teams

• Pricing sensitivity that makes Western pricing models uncompetitive

• Regulatory complexity that Western companies underestimate

Hypothesis A seems less likely, while Hypothesis C becomes more likely.

Strategic response: Focus on building a regional advantage that Western companies can’t easily copy, instead of trying to imitate their business models.

How to Start Using ACH Tomorrow

1: Pick One Competitive Question

Don’t try to use ACH for everything at once. Choose one question you’re truly unsure about:

• Why is Competitor X growing faster than we are?

• Will this market shift be permanent or temporary?

• Should we be worried about this threat from an adjacent category?

2: Develop Three Hypotheses

Your preferred hypothesis + one opposite hypothesis + one alternative hypothesis

Write them down specifically.

3: List Disconfirming Evidence

For each hypothesis, what would you need to see that would prove it wrong?

Write those down.

4: Search for Disconfirming Evidence

Actively look for evidence that would disconfirm each hypothesis, not just evidence supporting it.

5: Weight Disconfirming Evidence

Which hypothesis has the least disconfirming evidence?

That’s the conclusion that is most likely true.

6: Act on the Conclusion

What does this most likely hypothesis suggest you should do?

Use that insight to shape your strategy.

The Power of Intellectual Humility

Here’s what ACH teaches that most competitive intelligence misses:

Being remarkably certain is risky. Once you’re sure about your competitive hypothesis, you stop looking for evidence that could prove you wrong. You stop asking tough questions and start seeing unclear evidence as support for your own story.

ACH encourages intellectual humility. You keep your hypotheses flexible, look for evidence that could prove you wrong, and update your conclusions when new evidence comes in.

This kind of humility gives you a real competitive advantage. Companies that are too confident in their strategy often miss market changes. Those who stay humble and open to new evidence modify their strategy when needed.

Once you become certain, you stop thinking critically. ACH keeps you thinking, even when it’s uncomfortable.

This kind of discipline is important in markets where understanding what’s really happening matters more than mere confidence.

https://www.octopusintelligence.com/how-using-analysis-of-competing-hypotheses-shows-whats-really-happening-in-your-market/

Most people focus on copying what their competitors do well. But you can often learn more by looking at where they went wrong. Here’s how you can get ahead by learning from your competitors’ mistakes before you make the same ones.

They put $3 million into engineering, planned for eighteen months, hired a VP of AI, and did all they believed was needed.

But they never stopped to ask, “Has any competitor already launched AI content features?” If they had, they would have found out:

“Yes, three of them did last year.”

“How’s that working for them?”

Long pause. “We haven’t really looked at that.”

Spend your time looking deeply at these launches

If they had spent a few weeks looking into those competitor launches, trying out their AI features, scanning customer reviews, talking to prospects who had tested those features, and following public discussions and support forums,

They would have seen that all three competitors launched AI content generation with a lot of hype—press releases, conference demos, and big sales pushes.

Eighteen months later, less than 8% of customers were using these features. Review sites were full of complaints: “The AI writes generic content that needs complete rewrites.” “It’s faster to write from scratch than edit AI output.” “Our brand voice gets lost.”

All the competitors made the same mistake. They built AI that created content nobody wanted. And they focused on speed but ignored quality and brand consistency, so the results weren’t useful.

They were about to make the same $3 million mistake themselves.

But their competitive intelligence work changed their strategy. Instead of building AI to generate content, they built AI to improve human-written words for SEO, readability, and conversion, while keeping the brand voice.

This was a different problem and a different use of AI, and they learned it all from watching competitors. The feature launched six months later at just a quarter of the first development cost. In the first quarter, 64% of customers adopted it, making it the second most mentioned feature on sales calls.

They didn’t avoid failure because they were smarter. They avoided it by looking at what had already failed and learning from those mistakes.

Why Competitor Failures Could Be More Valuable Than Competitor Successes.

Every company studies competitor successes.

“Competitor X grew 200% with product-led growth. We should do that too.”

“Competitor Y raised a huge round with their vertical SaaS positioning. Let’s verticalize.”

“Competitor Z is winning with AI features. We need AI.”

Copying what works for others can seem like a shortcut. But you only see the results, not the context, skills, or conditions that made it work for them, which might not apply to you.

Competitor failures are different. They show you:

What doesn’t work even when well-executed?

Sometimes strategies fail not because they were done badly, but because the basic idea behind them was wrong.

What requires specific capabilities or conditions you might not have?

A strategy that failed for Competitor X might have worked if they had different resources, better timing, or a different market position.

What customers actually reject versus what they say they want.

Challengers often build features that customers ask for, but then those features go unused. This shows the difference between what customers say they want and what they actually use.

What traps exist that aren’t obvious until you step into them?

The first companies to try something often run into hidden problems. You can learn where these problems are by watching what happens to them.

At Octopus Intelligence, we’re a UK and US-based competitive intelligence agency built by former British military intelligence analysts. One of the most valuable services we provide is systematic analysis of competitor failures. Not to mock them, but to extract lessons that prevent our clients from repeating expensive mistakes.

The Types of Competitor Failures Worth Studying

Not all failures are the same. Some show problems with strategy, while others focus on how things were done.

Here’s what we look for:

Type 1: Well-Resourced Failures

When a competitor with plenty of money, skilled people, and time still fails at something, it means something important.

If a competitor raised $20 million, hired a team of experts, spent two years building, and still failed, that says something about the market itself, not just how well they executed.

They tracked enterprise collaboration software competitors in 2022-2023. Three companies with significant funding tried to build “Notion for Enterprise.” All three failed to get meaningful traction.

Why? Enterprise buyers didn’t want flexible document tools. They wanted a structured workflow with compliance and security. The “Notion for Enterprise” positioning was solving a problem enterprise customers didn’t have.

This helped them and others avoid making the same expensive mistake.

Type 2: Repeated Failures Across Multiple Competitors

When a number of competitors try the same thing, and all fail, it usually points to a bigger problem, not just bad luck.

Five different project management companies tried to add time-tracking features between 2020 and 2023. All five saw low adoption. All five eventually de-emphasised or removed the features.

This pattern showed that project management users and time-tracking users have different needs and ways of working. Trying to combine both led to a poor experience for everyone.

Competitors kept adding time tracking because their customers asked for it. But when it was available, those same customers didn’t use it. This showed a gap between what people say they want and what they actually do.

Type 3: Reversals

When competitors launch a strategy with certainty and then change direction, it’s a sign that something important has happened. We followed a competitor who announced a big move into the enterprise market in 2022, hired more people, expanded their sales team, and reorganized their product plans.

Eighteen months later, they quietly changed back to mid-market. Laid off the enterprise team. Stopped talking about enterprise positioning.

What happened? We interviewed people who’d left that company. They tried enterprise, discovered their product architecture couldn’t meet enterprise security requirements, found that rebuilding would take 2+ years, and retreated.

Our client was considering the same upmarket move. That competitor’s failure saved them from a two-year, multi-million-dollar strategic dead end.

Type 4: Feature Launches That Disappeared

When competitors ship features with fanfare, then quietly deprecate them, you learn what seemed like a good idea but wasn’t.

We tracked SaaS competitors across multiple categories. Common pattern: Competitor launches AI feature with big announcement. Six months later, it’s buried in settings. Twelve months later, it’s removed from marketing materials. Eighteen months later, it’s deprecated.

This pattern shows that some features sound good in meetings but don’t solve real problems or end up causing more trouble than they’re worth.

How to Extract Intelligence from Competitor Failures

Here’s the process we use to analyse competitor failures for clients:

Step 1: Identify Failures Worth Studying

Not every competitor failure deserves deep analysis. Focus on failures:

• In areas you’re considering investing in

• By competitors with similar resources or market status

• That seems surprising (well-funded, well-executed, still failed)

• Repeated by multiple competitors

Build a list of the 5-10 most relevant competitor failures from the past 2-3 years.

Step 2: Reconstruct What They Actually Did

Document the competitor’s approach:

• What exactly did they build or try?

• How much did they invest (team size, timeline, resources)?

• How did they position it to customers?

• What customer problem were they trying to solve?

Use press releases, product announcements, archived website versions, LinkedIn hiring patterns, and customer-facing materials to reconstruct their approach.

Step 3: Identify Why It Failed

This is the critical step. Don’t assume you know why it failed. Investigate.

Customer interviews

Talk to people who evaluated or tried the failed initiative. Why didn’t it work for them?

Former employee intelligence

People who worked on the failed project often have clear perspectives on what went wrong.

Usage and adoption data

Look for public signals—customer reviews, support forum discussions, and feature mentions that decline over time.

Financial or operational signals

Did the competitor cut resources, lay off teams, or reallocate budget away from this area?

The goal is to understand the root cause, not just the surface symptoms.

Step 4: Extract Generalizable Lessons

Some failures are execution problems specific to that competitor. Some reveal wider market truths.

Distinguish between:

“This failed because Competitor X executed poorly” (less valuable—you might execute better)

“This failed because the underlying assumption was wrong” (very valuable—you’d make the same mistake)

“And this failed because it requires capabilities/conditions Competitor X didn’t have” (valuable if you can assess whether you have those capabilities)

Step 5: Test Whether the Lesson Applies to You

Just because something failed for a competitor doesn’t mean it would fail for you.

Ask:

• Do we have different capabilities that might change the outcome?

• Are we serving different customers who might respond differently?

• Has market timing changed in ways that make this more viable now?

• Did they fail for reasons we can avoid?

Sometimes the lesson is to avoid the approach. Other times, it’s to try a different way.

Real Examples of Learning from Competitor Failures

Example 1: The Freemium Model That Didn’t Work

A B2B SaaS company was planning to launch a freemium tier. “All our competitors have freemium. We need it too.”

We analysed those competitor freemium offerings. Found:

• Three competitors launched freemium 2-3 years ago.

• All three had 15%+ conversion from free to paid users in Year 1

• All three were now below 3% conversion.

• The three were quietly limiting free-tier features or considering shutting down the free tier.

Why the decline? Free users attracted tire-kickers rather than qualified buyers. Support costs for free users exceeded revenue from conversions. Free tier became a competitor’s selling point: “Unlike them, we don’t have a crippled free version.”

So, the lesson here for this client was that freemium works at first, but over time, it attracts the wrong users and increases support costs.

Our client skipped freemium. Offered 30-day trials with high-touch onboarding instead. Higher conversion rate, better customer fit, lower support costs.

Example 2: The Mobile App Nobody Used

A project management company planned to invest $2M building native mobile apps.

They found:

Six competitors had mobile apps
Average rating: 2.4 stars
Common complaints: “Missing key features,” “Syncing issues,” “Slow and buggy”
Most telling: Competitors weren’t investing in mobile improvements despite low ratings

They investigated further. Interviewed customers who’d downloaded competitor mobile apps.

Mobile was for quick checks and updates, not real work. Users wanted lightweight read/write access, not full feature parity with the desktop.

Competitors built mobile apps with too many features for mobile use, but still too limited for serious work. It was the worst of both worlds.

They ended up building a minimal mobile app focused on notifications, quick updates, and task checking. 1/4 of the development cost. 4.2-star rating. 80% of users who downloaded it were still active six months later.

They avoided failure by understanding why their competitors’ approaches didn’t work.

Example 3: The Enterprise Push That Failed

A marketing software company wanted to move upmarket to the enterprise market.

We analysed three competitors who’d tried the same move in previous years:

Competitor A

Hired an enterprise sales team, failed to close deals, and laid off the team after 18 months

Competitor B

Rebuilt product for enterprise, existing customers complained about added complexity, and had to maintain two product versions.

Competitor C

Acquired an enterprise client base through M&A, couldn’t retain acquired customers, wrote down the acquisition

Three different approaches. All failed.

But why? We interviewed enterprise prospects in this category. They had established vendors (Marketo, Eloqua, Adobe) and weren’t looking to switch unless forced by those vendors failing or being acquired.

The market wasn’t actually open to new enterprise entrants in marketing automation. The window had closed 5-7 years earlier.

Our client stayed mid-market and dominated that segment instead of chasing enterprise deals that weren’t actually available.

The Questions That Reveal Failure Patterns

When analysing competitor failures, these questions reveal the most valuable intelligence:

1. What did customers say they wanted versus what they actually used?

This reveals stated versus revealed preferences. Competitors build what customers request in surveys, only to find that nobody uses it in practice.

2. What seemed like a good idea in planning that broke down in execution?

This uncovers hidden complexity or links people didn’t see. Strategies that sound great in meetings often fail because of practical business challenges.

3. What changed between launch and failure that invalidated the approach?

This reveals whether timing was wrong, market conditions shifted, or the approach was fundamentally flawed.

4. What capabilities did this require that the competitor didn’t have?

This reveals whether failure was due to a bad strategy or insufficient capabilities to execute a good strategy.

5. Would we make the same mistake if we tried this?

This is the test. Are we different enough from this competitor that we’d avoid their failure mode, or would we hit the same problems?

How to Get Intelligence on Competitor Failures

Competitor failures aren’t always public or obvious. Here’s how we gather this intelligence:

Monitor Product Changes

Track when features disappear from competitor websites, get deprecated, or stop being mentioned in marketing materials.

Use archive.org to compare competitor websites over time. Features that were prominent and then disappeared signal failures.

Read Customer Reviews Over Time

G2, Capterra, and TrustRadius reviews reveal when customers mention features that don’t work or initiatives that disappointed them.

Watch how reviews change over time. If a feature launches with zeal but reviews later turn negative, something went wrong.

Track Employee Departures

LinkedIn shows when teams get laid off or when leaders leave. Sudden departures often follow failed initiatives.

Connect with former employees who worked on failed projects. They often have a clear perspective on what went wrong once they’re no longer at the company.

Analyse Competitor Earnings Calls and Updates

Public companies discuss failed initiatives on earnings calls, often couched in terms such as “strategic reverse,” “refocusing resources,” or “sunsetting non-core initiatives.”

Private companies reveal failures through funding announcements, layoffs, or restructuring news.

Interview Customers Who Evaluated Failed Features

Talk to prospects or customers who looked at competitor initiatives that later failed. They can tell you why they didn’t adopt, what problems they encountered, or why they chose alternatives.

Why Companies Don’t Study Competitor Failures

Most companies avoid analysing competitor failures for bad reasons:

“We’ll execute better than they did.” Maybe. But first, understand if execution was the problem.

“Our customers are different.” Probably not as different as you think.

“Market conditions have changed.” Possibly. But what specifically changed that makes this viable now?

“We don’t want to be influenced by their failures.” But ignoring these lessons means losing out on valuable intelligence.

The companies that succeed aren’t the ones that avoid studying failures. They’re the ones who learn from every failure—their own and their competitors’.

What to Do This Month

List the 5-10 biggest competitive initiatives you’ve seen fail in your market in the past 2-3 years.

For each one, document:

• What did they try?

• How much did they invest?

• Why did it fail?

• What lesson does this teach?

Then think about whether you are planning anything similar? Would we make the same mistakes?

If yes, either change your approach or have a clear explanation for why you’d succeed where they failed.

Learning from your own failures can be costly. Learning from competitor failures is free, as long as you pay attention.

We are Octopus. The Global Competitive Intelligence Consultancy.

Outsmart your competition. Make the unknown known. Octopus helps you gain clarity in complex markets. With clients and tentacles around the world, we deliver sharp, actionable competitive intelligence through a blend of deep primary (HUMINT) and secondary research. If you’re looking to make smarter decisions, beat the competition, and reduce uncertainty, we’re the partner you want on your side.

https://www.octopusintelligence.com/competitive-intelligence-to-study-competitor-failures/

“Basecamp won by refusing features everyone else added. Stripe won by making integration simple when competitors made it complex. Zoom won by serving end users when competitors sold to IT. The pattern: sustainable advantage comes from doing what competitors’ business models prevent them from doing”

The Feature Every Competitor Refused to Build

A CRM company approached us in 2023 with an interesting yet frustrating observation.

They’d interviewed 40 customers who’d evaluated competitors before choosing them. Different customers. Different industries. And different use cases.

But the same complaint about every competitor came up in 32 of those 40 interviews:

“Their mobile app is terrible. We have field teams who need CRM access on phones, and none of the options actually work well mobile-first.”

The VP of Product was confused.

“If customers want better mobile experiences and all our competitors have bad mobile apps, why aren’t competitors fixing this?”

We did competitive intelligence. Checked roadmaps, analysed product releases, and tracked engineering hiring patterns throughout all major CRM competitors.

Here’s what we found: Every competitor had mobile apps. None were investing in making them actually good.

Why? Because CRM companies were built by enterprise software veterans who believed “real work happens on desktops.”

Mobile was an afterthought. A checkbox feature. Something they shipped to say they had it, not something they designed their entire product around.

They all had the same blind spot. Same assumptions. Same organisational DNA that made certain product decisions unthinkable.

My client made a different choice. They rebuilt their entire CRM as mobile-first, with desktop as secondary. Designed for field sales teams, construction managers, healthcare workers—people who barely sit at desks.

Competitors called it a niche play. “Enterprise buyers want desktop power.”

Eighteen months later, our client had 40% of the mobile-heavy industries. Revenue grew 420%. Competitors finally started rebuilding for mobile, but they were 18 months behind and fighting their own product architecture decisions.

The competitive advantage wasn’t better mobile features. It involved being willing to do what established competitors’ organisations couldn’t do.

Why “What Wouldn’t Competitors Do?” Matters More Than “What Are Competitors Doing?”

Most competitive intelligence tracks what competitors are doing:

What features are they shipping? What markets are they entering? And what pricing are they testing? Who are they hiring?

This intelligence is, of course, very useful. It tells you where competitors are moving. Keep doing it.

But it misses something just as valuable: What are competitors incapable of doing?

Every company has constraints that make certain strategies unthinkable:

• Public companies can’t sacrifice quarterly revenue for long-term positioning. Their shareholders won’t tolerate it.

• VC-backed companies can’t pursue slow, profitable growth. Their investors demand scale.

• Enterprise-focused companies can’t ship scrappy, imperfect products. Their brand positioning prevents it.

• Legacy companies can’t cannibalise existing revenue streams. Their business model depends on them.

These constraints create gaps. Opportunities that exist in plain sight but remain unexploited because nobody is competing to pursue them.

The question “What wouldn’t our competitors do?” reveals strategic territory that’s undefended not because it’s unimportant, but because it’s unthinkable to the companies currently competing there.

The Constraints That Create Opportunities

At Octopus, we’re a UK and US-based competitive intelligence agency built by former British military intelligence analysts. We’ve spent twenty years serving very interesting companies. When we analyse competitors, we don’t just track what they’re doing. We map what they can’t do. The restrictions that limit their planned options.

Here are the constraints that create the biggest opportunities:

Financial Model

Public companies need predictable quarterly revenue. This makes them not good at:

• Long-term bets that sacrifice near-term revenue

• Experimental pricing models that create uncertainty

• Market entries that take 18+ months to show returns

VC-backed companies need exponential growth. This makes them not great at:

• Sustainable, profitable business models

• Serving small segments profitably

• Patient market development

Bootstrapped companies need profitability. This makes them poor at:

• Expensive market education

• Capital-intensive infrastructure

• Competing on features that require large teams

Each financial model creates strategic constraints. If you have a different financial model, you can pursue strategies competitors can’t.

Organisational DNA

Enterprise software companies are built to sell to IT departments and procurement teams. This makes them not great at:

• Product-led growth

• Self-serve onboarding

• Consumerized UX that “just works”

Developer tool companies are built by and for engineers. This makes them poor at:

• Serving non-technical users

• Business-user-friendly interfaces

• Abstracting away technical complexity

Sales-led companies are built around complex deal cycles. This makes them terrible at:

• Simple, open pricing

• Self-service purchasing

• Low-touch customer acquisition

Your competitors’ organisational DNA determines what they can build. If you have different DNA, you can build what they can’t.

Customer Base

Companies with large enterprise customers can’t:

• Radically simplify products (enterprises want complexity and customisation)

• Lower prices significantly (devalue existing contracts)

• Move fast and break things (stability requirements prevent it)

Companies serving the mid-market can’t:

• Build for enterprise compliance (too expensive relative to contract values)

• Offer white-glove service (margins don’t support it)

• Invest in highly specialised features (not enough customers per use case)

Your competitor’s existing customer base constrains what they can build next. If you’re serving different customers, you can build differently for each.

Brand Positioning

Premium brands can’t:

• Compete on price (destroys brand equity)

• Ship “good enough” products (conflicts with quality positioning)

• Serve budget-conscious customers (wrong brand association)

Simplicity-focused brands can’t:

• Add complex power features (conflicts with positioning)

• Serve technical users who want control (wrong user base)

• Build for edge cases (violates simplicity principle)

Whatever positioned your competitor successfully now constrains what they can do next. Different positioning creates different opportunities.

How to Identify What Competitors Won’t Do

Here’s the systematic process we use to map competitor constraints:

Step 1: Map Their Success Formula

What made each competitor successful? What customers do they serve? And what positioning did they claim? What business model did they build?

Their success formula becomes their constraint. The things that made them successful are now things they can’t change without risking what’s working.

Step 2: Identify Their Sacred Cows

What would each competitor never sacrifice? What principles or approaches are core to their identity?

• “We never ship features without extensive testing” is a sacred cow that prevents rapid iteration.

• “We only build for technical users” is a sacred cow that prevents serving business users.

• “Can we compete on having more features than anyone” is a sacred cow that prevents strategic simplification.

Sacred cows reveal what competitors won’t do even when the market insists they do.

Step 3: Track What They’ve Consistently Avoided

Look at market opportunities that have existed for years that competitors haven’t pursued.

If every competitor has ignored mobile for a decade, there’s probably a reason rooted in organisational constraints, not market feasibility.

If every competitor has avoided certain industries or customer segments, ask why. The answer reveals constraints.

Step 4: Analyse Their Organisational Structure

Competitors structured around sales teams can’t easily shift to a product-led growth model. Their comp plans, processes, and culture prevent it.

Competitors built around professional services can’t easily shift to self-serve SaaS. Their margins and employee expectations prevent it.

Competitors organised by product lines can’t easily build unified platforms. Internal politics and revenue attribution prevent it.

Organisational structure is destiny. It determines which companies can build and which can’t.

Examples What Competitors Won’t Do

Basecamp: What Project Management Companies Won’t Do

Every enterprise project management tool competes on features and complexity. More capabilities. More integrations and more customisation.

Basecamp said: “We’re not adding features. We’re removing complexity. We’re building for teams that want simple tools, not enterprise platforms.”

This was unthinkable for competitors. Their customers expected feature growth. Their sales teams sold based on feature checklists. And their revenue model depended on upselling improved capabilities.

Basecamp grew by doing what established competitors organisationally couldn’t: saying no to features.

Stripe: What Payment Processors Won’t Do

Traditional payment processors were built for enterprise sales cycles and multi-month integrations. That’s how they made money—big contracts, long implementations, lock-in.

Stripe said, “We’re going to make payments so easy that developers can integrate in an afternoon with seven lines of code.”

Traditional processors couldn’t compete. Their entire business model depended on complex integrations and lengthy sales cycles. Simple integration would cannibalise their revenue model.

Stripe captured developers and startups by doing what legacy competitors’ business models prevented: making payments actually simple.

Zoom: What Video Conferencing Companies Won’t Do

Enterprise video conferencing companies (Cisco, Polycom) competed on security, reliability, and IT integration. They sold to IT departments with six-month procurement cycles.

Zoom said: “We’re building for end users, not IT departments. No downloads. No complex setup. Just click and it works.”

This was strategically impossible for enterprise competitors. Their sales teams sold to IT. Their product was designed for centralised deployment. And their brand was enterprise infrastructure, not consumer simplicity.

Zoom won by serving end users in ways enterprise competitors couldn’t, without alienating its existing customer base or sales model.

The Strategic Question Nobody Asks

Most strategy meetings ask: “What should we build to compete?”

Better question: “What could we build that competitors organisationally can’t respond to?”

If you build a better version of what competitors already do, they can respond by improving their existing approach.

If you build something competitors are structurally prevented from doing, they can’t respond without rebuilding their business model, alienating their customer base, or contradicting their positioning.

That’s not a temporary advantage. That’s a structural moat.

How Competitive Intelligence Reveals These Gaps

When Octopus Intelligence analyses competitors, we’re looking for patterns:

We Track What They’ve Avoided

If all competitors in a market consistently avoid certain segments, pricing models, or product approaches, we investigate why. Sometimes the answer is “because it doesn’t work.” Sometimes it’s “because it conflicts with their business model.” The second answer creates opportunity.

We Analyse Organisational Hiring

Which companies hire reveals what they can build. If competitors aren’t hiring for certain capabilities, they probably can’t build products requiring those capabilities.

• If no competitor is hiring UX designers, they can’t build consumer-grade experiences.

• Your competitor is hiring developer advocates, they may not be able to build developer communities.

• If no competitor is hiring data scientists, they probably can’t build ML-powered features.

Hiring patterns uncover organisational capability gaps that create product opportunity gaps.

The Risks of Doing What Competitors Won’t

This strategy isn’t risk-free. Sometimes competitors don’t do things because those things don’t work.

Before pursuing “what competitors won’t do,” validate:

Is there actual customer demand?

Competitors might avoid a segment because customers there don’t value or can’t afford the solution. Don’t assume avoidance equals opportunity.

Can you actually execute it?

Just because competitors can’t do something doesn’t mean you can. Make sure you have the capabilities, resources, and organisational structure to succeed where they can’t.

Is the opportunity big enough?

Sometimes competitors avoid things because the market is too small to matter for their scale. Make sure the opportunity is substantial enough for your business.

Will you create new constraints by pursuing this?

If you succeed with an approach competitors can’t match, that approach becomes your identity. Make sure you’re willing to own it long-term.

What to Do This Quarter

Map your competitors’ constraints. For each major competitor, identify:

What made them successful? (Their success formula becomes their constraint)

What would they never sacrifice? (Sacred cows that limit strategy)

What have they consistently avoided? (Reveals organisational or business model constraints)

What have they tried and failed at? (Shows what conflicts with their DNA)

Then ask: What could we do that their constraints prevent them from doing?

Not “what are they bad at” but “what are they structurally incapable of doing without rebuilding their business?”

That’s where sustainable competitive advantage lives. Not in being slightly better at what everyone does, but in doing what others organizationally can’t.

At Octopus Intelligence, we help companies find these structural gaps. We map competitor constraints systematically. And we identify what they won’t do and why. We help you build strategies around gaps that competitors can’t close without fundamentally changing who they are.

Get in touch. Tell us who you’re competing against and what strategic options you’re considering.

The best competitive advantages aren’t built by doing what competitors do better.

They’re built by doing what competitors would never do, even if they could.

We are Octopus. The Global Competitive Intelligence Consultancy.

Outsmart your competition. Make the unknown known. Octopus helps you gain clarity in complex markets. With clients and tentacles around the world, we deliver sharp, actionable competitive intelligence through a blend of deep primary (HUMINT) and secondary research. If you’re looking to make smarter decisions, beat the competition, and reduce uncertainty, we’re the partner you want on your side.

https://www.octopusintelligence.com/what-wouldnt-your-competitors-do-even-if-they-could/

Your Pricing Strategy is Guessing Dressed Up as Analysis: Compete

Most pricing approaches are educated guesses backed up with spreadsheets that assume rational customer behaviour, predictable competitor responses, and market conditions that never materialise. Then, possibly use ChatGPT and the like. Then, companies call it “strategic pricing analysis”.

The Spreadsheet That Lies

You built a pricing model. It has tabs for competitor pricing, customer willingness to pay, cost structures, and margin targets. It looks professional. It’s still just guessing.

The competitor pricing came from their website, which bears zero resemblance to what they actually quote in negotiations. The willingness to pay came from those “expert” surveys where prospects lied because they had no skin in the game. The market analysis assumes that customers evaluate options rationally rather than making emotional decisions that are later justified with logic.

Your pricing approach is a well-formatted guess that executives approved because it had numbers and charts.

What Actually Happens

You price based on competitors, but you don’t know what they’re really charging. Published pricing is marketing. Actual pricing includes discounts, payment terms, bundling, and concessions that never appear in your analysis.

You price based on value, but customers don’t perceive value the way your model assumes. Your ROI calculator says the product pays for itself in six months. Customers will see the risk, the implementation effort needed, and all those change management headaches that spreadsheets don’t capture.

Your price is based on costs plus margin, which guarantees you leave money on the table when customers would be willing to pay more and lose deals when competitors undercut you despite your higher costs.

Then we get a call from product managers telling us they are losing market share, dont know how to differentiate, and we dont know our competitors’ real pricing or their Go-to-Market strategy. And yes, we can help.

The Real Problem

Pricing isn’t an analysis problem. It’s a confidence problem. You don’t know what customers will actually pay, so you make a conservative guess. You don’t see how competitors will respond, so you play it safe. You don’t trust your value proposition, so you discount.

The analysis provides cover for uncertainty. It lets you tell executives “we’ve done the research” when you’re really just hoping you guessed right.

Pricing strategy isn’t about better analysis. It’s about testing, iterating, and accepting that you’ll guess wrong sometimes. The analysis just makes you feel better about guessing.

We are Octopus. The Global Competitive Intelligence Consultancy.

Outsmart your competition. Make the unknown known. Octopus helps you gain clarity in complex markets. With clients and tentacles around the world, we deliver sharp, actionable competitive intelligence through a blend of deep primary (HUMINT) and secondary research. If you’re looking to make smarter decisions, beat the competition, and reduce uncertainty, we’re the partner you want on your side.

https://www.octopusintelligence.com/your-pricing-strategy-is-guessing-dressed-up-as-analysis-2/

Many lose by chasing phantom threats. Leaders often think competitors have advantages that aren’t real. They then overlook the real challenges right in front of them. Here’s how to end speculation and focus on what drives results.

The Panic That Wastes Millions

A fintech startup was convinced its main competitor had secret AI technology that was winning deals. “They must have something we can’t see,” he said. “Their demos look the same as ours, but they’re closing enterprise deals twice as fast.” This is a common concern for high-growth SaaS platforms. Often, the threat isn’t as great as competitors’ marketing claims suggest.

The “secret advantage” turns out to be their sales team’s 15-minute response time to inbound leads. Or something they call AI that is no better than what you are doing. That’s it. No AI magic. No hidden technology. Just basic sales operations executed well.

Why Fear of the Unknown Kills Strategy

“We’re worried competitors are ahead in ways we can’t see.”

This sentence is one of the most expensive anxiety statements in business.

Here’s what happens: You see a competitor winning. You don’t understand why. Your brain fills the gap with worst-case scenarios.

They must have better technology. Or good old insider relationships, undiscovered features, or unlimited VC funding for pricing.

This anxiety spirals into analysis paralysis or panic spending. You either freeze, afraid to make moves without more information. Or throw money at building defences against threats that don’t exist.

Both responses kill companies.

The Real Advantages You’re Missing

We’ve conducted competitive intelligence for over 40 companies in SaaS, fintech, e-commerce, and professional services in the past three to four years. The “hidden advantages” competitors have almost never turns out to be what companies fear.

Most competitive advantages are boring and visible:

• They respond to leads faster.

• They have better customer onboarding.

• They’ve optimised their pricing page.

• They actually follow up after demos.

• Their support team answers questions in minutes instead of hours.

A marketing automator spent 2022 believing its competitor had better email deliverability technology. They were losing deals and assumed technical superiority was the reason.

The real advantage isn’t invisible; they just didn’t ask the right questions.

How to See What Competitors Have

Stop imagining and start looking. Here’s a process to decode what competitors are actually doing:

Step 1: Test Their Product Like a Real Customer

Don’t just sign up and click around for 20 minutes. Go through their entire customer journey.

Fill out their contact form. See how long it takes them to respond. Book a demo. Experience their sales process. Sign up for a trial. Complete their onboarding. Try to accomplish real tasks.

You can’t see execution advantages on their marketing site. You have to experience the actual product journey. And you can only identify execution advantages by experiencing their product journey.

Step 2: Interview Customers Who Chose Them

This is the step everyone skips. Talk to people who evaluated both products and chose your competitor. Not to argue with them or convince them they were wrong. To understand what they saw that you’re missing.

Interview five prospects who chose that competitor. Do you get the same answer from all of them: “They showed us exactly how to migrate our existing projects. Your team just sent documentation links.” You’ll see that the advantage isn’t product features. It was migration support. Something the competitor emphasised in every demo. Something this company never mentioned because they assumed customers would figure it out on their own. One process change. Win rate improves 31% in two months.

Step 3: Track What They’re Building

Product roadmaps aren’t secret. You can see what competitors are building by watching what they’re doing publicly.

Check their job postings. If they’re hiring three mobile engineers, they’re building mobile apps. If they’re hiring a VP of Enterprise Sales, they’re moving upmarket. Or if they’re hiring product marketing for vertical industries, they’re specialising. Monitor their changelog and release notes. Most SaaS companies publish every feature update. You can track exactly what they’re prioritising. Follow their executives on LinkedIn. They announce products, share hints about the roadmap, and telegraph strategic shifts months before they launch.

Step 4: Analyse Their Customer Base

Look at who’s actually buying from them. Not who they claim to target, but who shows up in their case studies, testimonials, and customer logos.

This tells you what they’re good at selling to, which is often different from their positioning. Insight from this work can change your entire competitive strategy. Instead of trying to compete on enterprise features, you double down on the mid-market segment where we were both competing.

The Advantages That Are Hard to See

Some competitive advantages are hidden. Here’s what matters and how to spot it:

Network Effects

If a competitor’s product gets more valuable when more users join, that’s a real moat. Slack had this. The more teams used it, the more valuable it became for collaboration. Look at their pricing model and product architecture. Do they charge per user or per account? Do they have features that only work when multiple users are active? And do customers mention “everyone we work with uses this” in reviews?

Proprietary Data

If a competitor has unique data that improves their product and you can’t replicate, that’s a real advantage. Zillow has home value data. Glassdoor has salary data. This data creates accuracy advantages. Analyse where their data comes from. Is it user-generated? Scraped? Licensed? Publicly available? If it’s user-generated and they have scale, you might not be able to replicate it easily.

Strategic Partnerships

If a competitor has exclusive partnerships with platforms or distribution channels, that’s a real advantage. Being the default integration in Salesforce or Shopify creates distribution moats. Check their integrations page. Look for “official partner” or “preferred partner” badges. Monitor their press releases. Partnership announcements usually get publicised.

Capital Advantage

If a competitor raised $50M and is subsidising pricing or outspending you 10:1 on customer acquisition, that’s a real advantage. Not permanent, but real.

Crunchbase and Rogo show funding amounts. SEMrush or Ahrefs shows their paid advertising spend. If they’re burning cash faster than revenue could sustain, they’re using capital as a competitive weapon.

What to Do When the Gap Is Real

Competitive intelligence can show that your competitor is ahead where it counts.

They have better technology. They have more resources. And they have structural advantages you can’t easily replicate.

This is where most companies panic. Don’t.

Having advantages doesn’t mean they’re using them effectively. And it definitely doesn’t mean you can’t win.

We worked with a startup competing against a competitor with 10 times more funding and 50 times more customers. The competitor had every advantage on paper.

We did deep competitive intelligence. Found something critical: the competitor’s product was built for enterprise and was too complex for SMB customers. Their sales process required three demos and a two-week security review.

Their product worked immediately for SMB customers. No demos. No security reviews. Self-serve signup to value in under an hour.

So they didn’t try to compete in enterprise. They owned SMB. Grew to $3M ARR, serving customers the competitor couldn’t efficiently acquire.

The gap was real. The opportunity was also real. We just had to see it clearly.

The Framework for Competitive Clarity

Stop obsessing over invisible advantages. Map competitor actions for clarity.

Every Monday, spend 30 minutes on this exercise:

Question 1: What deals did we lose this week, and why?

Not the reason your sales team thinks. The actual reason customers gave. Call them if you have to.

Question 2: What did competitors announce or ship this week?

Check their changelog, blog, LinkedIn, and Twitter. Most announcements are public.

Question 3: What are customers saying about competitors in reviews?

Read G2, Capterra, and Reddit discussions. Real customer voices reveal real advantages and real weaknesses.

These 30 minutes give you clearer insights than any quarterly strategy off-site.

The Competitor That Wasn’t a Threat

A SaaS company came to us in 2023, terrified about a competitor that had just raised a $30M Series B.

“They’re going to crush us,” the CMO said. “They have unlimited resources. They’re hiring aggressively. We can’t compete.”

We found that the competitor had raised money but was burning through it fast. Their customer acquisition cost was $40K per customer. Their average contract value was $15K annually. The maths didn’t work. We checked their Glassdoor reviews. Internal chaos. Three VPs had left in six months. The engineering team rebuilt the product from scratch. The first architecture couldn’t scale.

They had capital. They lacked execution. Execution always wins.

Six months later, that competitor announced layoffs and a tactical change. A year later, it got worse for them.

The threat everyone feared never materialised because the fundamentals were broken. But you couldn’t see that from their funding announcement. You had to actually look.

What Fear Costs You

Anxiety about competitors being ahead in ways that aren’t visible costs more than money.

It costs focus. You’re examining the horizon for threats instead of building for customers.

It costs confidence. Your team senses the fear and starts doubting whether you can win.

It costs speed. You’re hesitating on decisions because you’re worried about information you don’t have.

Most competitive advantages aren’t invisible. They’re just unexamined.

The competitor winning more deals isn’t hiding secret technology. They’re probably just doing basic things really well. Faster responses. Better onboarding. Clearer pricing. Simpler product experience.

Those advantages are all visible if you actually look. And they’re all copyable if you actually commit to fixing them.

What Octopus Intelligence Does Differently

At Octopus Intelligence, we are a competitive intelligence agency based in the UK and the US. Our team is made up of former British military intelligence analysts. We’ve spent 20 years helping companies like Mercedes, Samsung, and other product firms, as well as fast-growing SaaS platforms.

We don’t tell you what you want to hear. We tell you what’s actually happening.

When clients worry about hidden advantages of competitors, we conduct thorough investigations:

We mystery-shop competitor products throughout their entire customer journey.

We interview customers who chose competitors to understand real decision drivers.

And we analyse competitor hiring, funding, partnerships, and public signals to decode strategic direction.

We separate fear from fact. Assumptions from evidence. What competitors claim from what they deliver.

Most importantly, we tell you when the threat is real and when you’re fighting ghosts.

Sometimes the answer is: “Your competitor is ahead. Here’s where, here’s why, and here’s what you can do about it.”

Sometimes the answer is: “The competitive advantage you’re worried about doesn’t exist. Here’s what’s happening and what you should focus on instead.”

Both answers are valuable. Both require systematic investigation, not speculation.

What to Do This Week

Pick the competitor you’re most worried about. The one keeping you up at night. The one you’re convinced has advantages you can’t see.

Spend four hours systematically investigating:

• Sign up for their product. Go through their entire customer journey. Take notes on everything that feels better than your experience.

• Find three customers who chose them over you. Call them. Ask what they saw that you missed.

• Check their job postings, changelog, and social media. See what they’re actually building and where they’re investing.

• Read 20 customer reviews. Note what people praise and what they complain about.

• Write down what you learned. Not what you assumed. What you discovered.

• I guarantee the reality is different from your fears. Sometimes better. Sometimes worse. But always different.

• You can’t fight ghosts. You can only fight what you can see clearly.

Stop worrying. Start looking.

If you need help seeing clearly, that’s what we do. Get in touch with Octopus Intelligence. Tell us which competitor keeps you up at night. We’ll show you what they actually have versus what you worry they have.

Then you can make decisions based on reality instead of anxiety

.

https://www.octopusintelligence.com/worried-competitors-are-ahead-in-ways-we-cant-see/

Many think competitor analysis starts with certainty.

It doesn’t.

Competitor evaluation starts with action. The act of choosing the first questions to interrogate.

The market answers you after you start prodding it.

Many have learned this the hard way. Teams that make progress are not the ones who try to map every possible competitor. They were the ones who were willing to say:

“We don’t know enough yet. But we know the next step.”

That mindset uncovers more truth than any lovely-looking slide deck ever does.

Stop Waiting for the “Complete Picture”

A founder once told me they couldn’t move ahead with international expansion because they wanted a “full analysis of all competitors in the region.”

The phrase full analysis is a trap.

Competitor landscapes shift every quarter. New entrants, changing burn rates, shifting customer behaviour, pricing experiments, quiet changes in direction. If you wait for a complete view, you’ll be sitting in the middle of a stale map while faster operators rewrite your boundaries.

A better question is:

“What do we need to learn in the next seven days to reduce uncertainty by 10%?”

Seven days force clarity.

Ten per cent forces humility.

Once you get comfortable with those two constraints, competitor analysis becomes a rolling investigation rather than a mythical final document.

Markets Reward Curiosity, Not Certainty

Here is an example. Let’s call them VoltEdge, a five-year-old US-based energy storage company. They were obsessed with identifying their “direct competitors.”

The problem:

The market didn’t agree with their categories.

VoltEdge saw itself in “home battery storage.”

Customers saw them as “a portable alternative to diesel generators.”

Installers saw them as “a faster install option than fixed storage solutions.”

Three different groups. Three different definitions of competition.

VoltEdge discovered this only after they started interviewing distributors, monitoring pricing experiments from companies like EcoFlow and Bluetti, and shadow-following chatter inside niche Facebook groups.

They didn’t wait to be certain.

They built certainty through action.

That shift rerouted their go-to-market plan and formed their product roadmap more than any internal whiteboard session ever could.

The First Step in Competitor Analysis Is Always: Pick a Question

Not a spreadsheet.

Not a framework.

And no, not a data set.

Not a matrix filled with green and red dots.

A question.

Here are three starting questions that consistently expose real competitive threats:

1. “Who else is trying to win the same budget line we are?”

Competitors are anyone who forces the buyer to say, “I can only pick one.”

If you sell workflow software, your competitor might not be other workflow tools.

It might be a team lead who insists Excel “works fine.”

2. “Who scares our potential investors?”

VCs and angel investors have their own private threat lists. Studying these lists surfaces competitors you haven’t even seen yet.

3. “What would a newcomer build if our assumptions didn’t weigh them down?”

This question saved a fintech startup I advised last year.

They realised their biggest threat wasn’t an established bank. It was a six-person startup in Lisbon building fee-free treasury tools with no legacy features to support.

These questions open doors.

None requires perfect information.

Confidence Comes From Fast Cycles of Imperfect Information

We’ve seen global SaaS companies that refresh competitor analysis every two weeks.

Not because the market changes that fast — though sometimes it does — but because rhythm builds understanding.

Here’s the three-step cycle they use:

1. Form a hypothesis

Example:

“Competitor X is discounting because they’re losing mid-market deals.”

2. Collect the signals

• Win/loss notes

• Scraped pricing pages

• Customer conversation snippets

• Recruiter job posts

• Sales rep LinkedIn comments

3. Publish a one-page update

Not a fancy document.

Just a clear summary: What changed? What stayed the same? What requires checking again?

Truth compounds.

Confidence compounds.

Speed compounds.

Perfection does not.

The Market Won’t Reveal Everything. But Just Enough to Make the Next Move

Ben Gilad likes to say the biggest enemy in intelligence isn’t deception; it’s assumption.

And of course, he is right.

Assumptions rot your market view.

Action disinfects it.

Every step you take forces the market to show its hand:

Send a pricing test to discover who drops their price within 48 hours.

Launch a new feature. See who shifts messaging.

Target a new segment. Learn which competitors are lurking unnoticed.

Progress isn’t about holding all the answers.

It’s about building a habit of extracting answers from the market in small, deliberate slices.

Courage Beats Certainty — Every Time

People romanticise strategy.

They imagine long meetings, perfect clarity, brilliant insight.

Real strategy, especially in competitive intelligence, feels more like walking through fog with a cheap torch.

You see only a few metres ahead.

But that’s enough to keep moving. Courage keeps you in motion. Motion uncovers information and information sharpens your decisions.

Start before you feel ready.

Start with imperfect questions.

And start with scrappy notes, not a polished report.

Every useful competitor analysis I’ve ever seen was built after someone decided to take a step without knowing exactly where it would lead.

The market reveals itself one inch at a time — but only to the people willing to walk forward.

We are Octopus. The Global Competitive Intelligence Consultancy.

Outsmart your competition. Make the unknown known. Octopus helps you gain clarity in complex markets. With clients and tentacles around the world, we deliver sharp, actionable competitive intelligence through a blend of deep primary (HUMINT) and secondary research. If you’re looking to make smarter decisions, beat the competition, and reduce uncertainty, we’re the partner you want on your side.

https://www.octopusintelligence.com/how-real-competitor-analysis-emerges-start-before-youre-ready/

Competitive intelligence provides the missing market perspective product teams need to make investment decisions confidently. Product planning meetings often stall when debating which features to prioritise, like advanced reporting or mobile apps. Decisions are often based on stories from customers, sales, or competitors.

The CPO remarked, “We’re spending $2M on engineering next year, but our decisions rely on whoever argues best. Does anyone know what really wins deals now?”

Silence.

They collected customer feedback and tracked competitors, but lacked systematic insight into buying drivers, competitor strengths, and real market gaps.

Many SaaS companies make costly product choices based on opinions and isolated requests. Competitive intelligence provides a holistic market view, enabling data-driven decision-making and increasing the odds that new investments drive revenue.

“We Don’t Know What the Market Wants; Product Decisions Feel Like Guesses”

Why Product Decisions Feel Like Guesswork

SaaS product teams have access to more information than ever, including customer feedback tools, usage analytics, competitor monitoring, and sales insights. Yet, product decisions frequently remain uncertain.

The Loudest Voices Don’t Represent the Market

Large customers request features customised to their needs. Sales teams advocate for capabilities that might have prevented lost deals. Executives often push for popular solutions such as AI or mobile-first design.

None of these voices necessarily represent what the wider market values or what wins competitive deals.

We worked with a SaaS client whose roadmap was heavily influenced by requests from their three largest enterprise customers, who accounted for 40% of revenue. As a result, the product team focused on increasingly specialised enterprise features.

Competitive intelligence showed they were losing 70% of mid-market deals to competitors offering simpler, more intuitive products. The mid-market was five times larger than their enterprise segment, yet their product was optimised for a small group of vocal customers rather than the wider market. Took 18 months. They’d built two years of features the wider market didn’t care about because they confused “customer requests” with “market demand.”

Competitor Monitoring Doesn’t Reveal Strategy

Most SaaS companies track competitor releases, pricing, and partnerships. This reveals what competitors have done, but not why or how effective it was. Some rely only on competitive signals and intelligence tools, assuming that’s enough.

When a competitor launches an AI-powered offering, don’t just note the launch. Focus on why it was prioritised and whether it drives deals. They built AI to address customisation limits, but it was a workaround, not a core strength. Customer interviews showed prospects were underwhelmed by generic AI that didn’t save time. Instead of matching features, double down on your strengths and frame their AI as a workaround that misses the real issue.

Customer Feedback Is Biased and Incomplete

Customers say what they think they want, which often differs from what drives their purchases. For instance, they may request better reporting when the real issue is distrust in your data, or ask for API improvements when they actually want easier integrations.

Revenue operations teams see this often. Customers cite price as a driver of churn, but deeper interviews reveal that poor onboarding impedes the demonstration of ROI. Customers sometimes request attractive features that won’t improve satisfaction or growth.

Customer feedback suggests areas to explore, but only competitive intelligence cuts through the noise to find real market needs and buying factors. This is CI’s unique value: turning data into implementable market understanding.

Sales Feedback Is Filtered By Loss Aversion

Sales teams offer useful insights, but their feedback frequently stems from recent losses. For example, after losing several deals over ‘better integrations,’ integrations may top the priority list, even if the root cause was a lack of understanding of customer needs. Competitive intelligence realigns resources toward more effective efforts, such as deployment automation.

Understanding What Competitive Intelligence Actually Reveals

Systematic competitive intelligence replaces guesses with evidence about:

• What the market values,

• What competitors are winning on

• Where your product strengths and gaps create opportunities or risks.

Allow us to demonstrate how this works in practice. The following examples show this process in action.

Product intelligence goes beyond feature checklists to identify which capabilities drive buying decisions and the reasons behind them.

What competitors actually deliver versus what they claim

Competitors’ marketing materials promise features they may not deliver. For example, one vendor claimed ‘enterprise-grade scalability,’ but mystery shopping found their product slowed to a crawl beyond 500,000 records—the level many prospects need.

The company built messaging around ‘proven performance at scale,’ supported by real deployment data. Sales materials asked, “Have you checked their platform’s performance above 500,000 records?” This lets them confidently offer relevant proof to prospects.

This intelligence highlighted a perceived weakness in competitor solutions, allowing the company to turn it into a strong advantage in enterprise deals. Features are table stakes versus differentiators.

Not all features are equally important. Some are must-haves, others win deals. Product teams often waste resources on ‘nice to haves’ instead of real differentiators, usually asking competitive intelligence about the former, not the latter.

Win/loss interviews identify which features are mentioned in successful versus lost deals, which capabilities your customers value most, and which gaps are consistently cited by prospects who choose competitors. This analysis shows feature priorities based on actual buying behaviour rather than guesses.

Product positioning gaps in the market

Sometimes the big opportunity isn’t copying competitors’ features, but targeting a market segment they ignore. Competitors offered ‘enterprise platforms’ or ‘self-service tools,’ but nobody owned the middle: analyst-friendly tools needing no IT support.

Customer interviews confirmed high demand in this neglected segment. Analysts wanted advanced tools without the complexity of enterprise products or the limitations of self-serve options. The client repositioned around ‘power without complexity’ and shifted their roadmap to address this need. What to Build Next and Why

Roadmap intelligence enables product teams to focus on investments by considering market forces, competitive gaps, and opportunities for strategic differentiation.

Competitors’ hiring, partnerships, exec statements, and tech investment hint at their next moves. Reading these signals lets you anticipate competitor moves and adjust your position to take advantage of gaps.

Some competitor weaknesses are quickly fixed; others demand big changes. Knowing the difference helps you gauge how long your differentiation will last.

Intelligence enables investment in real-time capabilities with the confidence that differentiation will be sustainable over several years.

Competitive intelligence also supports build-versus-partner-versus-acquire decisions.

• Should you build a capability in-house?

• Partner with someone who has it?

• Or acquire a company?

Competitive intelligence reveals which approach works in your market.

Innovation areas where competitors are absent

In some cases, the best roadmap decisions involve developing capabilities that no competitor currently offers. Early-mover advantage in valuable features can greatly alter competitive dynamics.

However, this is effective only if customers value these features. Many “innovative” capabilities address issues that buyers do not focus on.

Customer interviews identified a consistent pain point: difficulty onboarding new team members. Since no competitor optimised for rapid onboarding, we addressed this gap.

Pricing Intelligence: What the Market Will Actually Pay

Pricing intelligence uncovers what competitors actually charge in real transactions, how they structure offers, existing discount patterns, and areas of pricing flexibility.

Published pricing rarely reflects reality in B2B SaaS. List prices, “starting at” figures, and published pricing rarely reflect actual B2B SaaS transaction values. List prices, “starting at” figures, and online calculators do not reveal what competitors charge during negotiations. Inside mystery shopping, as:

(1) a startup with 10 users, (

2) a mid-market company with 100 users,

(3) an enterprise with 1,000 users.

Same competitor quoted $29/user/month for the startup, $19/user/month for mid-market, and $12/user/month for enterprise.

The pricing flexibility was 2.4 times between the highest and lowest quotes. The client had used the competitor’s published $29 pricing as a benchmark and believed aggressive discounting was necessary. In reality, the competitor was discounting by 60% for enterprise customers. This insight enabled the client to modify their pricing strategy: maintain pricing for small customers, offer progressive discounts for larger accounts, and remain confident that their enterprise pricing was competitive without matching published rates. ished rates.

Pricing model trends and effectiveness

Are competitors moving from per-user to usage-based pricing? From monthly to annual contracts? From flat-rate to tiered pricing? Which models are winning deals and which are creating friction?

A client considered switching from per-user to usage-based pricing in response to competitor announcements. However, win/loss interviews revealed that customers were frustrated by the instability of usage-based pricing.

Customers stated that usage-based pricing “made sense theoretically,” but it introduced budget uncertainty, required CFO approval, and slowed deal cycles. Per-user pricing was easier to forecast and could be approved at the department level without executive involvement.

The client retained per-user pricing and described it as “predictable costs you can budget confidently.” They won deals against usage-based competitors because finance teams preferred predictability. The “innovative” pricing model adopted by competitors was actually creating sales friction.

Discount patterns and negotiation leverage

How much do competitors discount in different situations? What triggers larger discounts? What terms do they offer to close deals?

Understanding discount patterns helps avoid both under-discounting, which can result in lost deals, and over-discounting, which erodes margins on deals that would have closed regardless.

Mystery shopping revealed a competitor would discount 20% for annual prepayment versus monthly billing, an additional 10% for multi-year contracts, and another 15% for deals closing before quarter-end.

The competitor’s maximum discount was 40% for a three-year annual prepaid plan signed before quarter-end. This insight clarified where pricing flexibility existed and where matching competitor discounts was unnecessary to remain competitive.

Value metric optimisation

It is important to ensure that pricing corresponds with how customers perceive value. Misaligned value metrics can create pricing resistance, even if the total price is reasonable.

A marketing automation platform charges per “contacts in database.” Customer interviews revealed annoyance among those with large databases but low email volume, who felt overcharged, while customers with small databases and high engagement considered the pricing fair.

The competitor’s value metric (per email sent) aligned better with perceived value—customers paid for what they used, not what they stored.

The client restructured pricing from “per contact” to “per active contact” (contacted in the last 90 days). This change aligned pricing with customer value perception, reduced deal friction, and allowed for larger customer database limits as a competitive advantage. The key insight was not about price levels, but regarding aligning the pricing structure with customer value perception.tion.

Packaging and bundling strategies

It is important to understand how competitors package features into tiers, what is included in base plans versus add-ons, and whether they bundle or unbundle offerings.

A client initially offered three standard tiers. Competitor analysis showed that competitors were succeeding by delivering customizable packages that let customers select only the features they needed, without paying for unused capabilities.

Customer interviews confirmed the importance of this approach: buyers resented paying for “Professional tier” features they did not use simply to access a single “Enterprise tier” capability.

The client adopted modular pricing, allowing customers to build custom packages. Win rates improved as buyers felt they were paying for value they would use, rather than subsidising features for other customer segments.

How We Help SaaS Product Teams Make Evidence-Based Decisions

Most SaaS companies lack the methodical processes, specialised skills, and dedicated resources required to gather product-focused competitive intelligence that informs roadmap decisions. Most importantly, they do not have the time. Octopus was built specifically to address this need.

Win/Loss Analysis That Reveals Product Truth

We conduct structured win/loss interviews using sophisticated methods such as Five Whys and Laddering to uncover why customers really chose you or chose competitors—not the tactful explanations they give, but the actual decision drivers.

We interview customers across your wins, losses, and in-process evaluations.

• We ask about features, but we dig deeper:

• What business problem were they solving?

• What capabilities mattered most?

• How did they evaluate trade-offs?

• What made them confident or nervous about each option?

This usually reveals which product capabilities drive revenue, versus which customers request but don’t actually value in their buying decisions. You stop building what sounds important and start building what wins deals.

Mystery Shopping Competitor Products and Sales Experiences

We don’t just read competitor marketing materials. We become their prospects. And we approach competitors with realistic buyer scenarios and experience their products, sales process, and positioning firsthand.

For SaaS specifically, we:

• Request demos and thoroughly evaluate competitor products with your target use cases.

• Get actual pricing quotes among different buyer personas and deal sizes.

• Document what features they emphasise versus downplay

• Identify gaps between marketing claims and product reality.

• Experience their onboarding, implementation promises, and support interactions.

• Note specific positioning statements they use about your company.

You learn what competitors actually deliver, not what they claim. You discover where they’re legitimately strong versus where they’re covering weaknesses with marketing. And exactly how they position against you.

Deep Customer Interviews About Product Priorities

We interview your customers, your competitors’ customers, and prospects who are actively evaluating options. People tell us things they won’t tell vendors directly.

We use Laddering techniques to move from feature-level feedback (“we need better reporting”) to benefit-level understanding (“what would better reporting let you do?”) to emotional drivers (“how would that change how you feel about this investment?”).

This reveals the real product gaps, the features that seem important but don’t drive decisions, and the capabilities customers can’t articulate but desperately need.

A client’s buyers consistently requested “API enhancements.” Laddering revealed they didn’t actually need better APIs—they needed simpler out-of-the-box integrations so they wouldn’t have to use APIs at all. The stated request was the opposite of the actual need.

Systematic Feature Impact Analysis

We analyse which features are mentioned more often in wins than in losses, which capabilities customers who expanded with you valued most, and which gaps customers who churned or chose competitors cited most frequently.

This shows you:

• Table-stakes features every competitor must have

• Differentiating features that actually win deals

• Requested features that don’t impact buying decisions

• Hidden requirements customers don’t explicitly request but silently evaluate

You get data-driven feature prioritisation instead of opinion-based roadmap debates.

Competitor Roadmap Intelligence and Early Warning

We track competitor hiring patterns, partnership announcements, technology investments, and executive statements to predict their roadmap direction 6-12 months before they launch.

We monitor:

• LinkedIn hiring by role (ML engineers, mobile developers, specific technology skills)

• Technology partnerships and integration announcements

• Acquisition targets and strategic ventures

• Patent filings and technical publications

• Conference presentations and thought leadership themes

You get advance warning of competitor moves so you can prepare positioning, build differentiating responses, or avoid chasing features that won’t matter.

Pricing Intelligence Across Real Scenarios

We conduct mystery shopping specifically focused on pricing. approaching competitors with different buyer personas, company sizes, and use cases to get actual quotes.

We document:

• Real pricing among different customer profiles

• Discount patterns and negotiation dynamics

• Payment terms, contract structures, and flexibility

• Bundling and packaging approaches

• Hidden costs (implementation, training, support upgrades)

You understand true competitive pricing patterns instead of guessing based on published rates that don’t reflect reality.

Brand Positioning Gap Analysis

Sometimes the best product strategy isn’t matching competitors. It’s the owning positioning they ignore. We analyse the entire competitive landscape to identify gaps where customer demand exists, but no competitor dominates.

We map:

• How each competitor positions (enterprise vs SMB, simple vs powerful, industry-specific vs horizontal)

• Which customer segments feel underserved

• What territories remain unclaimed

• Where your product strengths correspond to market gaps

You find white space opportunities where you can win without fighting established competitors head-on.

Our Track Record with SaaS Product Teams

We’ve helped SaaS companies:

Reprioritise roadmaps based on actual buying patterns.

A client redirected $3M in engineering resources from requested features to capabilities that actually won deals. Win rates improved 24% in two quarters.

Identify positioning gaps worth owning.

A client found an unclaimed positioning between enterprise complexity and SMB limitations and captured 18% market share in 18 months.

Optimise pricing models for revenue.

A client restructured value metrics based on customer perception, reduced deal friction, and expanded average contract values 31%.

Avoid expensive feature mistakes.

A client discovered that a planned $1.5M mobile investment wouldn’t improve win rates and redirected resources to implementation automation, which became their key differentiator.

Predict competitor moves early.

A client received a 6-month advance warning of a competitor’s AI feature launch, prepared counter-positioning, and neutralised the risk before it materialised.

We are Octopus. The Global Competitive Intelligence Consultancy.

Outsmart your competition. Make the unknown known. Octopus helps you gain clarity in complex markets. With clients and tentacles around the world, we deliver sharp, actionable competitive intelligence through a blend of deep primary (HUMINT) and secondary research. If you’re looking to make smarter decisions, beat the competition, and reduce uncertainty, we’re the partner you want on your side.

https://www.octopusintelligence.com/how-competitive-intelligence-transforms-saas-product-strategy/

Many companies lose because they fight ghosts. Imagining competitor advantage that doesn’t exist. Missing the real threats right in front of them. Stop worrying about invisible competitors and start seeing what matters.

The Panic That Wastes Millions

A fintech startup approached us in 2025 with $800K in their bank account and 6 months of runway. The CEO was convinced their main competitor had secret AI technology that was winning deals. “They must have something we can’t see,” he said. “Their demos look the same as ours, but they’re closing enterprise deals twice as fast.”

We spent five weeks on deep competitive intelligence. We gathered everything we could find, tested their product, interviewed customers who evaluated both companies, and spoke with former employees through our network.

The “secret advantage” turned out to be a sales team that responded to inbound leads within 15 minutes. That’s it. No AI magic. No hidden technology. Just basic sales operations executed well.

Meanwhile, fintech companies burn through their cash by building machine learning features nobody asked for, assuming that’s what competitors had.

These companies don’t make it. They run out of money following shadows while ignoring basic execution problems. Those that kill their conversion rates.

Why Fear of the Unknown Kills Strategy

“We’re worried competitors are ahead in ways we can’t see.”

It’s the most expensive anxiety in business.

Here’s what happens: You see a competitor winning. You don’t understand why. Your brain fills the gap with worst-case scenarios.

They must have better technology, insider relationships, undiscovered features, or be subsidising pricing with VC funding.

This anxiety spirals into analysis paralysis or panic spending. You freeze, afraid to make moves, lacking more information, or throw money at building defences against threats that don’t exist.

Both responses kill companies.

The Real Advantages You’re Missing

We’ve done competitive intelligence for many years with companies across SaaS, fintech, e-commerce, and professional services. The “hidden advantages” competitors have almost never turned out to be what companies fear.

Most competitive advantages are boring and visible:

They respond to leads faster. They have better customer onboarding. They’ve optimised their pricing page. They actually follow up after demos. Their support team answers questions within minutes rather than hours.

A marketing automation company spent 2022 convinced that its competitor had superior email deliverability technology. They were losing deals and assumed technical superiority was the reason.

We do customer interviews with people who’d chosen the competitor. The actual reason? The competitor’s templates looked better out of the box. That’s it. Better default templates that made emails look professional without customisation.

The advantage was never invisible. They just didn’t ask the right questions to see it.

How to Actually See What Competitors Have

Stop imagining and start looking.

Here’s the systematic process I use to decode what competitors are actually doing:

Step 1: Test Their Product Like a Real Customer

Don’t just sign up and click around for 20 minutes. Go through their entire customer journey.

Fill out their contact form. See how long it takes them to respond. Book a demo. Experience their sales process. Sign up for a trial. Complete their onboarding. Try to accomplish real tasks.

You can’t see execution advantages from their marketing site. You have to experience the actual product journey.

Step 2: Interview Customers Who Chose Them

This is the step many skip. Talk to people who evaluated both products and chose your competitor, or convince them they were wrong. To understand what they saw that you’re missing.

We worked with a project management software company, losing deals to a competitor. The founder assumed the competitor had better features or lower pricing.

We interviewed a number of prospects who’d chosen the competitor. Same answer from all of them: “They showed us exactly how to migrate our existing projects. Your team just sent documentation links.”

The advantage wasn’t product features. It was migration support. Something the competitor emphasised in every demo. Something this company never mentioned because they assumed customers would figure it out on their own.

One process change. Win rate improved.

Step 3: Track What They’re Actually Building

Product roadmaps aren’t secret. You can see what competitors are building by watching their public actions.

Check their job postings. If they’re hiring three mobile engineers, they’re building mobile apps. And if they’re hiring a VP of Enterprise Sales, they’re moving upmarket. If they’re hiring product marketing for vertical industries, they’re specialising.

Monitor their changelog and release notes. Most SaaS companies publish every feature update. You can track exactly what they’re prioritising.

Follow their executives on LinkedIn. They announce products, share hints about the roadmap, and telegraph strategic alterations months before official launches.

Step 4: Analyse Their Actual Customer Base

Look at who’s actually buying from them. Not who they claim to target, but who shows up in their case studies, testimonials, and customer logos.

This shows who they’re actually good at selling to, which is often different from their positioning.

This insight changed the entire competitive strategy. Instead of competing on enterprise features, we doubled down on the mid-market segment where we were both competing.

The Advantages That Are Actually Hard to See

Some competitive advantages are legitimately hidden. Here’s what actually matters and how to spot it:

Network Effects

If a competitor’s product gets more valuable while more users join, that’s a real moat. Slack had this. The more teams used it, the more valuable it became for collaboration. Look at their pricing model and product architecture. Do they charge per user or per account? Do they have features that only work when multiple users are active? And do customers mention “everyone we work with uses this” in reviews?

Proprietary Data

If a competitor has unique data that improves their product and you can’t replicate, that’s a real advantage. Zillow has home value data. Glassdoor has salary data. This data creates accuracy advantages.

Analyse where their data comes from. Is it user-generated? Scraped? Licensed? Publicly available? If it’s user-generated and they have scale, you might not be able to replicate it easily.

Tactical Alliances

If a competitor has exclusive partnerships with platforms or distribution channels, that’s a real advantage. Being the default integration in Salesforce or Shopify creates distribution moats.

Check their integrations page. Look for “official partner” or “preferred partner” badges. Monitor their press releases. Partnership announcements usually get publicised.

Capital Advantage

If a competitor raised $50M and is subsidising pricing or outspending you 10:1 on customer acquisition, that’s a real advantage. Not permanent, but real.

Crunchbase shows funding amounts. SEMrush or Ahrefs shows their paid advertising spend. If they’re burning cash faster than revenue could sustain, they’re using capital as a competitive weapon.

What to Do When the Gap Is Real

Sometimes, competitive intelligence reveals that your competitor is actually ahead in ways that matter.

They have better technology. They have more resources. And they have structural advantages you can’t easily replicate.

This is where most companies panic. Don’t.

Having advantages doesn’t mean they’re using them effectively. It doesn’t mean you can’t win.

We worked with a startup competing against a competitor with 10x more funding and 50x more customers. The competitor had every advantage on paper.

We did deep competitive intelligence. Found something critical: the competitor’s product was built for enterprise and was too complex for SMB customers. Their sales process required three demos and a two-week security review.

The product worked for SMB customers immediately. No demos. No security reviews. Self-serve signup to value in under an hour.

They didn’t try to compete in the enterprise. We owned SMB. Grew to $3M ARR, serving customers that the competitor couldn’t efficiently acquire.

The gap was real. The opportunity was real. They just had to see it clearly.

The Framework for Competitive Clarity

Stop worrying about invisible advantages. Start systematically mapping what’s actually happening.

Every Monday, spend 30 minutes on this exercise:

Question 1: What deals did we lose this week, and why?

Not the reason your sales team thinks. The actual reason customers gave. Call them if you have to.

Question 2: What did competitors announce or ship this week?

Check their changelog, blog, LinkedIn, and Twitter. Most announcements are public.

Question 3: What are customers saying about competitors in reviews?

Read G2, Capterra, and Reddit discussions. Real customer voices reveal real advantages and real weaknesses.

This 30-minute routine gives you more competitive clarity than quarterly strategy off-sites ever will.

The Competitor That Wasn’t a Threat

A SaaS company came to me in 2023, terrified about a competitor that had just raised a $30M Series B.

“They’re going to crush us,” the CEO said. “They have unlimited resources. They’re hiring aggressively. We can’t compete.”

I pulled competitive intelligence. The competitor had raised money but was burning through it fast. Their customer acquisition cost was $40K per customer. Their average contract value was $15K annually. The math didn’t work.

I checked their Glassdoor reviews. Internal chaos. Three VPs had left in six months. The engineering team was rebuilding the product from scratch because the original architecture couldn’t scale.

They had money. They didn’t have execution.

Six months later, that competitor announced layoffs and a strategic change. A year later, they shut down.

The threat everyone feared never materialised because the fundamentals were broken. But you couldn’t see that from their funding announcement. You had to actually look.

What Fear Costs You

The anxiety about competitors being ahead in ways that aren’t visible costs more than money.

It costs focus. You’re surveying the horizon for threats instead of building for customers.

It costs confidence. Your team senses the fear and starts doubting whether you can win.

And it costs speed. You’re hesitating on decisions because you’re worried about information you don’t have.

Most competitive advantages aren’t invisible. They’re unexamined.

The competitor winning more deals isn’t hiding secret technology. They’re probably just doing basic things really well. Faster responses. Better onboarding. Clearer pricing. Simpler product experience.

Those advantages are all visible if you actually look. And they’re all copyable if you actually commit to fixing them.

What to Do This Week

Pick the competitor you’re most worried about. The one keeping you up at night. The one you’re convinced has advantages you can’t see.

Spend four hours systematically investigating:

• Sign up for their product. Go through their entire customer journey. Take notes on everything that feels better than your experience.

• Find three customers who chose them over you. Call them. Ask what they saw that you missed.

• Check their job postings, changelog, and social media. See what they’re actually building and where they’re investing.

• Read 20 customer reviews. Note what people praise and what they complain about.

• Write down what you learned. Not what you assumed. What you actually discovered.

The reality will be different from your fears. Sometimes better. Sometimes worse. But always different.

You can’t fight ghosts. You can only fight what you can see clearly.

Stop worrying. Start looking.

https://www.octopusintelligence.com/are-you-worried-that-competitors-are-ahead-in-ways-we-cant-see-how-to-stop-playing-blind-and-start-seeing-what-actually-matters/

Many think of themselves as “strategic”. But are making considered decisions, as if they’re blindfolded in a casino. Real strategy starts with one question nobody asks:

“What do we really know about the competition?”

Here’s why competitive intelligence is the only thing separating planned good moves from those expensive guesses.

The $4 Million Decision Made in Complete Darkness

A SaaS company burned through $4 million in 2022, building a feature that its competitor had already tried and abandoned.

They spent nine months in development. Hired a team of six engineers. Built custom infrastructure and launched with a full marketing push.

Three customers used it. None paid extra for it.

Here’s the part that should make their then-investors angry: Their competitor had detailed blog posts explaining why they killed the same feature eighteen months earlier. The data was public. The lessons were free.

Nobody looked.

The CEO said, “We thought we knew our market. Turns out we knew our product and nothing else.”

That’s the gap. That’s where companies die.

The Lie Everyone Believes

Walk into most strategy meetings, and you’ll hear the same confident statements:

“We know our competitors.”

“We’re better than them.”

“They just win on price.”

“We’re too small to need formal competitive intelligence.”

You may have heard versions of these yourself. They’re all wrong.

You don’t know your competitors. You know the version of them you saw six months ago when you last checked their website. And you may know the sales pitch their rep gave your customer. You know what your team thinks they do.

You don’t know what they’re building right now. And you don’t know where they’re investing. And you don’t know what customers actually say about them when your team isn’t in the room.

That ignorance costs companies millions every year in bad product decisions, ineffective positioning, and missed opportunities.

What is Competitive Intelligence?

Competitive intelligence isn’t spying. It’s not hiring private investigators or stealing documents.

It’s respecting the game enough to study the players.

Ben Gilad, who founded the Academy of Competitive Intelligence, calls it “competitive insight”—not data points, but understanding. The kind that lets you make moves nobody else sees because you understand what everyone else is doing.

Most companies collect competitive data. They track product releases, monitor pricing, and capture screenshots of competitor websites. You can even spend a lot of money convincing yourself that the competitive intelligence box is ticked because you invested in a platform.

That’s surveillance, not intelligence.

Intelligence is connecting dots. It’s seeing that three competitors have just hired VPs of Enterprise Sales, and that means the market is shifting upmarket. It’s noticing job postings reveal what your competitor is building six months before they announce it.

And it’s pattern recognition that turns information into action.

The Focus Strategy That Actually Works

Look at the competitive landscape, and you will see product sprawl everywhere. Everyone is trying to be everything to everyone. What if you chose the opposite: own one category so completely that customers don’t even consider alternatives.

Michael Porter calls this a focus strategy. It’s understanding what competitors are doing and choosing a different path.

In a market full of SaaS platforms offering everything, become the specialist that owns their category. Less Rippling and more MHR, for instance.

A decision that requires studying the competition deeply enough to spot the gap nobody else was exploiting.

Why Most Strategy Is Just Expensive Guessing

We consult on Series A and B rounds for startups. The pattern is consistent and depressing.

Founders pitch both massive TAM and niche specialisation in the same deck. They claim to be “the Salesforce of X” and “purpose-built for X vertical.”

Contradictions exist because they arn’t doing competitive intelligence. No one’s asking:

• What positioning is already crowded?

• What gaps really exist?

• Where can we win?

Instead, they’re guessing. Building what they think customers want without checking who else has tried this and failed.

We worked with a marketing automation company in 2023. They wanted to add social media management features. “Our customers are asking for it,” they said. They asked us to confirm this.

Our work showed that the six major players already dominate social media management. Two had tried to expand from marketing automation into social, but retreated after 12 months because integration complexity killed adoption.

The data was public. It was free to see. Nobody looked.

They redirected their roadmap toward workflow automation, where competition was lighter. The feature launched six months later and drove 30% of new enterprise deals.

That change of direction happened because they were open enough to do competitive intelligence to prove or disprove their thinking. We studied what competitors tried, what worked, what failed, and where opportunities existed.

The Blindspots That Kill Companies

Every company has competitive blind spots. The question is whether you’re actively looking for them or ignoring them until they destroy you.

Again, we worked with a project management software company around 2023. They believed their main competitor was Asana. They obsessed over Asana’s features, pricing, and positioning.

Meanwhile, Notion was quietly eating their lunch from an adjacent category. Notion wasn’t even on their competitive radar because “they’re a note-taking app, not project management.”

Customers didn’t care about categories. They cared about solving their workflow problems. Notion’s flexibility solved those problems better than rigid project management tools.

That’s a blind spot. Not seeing threats because they don’t fit your mental model of who you compete with.

Real competitive intelligence forces you to expand your horizons. It asks:

Who else solves the same customer problem?

Who could solve it tomorrow?

Who’s building capabilities that overlap with yours, even if they’re in a different category?

The Pattern Recognition

The best strategists aren’t visionaries. They aren’t futurists with great beards and cool glasses. They’re pattern recognisers. And of course, pattern rejectors.

They see that competitor hiring patterns that predicts future product launches.

They notice when a few competitors move in the same direction and ask why.

And they track which features customers mention in reviews and are getting ignored.

Run a monthly competitive intelligence scan to track:

• Competitor job postings.

• What roles are they hiring? Where are they investing?

• Product changelogs and release notes.

• What are they building?

• What are they killing?

• Customer reviews on G2, Capterra, and Reddit. What are customers actually saying when sales teams aren’t listening?

• LinkedIn activity from their executives and employees. What are they talking about? What problems are they focused on?

• Funding announcements and financial news.

• Where’s money flowing? What’s getting starved?

Every time you do this, compile three insights. Not fifty data points. Three things that matter.

Sometimes it’s “Competitor X just hired their third VP of Sales this year—they’re struggling with go-to-market execution.”

It could be “Four customers mentioned in reviews that they switched from Competitor Y because of poor support response times—there’s an opportunity in customer experience differentiation.”

Or “Two competitors just launched the same feature we were planning—we need to find a different angle.”

These insights drive strategy. They prevent bad decisions. And they surface opportunities before they become obvious to everyone else.

The Moves That Look Like Genius

When Uber started dynamic pricing, people called it a brilliant innovation.

It wasn’t innovation. It was competitive intelligence applied from outside the industry.

Airlines had been doing dynamic pricing for decades. Hotels did it. Events did it. The model was proven. Uber just launched ride-sharing before their competitors did.

That’s not genius. That’s studying adjacent markets, identifying what works, and applying it before everyone else figures it out.

Most breakthrough strategies aren’t breakthroughs. They’re smart applications of competitive intelligence from other industries, markets, or time periods.

Netflix didn’t invent streaming. They studied how Blockbuster failed and built the opposite business model. They watched cable companies bundle content and did the same thing digitally.

Amazon didn’t invent e-commerce. They studied mail-

order catalogues, retail logistics, and Walmart’s distribution strategies. They imported retail intelligence into the digital world.

The pattern is consistent. Study what works elsewhere. Apply it where competitors haven’t figured it out yet. Execute faster.

Why Internal BS Kills More Companies Than Competition

Most companies don’t fail because competitors beat them. They fail because they lied to themselves about their competitive position.

We worked with a B2B SaaS company that claimed “enterprise-ready” positioning while having zero enterprise customers. Their competitor analysis showed they were “better” across every dimension.

The reality was that they’d never used their competitors’ products. They were comparing their own marketing claims to competitors’ claims.

When we did real competitive intelligence. Actual product testing, customer interviews, and win-loss analysis—the truth was a wake-up call.

Their product was easier to use but lacked security features enterprises required. Their support was faster, but only during US business hours. And their pricing looked competitive until you added the features enterprises really needed.

Their competitors were winning because they actually delivered what enterprises needed.

Real competitive intelligence destroys the comfortable stories we tell ourselves. It forces honesty about where you actually stand.

That’s uncomfortable. It’s also essential.

The Small Moves That Builds Positioning

Strategy doesn’t require McKinsey consultants and 200-slide decks.

It requires small, intentional moves based on what the market is already showing you.

Constantly learning what customers want, what margins work, and what they can execute consistently.

That’s competitive intelligence as practice, not theory.

Build something small. Ship it. See how customers respond compared to alternatives. Learn. Adjust. Build the next thing.

Each cycle, you’re gathering competitive intelligence. You’re learning what customers value that competitors aren’t delivering. You’re finding gaps in execution, positioning, or experience.

Over time, these small moves compound into positioning that’s nearly impossible to disrupt.

What Strategy Actually Looks Like

Strategy isn’t about those vision statements and your five-year plans.

It’s about asking better questions:

• What are our competitors doing that we should ignore?

• What are customers complaining about that nobody’s (including us) fixing?

• What trends can we see that haven’t yet hit our market?

• Where are competitors investing that’s leaving other areas undefended?

• What worked in adjacent markets that we could adapt?

These questions only get answered through disciplined competitive intelligence.

Not guessing. Not assuming. And not trusting your gut about what competitors are doing.

Actually looking. Actually tracking. And by analysing.

The Practice That Separates Winners From Pretenders

Most companies treat competitive intelligence as a project. Something you do once during strategy planning. A consultant deliverable. Or a pre-pricing session. A metaphorical binder that sits on a shelf.

With active competitive intelligence, you spot trends earlier. You see threats before they mature. You find opportunities while competitors are still guessing.

And you stop reacting to market moves and start anticipating them.

That’s the difference between strategy theatre and actual strategy.

What to Do Tomorrow

Stop pretending you understand your competitive landscape.

• Select your top three competitors

• Use their products

• Read their customer reviews

• Check their job postings

• Then study their pricing

Then ask yourself:

• What do they know that we don’t?

• What are they building that we’re ignoring?

• And what are customers saying about them that contradicts our assumptions?

Write down three insights. (Not fifty data points). Three things that change how you think about your market position.

Then do it again next week. And the week after.

That’s how you stop guessing and start knowing.

And it’s how you turn strategy from those PowerPoint slides into decisions that have a better chance of winning.

https://www.octopusintelligence.com/think-you-know-your-competitors-you-probably-dont/

The LinkedIn Profile Map: Your Underrated CI Weapon: Weekly Winning Strategies

If you’re doing competitive intelligence without enterprise tools, this is for you.

You don’t need Klue.

And you don’t need a Crayon.

You need 90 minutes a week, LinkedIn’s search bar, and the discipline to think like an analyst, not a browser.

By tracking how a competitor’s team is shifting—who they’re hiring, what they’re renaming, where they’re posting—you can build a working theory of their go-to-market and product roadmap before they tell the world.

This isn’t guesswork.

It’s people-watching at scale.

And it works.

Question: How can LinkedIn profiles be used for competitive intelligence without enterprise tools?

Answer: By systematically tracking title changes, new hires, job descriptions, and content patterns on LinkedIn, you can anticipate a competitor’s go-to-market strategy and product roadmap months before public announcements.

Summary: LinkedIn isn’t just a resume hub—it’s a live feed of strategic intent. By mapping job titles, hires, and post patterns, even small teams can detect competitive shifts early and act faster than larger rivals.

Why LinkedIn Profiles Are a Map, Not a Mirror

Too many founders treat LinkedIn like a resume database.

But here’s the real value: it’s a forward-looking map of company intent.

• Every new job title is a strategic signal.

• Every content theme is a positioning experiment.

• And every regional hire is growth.

LinkedIn profiles don’t reflect where a company is. They reflect where it’s going.

Case Study: How a FinTech Startup Beat a Competitor to LATAM

In 2023, we were advising a bootstrapped B2B FinTech startup—under 50 people, targeting mid-sized accounting firms in the US.

One of their biggest threats was a US-based Series B competitor with aggressive growth targets and a slicker product. Let’s call them LedgerIQ (not the real name).

By Q1, LedgerIQ had a steady content stream, standard hiring in the US, and a strong foothold in SMB finance.

Nothing out of the ordinary.

But one junior product marketer at my client’s company noticed something weird.

“LedgerIQ just hired a Spanish-speaking CS manager based in Mexico City… but they don’t support Spanish yet.”

That single data point kicked off an analysis of a LinkedIn profile map.

Here’s what they found:

• Five new hires in Mexico, Argentina, and Colombia—titles included Regional Partnerships Manager, LATAM Marketing Lead, Spanish-Speaking Implementation Specialist

• Job descriptions hinted at “go-to-market launch planning,” “local compliance adaptation,” and “Spanish-language onboarding”

• No public announcement had been made. The website still said “US only.”

• Content strategy on LinkedIn had subtle shifts—more mentions of “multi-currency,” “international expansion,” “LATAM opportunities”

Within three weeks, we were confident: LedgerIQ was quietly prepping for a LATAM expansion.

My client immediately accelerated its Spanish-language onboarding experience, expanded partnerships with two LATAM accounting software vendors, and began producing localised lead-gen content.

By the time LedgerIQ officially launched in LATAM—93 days later—my client had already landed six anchor clients in the region.

Small signals. Big edge.

How to Build a LinkedIn Profile Map in 5 Steps

You don’t need tools or APIs. You just need focus and a spreadsheet. Here’s how:

1. Identify Key Competitor Personas

Map out 5–10 roles that could isolate a change in their strategy. Examples:

• Product Marketing Manager

• Regional Sales Lead

• Partner Manager

• Solutions Architect

• Implementation Specialist

These roles are usually tied to go-to-market or geographic expansion.

2. Track Title Changes and New Hires

Use LinkedIn search filters:

• Company? (Your Competitor)

• Location? (Emerging Region or is it Global)

• Date Posted? Past Month or sooner? What have they posted in the past?

Look for:

• Title changes (e.g., “Sales Enablement → GTM Strategy Lead”)

• New team members in unexpected locations

• Promotions into newly formed teams (e.g., “Head of LATAM GTM”)

3. Analyse Job Descriptions

Even if you can’t see full listings, check archived job posts on Google Jobs or Wayback Machine.

Focus on:

• GTM language (launch, expansion, product rollout)

• Geography

• New feature mentions (AI, embedded finance, B2B payments, etc.)

• Language or compliance-specific requirements

These clues often beat press releases by months.

4. Watch for Content Pattern Shifts

Follow 5–10 employees from marketing, sales, and product on LinkedIn. Don’t track the brand account—it’s often sanitised.

What to look for:

• New hashtags

• Language localisation

• Geography mentions

• Specific verticals (e.g., “new tools for LATAM tax workflows”)

You’ll spot the new positioning themes long before they go on the website.

5. Log and Compare Monthly

Don’t try to “analyse” every post.

Instead, log 5–10 consistent signals across 3–6 months:

• Growth in regional headcount

• Recurring content themes

• Job post terminology

• Partner manager hires

• Internal title standardisation (e.g., everyone becomes “Customer Experience Architect” — why?)

This lets you see movement patterns over time—not just one-off guesses.

A Strategic Timeline

By tracking team changes, regional hires, and job language, you can model the likely strategy path your competitor is on.

Here’s a simplified example from a real CI map:

The point isn’t to be 100% right.

The point is to move 90 days earlier than your competition.

When This Fails: What NOT to Do

A few common mistakes kill the value of this approach:

• Over-indexing on individual hires

• One CS rep in Brazil doesn’t mean a launch is coming. Wait for a pattern.

• Watching only the company page

• Brand content is usually lagging behind reality. Track individual employees.

• Not timestamping your observations

• Without a timeline, your insights lose predictive power.

• Assuming silence means inactivity

If a competitor goes quiet, it often means they’re building. Not scaling back. It can often mean inactivity, of course. Until it doesn’t. But if you aren’t looking, then you will never know the difference anyway.

Why This Works So Well in B2B SaaS

SaaS GTM motion is resource-heavy and slow to pivot.

Which means:

• Every regional expansion requires hiring in advance

• Every product feature needs enablement and marketing alignment

• Every ICP shift changes who they hire and how they title those hires

The hiring plan becomes the roadmap.

And LinkedIn is where that plan leaks first.

The Takeaway: Quiet Patterns Beat Loud Launches

If you wait for a competitor to make an announcement, you’ve already lost the edge.

But if you build the muscle of watching the people behind the company—before the company updates its homepage—you can:

• Predict product bets

• See market expansion 3–6 months early

• Detect ICP pivots

• Spot pricing strategy changes

And if you’re small?

This is how you win against competitors 10x your size.

Because you’re watching while they’re busy shipping.

Bottom line?

Competitor strategy leaks through people, not press releases.

Track them. Then you’ll spot the playbook before the rest of the market catches on.

Let’s talk…

https://www.octopusintelligence.com/the-linkedin-profile-map-your-underrated-ci-weapon/

Most businesses lose to competitors not because they lack talent, but because they believe their own BS.

The same mental errors that help humans survive. The confirmation bias, faulty causality, and fear of uncertainty. These are the exact forces that undermine sharp competitive analysis.

Your biggest competitor isn’t another company — it’s the story you keep telling yourself.

Why Competitor Analysis Fails: The Brain Lies, Then Believes Its Own Lies

Competitor analysis goes wrong when strategy becomes a faith-based initiative. You think you “understand the market,” when what you actually understand is the version of the market your brain invented to make yourself feel secure.

Question: What is cognitive bias, and how does it sabotage competitor analysis?

Answer: Cognitive bias leads teams to misread competitor behaviour by building narratives based on feelings or assumptions rather than verified data. This distorts strategy, leading businesses to act on internal stories rather than external realities.

Summary: Cognitive biases cause businesses to misinterpret competitors’ moves, leading to poor strategic decisions. This article shows how to strip away false narratives and use observable behaviour to guide real competitive insight.

If you’re not testing that mental model against hard external data, you’re flying blind. And worse, you’re emotionally invested in the wrong flight path.

Let me show you why this happens, how companies fall into the trap, and how to reverse engineer competitor strategy based on actual behaviour. Not the comfortable stories you tell yourself.

The Fake Game: Why False Patterns Feel Real

In a psychology experiment (referenced in Mark Manson’s work), people were told to earn points by pressing buttons. But the system randomly awarded points. Still, everyone left convinced they’d cracked the “winning” pattern.

One guy invented a complicated sequence that made no sense. Another girl jumped to tap the ceiling every few minutes. Total nonsense. But it was deeply believed to be nonsense.

That’s competitor analysis in most startups with revenue under $ 20 M.

The founder sees one feature their competitor launches, a bump in traffic, or a new hire announcement. Then they piece together a narrative: “Ah, they’re changing direction and moving into enterprise!” or “Their growth’s slowing — we’re fine!”

No data. No pattern. Just inference layered on inference.

The result? A confident but inaccurate take.

The brain loves stories. But stories don’t win markets. Patterns of behaviour, tracked over time, do.

The Brain’s Pattern Addiction in Strategy

Here’s what happens inside the minds of strategy teams:

1. They observe a competitor raise funding.

2. They attach meaning: “They’re scaling too fast. Risk of bloat.”

3. They feed that to their team as a win.

4. They stop examining what the competitor is actually doing — pricing changes, GTM partnerships, headcount by function.

This is causation fiction dressed up as market analysis.

A sharp operator doesn’t take signals at face value. They test for repeat behaviour, triangulate using multiple data sources (job boards, customer reviews, dark social, Glassdoor changes, etc.), and track how messaging evolves with each site refresh.

Case Study: Copy.ai vs Jasper – What 99% of People Missed

Copy.ai and Jasper both launched around 2020—same space: AI-powered copywriting tools.

Everyone focused on their homepage design, product features, and pricing changes. That was the surface-level noise.

But when you zoomed out and ran behavioural tracking across:

• New job postings (Sales, CS, Product)

• LinkedIn engagement by persona

• Funding press releases and how fast it hits headcount growth

• G2 review velocity

• Niche community mentions (e.g., Reddit, Indie Hackers)

The story was clearer.

Jasper was aligning with the B2B enterprise market by mid-2022. Their hires shifted toward Account Executives and Partner Marketing.

Copy.ai was doubling down on SMB and growth hacking.

Two different plays. But both still got lumped into the “AI writing tools” category — which led some teams to copy pricing and messaging from the wrong benchmark.

Many misread the game board, and they misplaced their bets.

You Don’t Have a Competitor Problem — You Have a Cognitive Bias Problem

This isn’t just a Copy.ai vs Jasper issue. It’s systemic.

We all do it.

We build a strategy around what feels right. And we build meaning from correlation, not causation. And once we do, we fight like hell to keep it — even when the data says otherwise.

Just like the button-pushing experiment, we keep jumping to tap the ceiling, convinced that’s what makes the light come on.

What we’re actually doing is mortgaging future advantage for short-term psychological comfort.

You can either be right or feel right. Rarely both.

How to Break the Pattern: Market Analysis Grounded in Reality

You need a process that disrupts the brain’s preferred pattern-making. Something like this:

1. Catalogue Behaviour, Not Noise

Track actual actions over time. The product updates, job postings, new hires, pricing shifts, API docs, and partnerships. This tells you what they’re doing, not what they’re saying.

2. Triangulate Intent with External Signals

Pair behaviour tracking with intent signals:

• Job board analysis. The sales hires = push into a new vertical

• Website tech stack. Adding Segment + Clearbit equals prepping for ABM

• LinkedIn advertising changes. New personas are being targeted.

3. Segment by Strategy Layer

Split your analysis into three verticals:

• GTM Motion (How they sell)

• Product Roadmap (Where they’re investing)

• Positioning (How they explain their value)

This removes emotional bias and focuses on function rather than feeling.

4. Kill Old Narratives Quarterly

Create a standing review to invalidate your previous assumptions. Ask:

• What did we believe 90 days ago?

• What no longer holds up?

• What do their current behaviours contradict?

Forcing the team to let go of old beliefs clears the slate for better pattern recognition.

Uncertainty Is a Strategic Weapon

Most founders think certainty is strength.

It’s not.

Certainty hardens your perception. You stop seeing. You stop adapting.

The strongest strategists run constant micro-tests on their own beliefs. They treat every signal as a hypothesis to be validated. Never a truth to anchor to.

Being uncertain opens you to what is, not what you wish it were.

It’s not “we’re better than Competitor X.” It’s: “They’re moving toward this market. Here’s what that means for our acquisition motion. What are our three counter-moves?”

Competitive strategy isn’t about feeling confident. It’s about staying curious. Always.

A Final Word: Stop Tapping the Ceiling

If your market analysis starts with a homepage scroll and ends in a Slack thread of opinions, you’re not analysing — you’re rationalising.

Ask yourself:

“What’s the ceiling I’ve been tapping in this business?”

It could be a competitor you assume is always ahead. Or a pricing belief you refuse to test. Or a customer segment you’re emotionally attached to but doesn’t scale.

Your brain will keep lying to you. That’s its job. But your job is to catch the lie, question the story, and build strategy from verified actions — not assumptions.

Be ruthless with your meaning-making.

Because in the end, markets reward action, not belief.

Let go of the need to “know.”

Start tracking what’s real.

Then build your edge — not by guessing better, but by thinking less.

Frequently Asked Questions (FAQs)

1. What is the biggest mistake companies make in competitor analysis?

Most companies assume correlation equals causation. They see a competitor make a move and invent a story around it — often without verifying the behaviour through multiple data points.

2. How can I do better competitor research with limited tools or budget?

Use free tools like LinkedIn job posts, G2 reviews, BuiltWith, and Google Alerts. Then build a habit of comparing behaviour over time — not just reacting to announcements.

3. How do I stop emotional bias in competitive strategy?

Run quarterly assumption audits. Document what you believe about each competitor, then test each belief against observed behaviour. Remove anything that no longer holds up.

4. What should I track to understand a competitor’s strategy?

Track new hires by function, product updates, pricing changes, partnerships, ad targeting, and positioning language. These show where they’re actually going — not where they say they are.

5. Why is uncertainty helpful in market analysis?

Uncertainty keeps you open to learning. The more you believe you “know,” the less you test, adapt, or notice real shifts in the market. Confidence is a poor substitute for clarity.

6. How do I separate noise from useful competitive signals?

Ignore what can’t be verified by repeated behaviour. Focus on signals tied to action: headcount growth, fundraising tied to execution, and GTM shifts. Skip PR spin.

7. What companies are good examples of clear competitor strategy?

Companies like Loom, Notion, and Descript — all under 10 years old — have used public behavioural signals (e.g., feature launches, user segmentation) to execute clear and observable strategy shifts.

8. Can startups without a strategy team still do strong market analysis?

Yes. The key is to build a simple, repeatable process: weekly check-ins on competitors, a monthly summary of movements, and a quarterly strategic implications review. One person can run it.

9. How often should I update my competitive positioning?

Every 90 days at a minimum. The market shifts too fast to leave your positioning on autopilot. You don’t need to overhaul messaging, but you do need to revalidate your assumptions.

10. What’s the difference between competitor analysis and strategy?

Competitor analysis is an observation. Strategy is a response. But your strategy is only as good as your observation is accurate. Get the inputs wrong, and you’ll act on fantasy.

Let’s talk…

https://www.octopusintelligence.com/stop-guessing-how-cognitive-bias-is-sabotaging-your-competitor-analysis/

The Two-Path Trap in Competitor Analysis: Weekly Winning Strategies

Most competitor analysis treats business problems like coin flips—two sides, one choice. The companies winning right now see problems as prisms with dozens of refracting angles, and they’re capturing opportunities everyone else is missing.

Question: What is the third-path strategy in competitive intelligence?

Answer: The third-path strategy in competitive intelligence involves rejecting false binary choices—such as “compete on price or features”—and uncovering overlooked approaches that address the real customer problem. Gain an edge by identifying unexpected opportunities through customer insight, adjacent market analysis, and challenging assumptions.

Summary: Winning companies don’t settle for binary decisions. They find and act on overlooked paths by understanding deeper customer needs and blind spots in their competitors’ strategies.

Like that marketing automation company, which imploded in 2021 because it saw its strategic problem in binary terms.

They had two options:

1. Compete on price

2. Or compete on features

They chose features. Built a product with 847 different capabilities. Lost to a competitor with 12 core functions priced 40% lower.

The real problem wasn’t their choice. It was assuming only two paths existed.

While they debated features versus price, their actual competitor was building a community. They created a network effect through integrations, user-generated templates, and a marketplace that turned customers into stakeholders.

Third path. Nobody saw it coming.

Why Binary Analysis Kills Companies

Every business problem looks binary when you’re moving too fast to think properly.

Build or buy. Expand or consolidate. Invest or cut costs. Hire or automate.

Competitive intelligence can paralyse companies with these false choices. The analysis becomes a cage.

Berlin eye opener

Still, this situation is better than what I experienced at a recent conference in Berlin on competitive intelligence. Big corporations presented how they are using AI and secondary data for competitive intelligence. However, few could explain where their data came from, how they validated it, or, most importantly, what they did with it and what decisions they actually made based on it.

I spent three days surrounded by Power BI dashboards, AI-driven summaries, and executives addressing rooms full of analysts on how they were utilising “granular data” to gain an edge.

The Berlin Reality: Data Without Context

Worse still, several presenters admitted their market intelligence work relies heavily on assumptions. One said they use AI and their secondary-based competitive intelligence to “prove” their own hypotheses about competitors. Another admitted their system “pulls everything public” and then “summarises it beautifully” in dashboards. Totally missing the Humint route.

So, most of these individuals have no idea if they are on the right path, let alone the right one.

The Multi-Path Reality

Real competitive advantage comes from seeing paths your competitors don’t know exist.

Take a look at the streaming wars from 2019 to 2024. Everyone framed it as a binary choice:

Netflix vs Disney+. Content volume vs content quality. Subscription vs ad-supported. Global vs regional.

Apple said “none of the above” and built Apple TV+ as a loss leader bundled with hardware and services.

Amazon made Prime Video a retention tool for e-commerce.

YouTube challenged the entire premise by staying free with ads.

Five different paths to the same market. Only one company (Netflix) was actually playing the game everyone thought they were playing.

How to Find the Hidden Paths

Stop asking “which option is better”

And start asking, “what problem are we actually solving?”

Reframe the Customer Problem

Most binary thinking starts with product-centric questions. Flip it to customer-centric framing.

Instead of:

“Do we add feature X or improve performance Y?”

Ask

“What job is the customer hiring our product to do?”

We consulted for a project management software company in 2022. They were stuck on the question: “Do we build better reporting or better collaboration tools?”

We interviewed customers. It turned out that the real problem wasn’t reporting or collaboration. It was “how do I prove my team’s value to executives who don’t understand our work?”

The third path of developing stakeholder visibility tools that translate project data into business impact metrics.

All resulting in a different problem, a different solution, and a different competitive position.

Map Competitor Blind Spots

Your competitors are likely trapped in the same binary thinking as you.

When everyone sees two paths, the third path is wide open.

Consider the food delivery sector from 2018 to 2020. DoorDash and Uber Eats in the US fought over restaurant selection and delivery speed. Binary competition—more restaurants or faster delivery.

Then COVID hit. Suddenly, the market needed: contactless delivery, family meal options, grocery integration, and restaurant survival tools.

The companies that had been exploring non-binary paths (DoorDash Kitchens, Uber Direct) were ready. The companies stuck in the delivery speed versus restaurant selection debate had to rebuild their entire strategy.

We spoke with Deliveroo before COVID (thinking about it, it was actually well before COVID, probably in 2018). The UK head was primarily interested in identifying the restaurants their competitors had and how they could persuade those restaurants to sign up with them. (and seeing how cool they could have their London office interior) How the world changed.

On the same visit, I also attended Autotrader’s London HQ, and they had old Minis driving on the ceiling, so Deliveroo’s HQ wasn’t even the coolest on the day. Anyway, back to the article...

The Intelligence Framework for Multi-Path Analysis

Here’s how you could break binary thinking:

Step 1: List the Obvious Paths

Write down the two options everyone sees. This is your baseline. These paths are probably crowded with your competition.

Step 2: Question the Constraints

What assumptions are baking these two options into existence?

“We must compete on price or features” assumes customers choose based on value calculations.

What if they choose based on trust, convenience, or network effects instead?

Step 3: Study Adjacent Markets

How do companies in related industries solve similar problems?

When Airbnb faced the binary choice of “more listings or better quality control,” they studied luxury hospitality, boutique hotels, and even cruise lines.

That research led to Airbnb Plus, Airbnb Luxe, and Experiences—multiple paths, rather than a single binary choice.

Step 4: Interview Customers Who Left

Lost customers reveal paths you’re not seeing.

A SaaS company we worked with believed they were losing deals to cheaper competitors or more feature-rich alternatives. Exit interviews revealed a third path: customers weren’t buying anything. They were building internal solutions using no-code tools.

New competitor category. New strategic response needed.

Real-World Multi-Path Mapping

Let me illustrate this with a 2023 example.

A cybersecurity company came to us with a binary problem: “Do we sell to IT departments or security teams?”

Standard analysis said pick one. IT departments had bigger budgets. Security teams had more urgency.

We mapped the actual buying process across 30 recent deals. Found something interesting.

Neither IT nor security teams made the final call. Legal and compliance teams were driving 68% of purchase decisions due to regulatory requirements surrounding data protection.

The third way

Three additional paths emerged:

They chose Path 4 and 5 combined. Revenue jumped 340% in 18 months by avoiding the binary choice everyone else was fighting over.

The Competitive Intelligence Discipline

Seeing multiple paths requires different information sources than those used in binary analysis.

Track Non-Obvious Competitors

Don’t just monitor direct rivals. Watch companies solving adjacent problems.

When Notion started competing with project management tools in 2020, most PM software companies didn’t notice. They were watching Asana and Monday.com. Notion wasn’t coming from project management. They were coming from note-taking and knowledge management. Different path. Same customer problem.

Monitor Customer Behaviour Changes

Markets create new paths when customer behaviour shifts.

The rise of TikTok from 2019 to 2021 wasn’t just about short videos. It revealed that customers wanted (even if they didn’t know it themselves): algorithm-driven discovery, authentic creator content, and participation without production quality barriers. Companies stuck in the “Instagram vs YouTube” binary thinking missed the entirely new path TikTok was cutting.

Study Regulatory and Technology Shifts

New paths often open when infrastructure changes.

GDPR created new competitive paths around privacy and data ethics. 5G is creating paths around edge computing and real-time applications. AI is creating paths around automation and augmentation. The companies that win are those that saw these as new paths, not just modifications to existing binary choices.

Why This Matters Now

Markets are moving too fast for binary thinking.

Companies are currently making decisions without having all the necessary information. Stuck in false choices like:

“Do we adopt AI or protect our existing workflow?”

Wrong question.

The path is figuring out where AI augments humans and where humans add value that AI can’t match.

“Do we compete on product or community?”

Wrong question.

The path is understanding what role each plays in customer retention and expansion.

“Do we focus on acquisition or retention?”

Wrong question.

The path is building growth models where retention drives acquisition through network effects.

The Analysis You Need to Run

Stop your next strategy meeting and do this exercise:

1. Write down your biggest competitive challenge.

2. List the two paths everyone agrees are the options.

3. Now force your team to find five more paths. Not better versions of the original two. Completely different approaches that solve the underlying problem.

4. Interview customers. Study adjacent markets.

5. Question your assumptions about what business you’re actually in.

The third path is where the opportunity lives. The fourth and fifth paths are where you build competitive moats.

Moving Forward

Binary thinking is a cognitive shortcut that may feel efficient, but ultimately costs you market position.

The companies dominating their markets right now—Shopify in e-commerce infrastructure, Figma in design tools, Stripe in payments—won by seeing paths their competitors didn’t know existed.

Your competitor analysis should map the entire landscape, not just the two roads everyone else is travelling.

Find the paths nobody’s walking yet. That’s where you build the business everyone will be studying five years from now

https://www.octopusintelligence.com/the-two-path-trap-in-competitor-analysis/

How to Predict a Competitor’s Product Launch from Patent Filings, GitHub, and Trademark Records: Weekly Winning Strategies

Most companies react to competitor launches 6 months too late—but patent filings, GitHub commits, and trademark applications reveal product roadmaps 18-24 months in advance.

The $5M Product Launch They Saw Coming Two Years Early

In March 2022, they noticed something interesting in the USPTO database: Apple had filed a patent for “augmented reality contact lens display systems.” Most people ignored it as typical Apple experimentation.

Question: How can companies predict a competitor’s product launch 18–24 months before it happens?

By monitoring public patent filings, GitHub commits, and trademark applications, businesses can identify patterns that reveal product development timelines, technology focus areas, and go-to-market strategies well before any public announcement..

Tracking patents, GitHub activity, and trademark filings provides early visibility into a competitor’s future products—often revealing their roadmap up to two years ahead of a public launch. These signals offer a strategic edge that press releases and analyst reports can’t match.

But the filing details were too specific. The patent included manufacturing processes, user interface mockups, and partnership structures with optical companies. This wasn’t research—this was product development. They started tracking related signals:

• Apple’s hiring spree of optical engineers on LinkedIn

• Trademark applications for “iSight Contact” and “Vision Touch,”

• GitHub repositories with AR eye-tracking code commits.

By late 2022, the pattern was undeniable. Apple wasn’t just researching AR contacts—they were building them. The intelligence enabled this wearable tech firm to adjust its roadmap, secure partnerships with contract manufacturers, and position itself as the enterprise solution before Apple launched its consumer products.

When Apple finally announced their AR contact initiative in 2024 (still in development), they had already captured 40% of the enterprise AR contact market.

The total competitive advantage from free public record intelligence: $5M in revenue protection and market positioning.

Why Public Records Beat Press Releases by 24 Months

Not surprisingly, companies tend to announce products after they have been built. Patent filings reveal products while they’re being conceived. GitHub commits show development progress in real-time. Trademark applications expose branding strategies before marketing campaigns launch.

It is also annoying that your best competitors will hide their strategic intentions from industry analysts and journalists. But they can’t hide their intellectual property filings, development code, or legal trademark protection from public databases.

This intelligence gap creates significant competitive advantages for those willing to delve into government databases and open-source repositories.

The Three-Source Intelligence System

Patent Filings: The Strategic Intent Decoder

Patent applications reveal not just what they are building, but how they plan to develop it and why it matters strategically:

USPTO Database (patents.uspto.gov):

Free access to all US patent applications and grants. Search by company name, inventor, or technology keywords.

Google Patents (patents.google.com)

More user-friendly interface with better search functionality and international patent coverage.

WIPO Global Brand Database

International patent and trademark filings reveal global expansion plans.

Key intelligence indicators in patent filings:

• Detailed technical specifications indicate a serious development commitment

• Multiple related patents suggest comprehensive product strategies

• Partnership mentions in filings reveal strategic relationships

• Manufacturing process patents indicate production readiness

• User interface mockups show customer experience priorities

We tracked a fintech competitor through their patent filings and discovered that they had been building an AI-powered fraud detection system for 18 months before their product launch. The patents revealed their exact machine learning approach, data sources, and implementation timeline.

GitHub Repositories: The Development Progress Tracker

Open source code commits provide real-time visibility into product development:

Public Repositories

Direct access to competitor development progress, feature priorities, and technical architecture decisions.

Contributor Activity

Track which companies’ employees are contributing to which projects and technologies.

Commit Message Analysis

Development priorities and timeline insights from commit descriptions and branch naming.

Issue Tracking

Bug reports and feature requests reveal product limitations and roadmap priorities.

Fork and Star Patterns

Community interest and adoption indicators for new technologies and approaches. GitHub intelligence requires technical expertise but reveals incredibly detailed roadmap information. We assisted a cybersecurity client in tracking their competitor’s API development through GitHub commits, enabling them to build compatible integrations before the official API launch.

Trademark Applications: The Brand Strategy Crystal Ball

Trademark filings reveal branding strategies, product names, and market expansion plans:

USPTO TESS Database

Free trademark search revealing all US trademark applications and registrations.

TMView (European Union)

EU trademark database showing international brand protection strategies.

Madrid System Database

International trademark applications reveal global expansion plans.

Trademark intelligence indicators:

• Product name registrations indicate launch timeline (companies typically file 6-12 months before launch)

• Service category classifications reveal intended market segments

• Geographic filings show expansion priorities

• Multiple related trademarks suggest product line extensions

• Defensive registrations indicate strategic importance

A SaaS client discovered their competitor’s enterprise pivot through trademark filings: applications for “EnterpriseFlow,” “BusinessSync,” and “CorporateHub” all filed within two months, clearly indicating upmarket positioning.

Case Study: The Shopify Commerce Revolution Prediction

In early 2021, we were monitoring patent and trademark databases for an e-commerce platform client when we discovered Shopify’s master plan:

Patent Intelligence:

• 23 patents filed for “distributed commerce infrastructure”

• Detailed specifications for multi-vendor marketplace technology

• Manufacturing and fulfilment automation patents

• Cross-border payment processing innovations

• AI-powered inventory optimisation systems

GitHub Signals:

• New repositories for “commerce-infrastructure” and “marketplace-core”

• Hiring activity focused on marketplace and payments engineers

• Open source contributions to multi-vendor commerce frameworks

• API development for third-party seller integrations

• Mobile SDK updates supporting marketplace functionality

Trademark Applications:

• “Shopify Markets” filed across 47 countries

• “Commerce Exchange” trademark applications

• “Unified Commerce” brand protection filings

• International marketplace-related trademark clusters

• Payment processing service mark applications

The pattern revealed Shopify’s transformation from a simple e-commerce platform to a comprehensive commerce infrastructure provider—18 months before their public strategy announcement.

Our client used this intelligence to:

• Partner with complementary service providers before Shopify acquires them

• Develop specialised features for market segments that Shopify was abandoning

• Position themselves as the “boutique alternative” to Shopify’s platform approach

• Secure enterprise contracts by emphasising personalised service vs. platform commoditisation

Result

They maintained a 65% customer retention rate and grew revenue by 40% during Shopify’s aggressive expansion, rather than being steamrolled by a much larger competitor.

Building Your Intelligence Collection System

Patent Monitoring Setup

Create systematic patent search strategies:

• Company name searches: “assignee:(competitor name)”

• Inventor tracking: Monitor key engineers and executives

• Technology keyword alerts: Industry-specific terms and innovations

• Classification code monitoring: International Patent Classification (IPC) codes for your industry

• Related company searches: Subsidiaries, partnerships, and acquisition targets

Set up Google Alerts for patent publications:

• “site:patents.google.com competitor name”

• “site:patents.uspto.gov assignee competitor”

• Patent-specific news alerts for industry publications

GitHub Intelligence Workflows

Monitor competitor development activity:

• Repository watching: Star key competitor repositories for update notifications

• Organisation following: Track all repositories under competitor GitHub organisations

• Contributor monitoring: Follow key competitor employees and track their commits

• Technology trend tracking: Monitor emerging technologies that competitors are adopting

• API development surveillance: Track new integrations and platform capabilities

Use GitHub’s advanced search operators:

• org:competitor-name language:python (language-specific development)

• user:competitor-employee pushed:>2024-01-01 (recent activity)

• org:competitor-name “API” “integration” (specific functionality)

Trademark Surveillance System

Establish trademark monitoring workflows:

• Weekly USPTO TESS searches for competitor names

• International trademark database monitoring

• Brand protection filing analysis

• Product name speculation and verification

• Market expansion geographic analysis

Create Google Alerts for trademark activity:

• “site:uspto.gov trademark competitor name”

• “trademark application competitor name filed”

• Industry publication trademark news alerts

Intelligence Techniques

Patent Citation Analysis

Track how competitors reference existing patents:

• Which technologies are they building upon?

• What prior art are they trying to circumvent?

• Which companies are they collaborating with through cross-licensing?

• What patent thickets are they creating for defensive purposes?

Patent citation patterns reveal technology relationships and strategic partnerships before public announcements.

GitHub Network Analysis

Monitor contributor patterns and repository relationships:

• Which open source projects are competitors contributing to?

• What technologies are they adopting through community involvement?

• Which developers are switching between competing organisations?

• What experimental projects suggest future product directions?

Trademark Opposition Research

Monitor trademark opposition proceedings:

• Which trademarks are competitors challenging?

• What brand conflicts reveal market expansion plans?

• Which trademark abandonments indicate strategic pivots?

• What international filing patterns show geographic priorities?

Human Intelligence (HUMINT) Integration

Combine public record intelligence with human sources:

Conference and Trade Show Intelligence

• Patent inventors speaking at technical conferences

• GitHub contributors presenting at developer events

• Trademark attorneys discussing client strategies at legal conferences

• Technical demonstrations revealing patent implementation progress

Professional Network Analysis

• LinkedIn connections between patent inventors and industry partners

• GitHub collaborations indicating business relationships

• Legal counsel relationships suggesting patent strategy coordination

• Academic partnerships revealed through patent co-inventorship

Industry Expert Interviews

• Patent attorneys specialising in competitor technologies

• Former competitor employees with patent and development knowledge

• Industry analysts tracking competitor intellectual property strategies

• Technical consultants working with multiple companies in your space

Reading the Intelligence Signals

High-Confidence Launch Indicators:

Patent Maturity

Detailed implementation specifications, rather than broad conceptual descriptions, indicate a serious development commitment.

GitHub Acceleration

Increased commit frequency and contributor additions suggest that approaching launch timelines are imminent.

Trademark Clustering

Multiple related brand filings within short timeframes indicate comprehensive preparation for a product launch.

Cross-Platform Consistency

Same technology themes appearing across patents, GitHub, and trademarks confirm strategic priorities.

Early-Stage Speculation Signals:

Research Patents

Broad, conceptual filings exploring possibilities rather than defining implementations.

Experimental Repositories

Proof-of-concept code without production infrastructure or documentation.

Defensive Trademarks

Brand protection filings without corresponding patent or development activity.

Academic Collaboration

University partnerships and research paper citations suggest early-stage investigation.

Competitive Response Strategies

When intelligence reveals competitor development activity:

Immediate Actions (1-4 weeks):

• Accelerate parallel development efforts to maintain competitive parity

• File competing patents to create freedom-to-operate challenges

• Secure trademark protection for alternative brand strategies

• Begin building technical expertise in identified technology areas

Medium-Term Strategy (1-6 months):

• Partner with technology providers before competitors can acquire them

• Develop alternative technical approaches, circumventing competitor patents

• Build customer education and thought leadership around emerging technologies

• Create strategic partnerships complementing anticipated competitor offerings

Long-Term Positioning (6-24 months):

• Invest in next-generation technologies beyond the competitor’s current focus

• Build patent portfolios, creating defensive and offensive intellectual property positions

• Establish market positions in segments that competitors are likely to abandon

• Develop acquisition strategies for companies with complementary patent portfolios

Legal and Ethical Considerations

All public record intelligence operates within legal boundaries:

Patent Information

Published patent applications are public records intended for disclosure and the advancement of innovation.

GitHub Code

Open source repositories are publicly accessible with explicit sharing intentions.

Trademark Filings

Trademark databases exist to promote public transparency and prevent conflicts.

However, maintain ethical standards:

• Focus on strategic intelligence rather than copying specific implementations

• Respect intellectual property rights and avoid patent infringement

• Use intelligence for competitive positioning rather than sabotage

• Maintain confidentiality of analysis and insights until competitive responses are implemented

The 90-Day Intelligence Operation

Days 1-30: Foundation Building

• Set up patent, GitHub, and trademark monitoring systems

• Identify key competitors and their intellectual property portfolios

• Establish baseline understanding of current competitive positioning

• Create intelligence collection and analysis workflows

Days 31-60: Pattern Recognition

• Analyse filing patterns and development trends

• Identify technology focus areas and strategic directions

• Track timing patterns between filings and product launches

• Build predictive models for competitive move timing

61-90: Strategic Implementation

• Develop competitive response strategies based on intelligence findings

• Implement product roadmap adjustments addressing anticipated competition

• File defensive patents and trademarks protecting your strategic interests

• Build partnerships and capabilities to counter expected competitive moves

The Unfair Advantage

This is what your competitive intelligence teams should be doing. Managing the competitor monitoring machine and creating newsletters and battlecards are important, but these types of activities are not enough to elevate your game.

Most companies react to competitor announcements rather than predicting them. Public record intelligence provides 18-24 months’ warning of strategic moves.

While competitors spend millions on market research and strategy consulting, their actual plans are often documented in free government databases and open-source repositories.

This intelligence asymmetry creates significant competitive advantages for those willing to monitor public records and development activity systematically.

Your competitors are already revealing their next two years of product development.

The question is: are you reading the signals they’re broadcasting to the world?

Start with one competitor. Monitor their patents, GitHub activity, and trademark filings for a period of 30 days. You’ll never look at competitive intelligence the same way again.

Let’s talk…

https://www.octopusintelligence.com/how-to-predict-a-competitors-product-launch-from-patent-filings-github-and-trademark-records/

Real-Time Intelligence from Reddit, Discord, and Hacker News: Weekly Winning Strategies

Your competitor’s angry customers are broadcasting their exact pain points on Reddit, Discord, and Hacker News—while you’re still reading sanitised G2 reviews.

The $300K Feature That Started with a Reddit Rant

Six months ago, we were monitoring r/SaaS for a project management client when I spotted a brutal thread: “Why does [Competitor] make it impossible to bulk edit tasks?” The post had 47 upvotes and dozens of comments from frustrated users sharing workarounds and threatening to switch platforms.

The Question: How can companies identify hidden customer frustrations and competitive opportunities without spending on traditional market research?

Answer: By monitoring real-time conversations on Reddit, Discord, and Hacker News, companies can uncover unfiltered complaints, feature gaps, and switching triggers that competitors often miss.

Companies can gain a competitive edge by tracking unfiltered user feedback on Reddit, Discord, and Hacker News. These platforms expose real pain points and switching behaviour in ways traditional research often misses.

Within a week, three more complaints appeared across different subreddits. Discord servers echoed the same frustration. Hacker News discussions mentioned it as a major limitation.

My client’s response

Build bulk editing as their next major feature and launch a targeted campaign highlighting this exact capability. The result? $300K in new revenue from competitor switchers who found exactly what they were looking for.

The intelligence wasn’t hidden in expensive user research or focus groups. It was sitting in public forums where real users vent their real frustrations in real-time.

Why Forum Intelligence Beats Survey Data

Traditional competitive research asks customers what they think. Forum intelligence captures what they actually feel when nobody’s taking notes for a case study.

Reddit users aren’t performing for marketers. Discord conversations aren’t filtered through PR teams. Hacker News discussions cut through product marketing fluff to address real technical limitations.

These platforms reveal three types of intelligence you can’t get anywhere else: unfiltered frustration (what really bothers users), genuine feature requests (what they actually need), and switching triggers (what makes them leave).

The Three-Platform Intelligence System

Reddit: The Complaint Cathedral

Reddit is where customers go to solve problems and share frustrations. The key subreddits reveal different intelligence layers:

Product-Specific Subreddits: Direct user discussions about your competitors’ products. Search for subreddits like r/Notion, r/Slack, or r/Monday.

Industry Communities: Broader discussions comparing solutions. Try r/ProjectManagement, r/MarketingAutomation, or r/DataScience.

Problem-Solving Communities: Users seeking alternatives and solutions. Monitor r/SaaS, r/Productivity, r/Entrepreneur.

Technical Communities: Deep dives into product limitations and integrations. Check r/APIs, r/NoCode, r/DevOps.

I tracked a CRM competitor through r/Sales and discovered users consistently complained about their mobile app crashing during client meetings. This became my client’s primary competitive message: “The CRM that actually works when you’re with customers.”

Discord: The Real-Time Feedback Loop

Discord servers provide immediate, unfiltered reactions to product updates, pricing changes, and competitor moves:

Official Company Servers: Join competitor Discord communities to monitor user feedback and support requests directly.

Industry Servers: Professional communities discussing tools, workflows, and recommendations.

Product Hunt Communities: Early reactions to new launches and feature releases.

Developer Communities: Technical discussions about integrations, APIs, and implementation challenges.

Discord conversations happen in real-time, revealing immediate user sentiment that doesn’t make it to public reviews or social media.

Hacker News: The Technical Truth Detector

Hacker News discussions cut through marketing claims to examine actual product capabilities:

Show HN Posts: New product launches with immediate technical feedback from experienced users.

Ask HN Threads: Users seeking tool recommendations with honest comparisons.

Discussion Threads: Deep technical analysis of product announcements and industry trends.

Job Posting Comments: Insights into which tools companies actually use versus what they claim publicly.

Hacker News users have zero patience for marketing speak. Their comments reveal technical limitations, scalability issues, and implementation realities that never appear in official documentation.

Case Study: The Slack Enterprise Warning System

In early 2023, we were monitoring Discord servers and Reddit for a team communication client when Slack enterprise customers started complaining about performance issues during large meetings.

Reddit Intelligence:

• Multiple posts in r/Slack about call quality degradation

• IT managers in r/sysadmin are discussing Slack performance problems

• Remote work communities sharing Slack alternatives for large teams

Discord Signals:

• IT professionals servers discussing Slack enterprise limitations

• Startup founder communities mentioning Slack scaling issues

• Developer servers are comparing Slack’s API limitations to alternatives

Hacker News Analysis:

• Technical discussions about Slack’s architecture constraints

• Comment threads revealing enterprise customer frustration

• Job posting discussions mentioning “Slack alternative” requirements

The pattern

The pattern was clear: Slack’s enterprise customers were hitting performance limits and actively seeking alternatives.

Our client immediately launched an “Enterprise Scale” messaging campaign, highlighting their superior performance for large teams. They created targeted content addressing every specific complaint found in forum discussions.

Within three months, they’d converted 12 enterprise accounts directly from Slack, generating $1.8M in new annual recurring revenue. The intelligence cost was zero—just time spent reading public forums.

Building Your Forum Intelligence System

The Monitoring Setup

Create Google Alerts for competitor mentions across platforms:

• “site:reddit.com competitor name problem”

• “site:reddit.com competitor name vs alternative”

• “site:reddit.com competitor name switching”

• “site:reddit.com competitor name integration”

• “site:reddit.com competitor name pricing”

Use Reddit search operators for deeper intelligence:

• subreddit:r/productivity competitor name

• title:competitor name flair:question

• selftext:competitor name alternative

The Daily Forum Sweep (15 minutes)

Morning routine for real-time intelligence:

• Check Reddit alerts and saved searches

• Scan relevant Discord servers for new discussions

• Review Hacker News comments on competitor-related posts

• Screenshot particularly revealing complaints or feature requests

The Weekly Deep Dive (45 minutes)

Comprehensive analysis for pattern recognition:

• Analyse complaint themes across platforms

• Track feature request frequency and urgency

• Monitor user sentiment changes over time

• Identify switching triggers and competitor weaknesses

The Monthly Intelligence Report (60 minutes)

Compile findings into actionable insights:

• Top competitor pain points mentioned across platforms

• Most requested missing features or improvements

• Common switching triggers and decision factors

• Emerging competitive threats or market shifts

Advanced Forum Intelligence Techniques

The Sentiment Timeline Tracking

Monitor how user sentiment changes over time:

• Post-launch honeymoon period discussions

• Growing complaint frequency and intensity

• Feature request evolution and urgency

• Switching conversation volume increases

Create timeline charts tracking sentiment shifts to predict competitive opportunities.

The Cross-Platform Verification Method

Validate intelligence across multiple forums:

• Reddit complaint appears in Discord discussions

• Hacker News technical criticism confirmed by Reddit users

• Discord feature requests echoed in Reddit communities

Cross-platform consistency indicates genuine market needs versus isolated complaints.

The User Journey Mapping

Track individual users across platforms discussing the same issues:

• Initial Reddit post seeking advice

• Follow-up Discord questions about alternatives

• Final Hacker News comment about switching solutions

This reveals the complete customer switching journey and decision timeline.

The Integration Pain Point Detection

Monitor technical discussions about competitor integrations:

• API limitation complaints in developer forums

• Webhook reliability issues in technical communities

• Data export difficulties in migration discussions

• Security concern conversations in IT communities

Integration pain points often trigger enterprise customer switches.

Reading the Forum Signals

High-Value Intelligence Indicators

Repeated Complaints: Same issue mentioned across multiple platforms indicates systemic problems.

Technical Criticism: Developer communities highlighting architectural limitations reveal scalability concerns.

Pricing Frustration: Cost-related complaints suggest competitive pricing opportunities.

Feature Gap Discussions: Missing capability conversations reveal product development priorities.

Migration Conversations: Users actively discussing switches indicate immediate competitive opportunities.

Low-Value Noise to Ignore

Single Negative Reviews: Isolated complaints without supporting evidence across platforms.

Obvious Competitor Plants: Suspiciously promotional posts about alternatives.

Technical Trolling: Unconstructive criticism without specific examples or evidence.

Off-Topic Rants: General industry complaints unrelated to specific products.

The Competitor Switching Playbook

When forum intelligence reveals switching conversations:

Immediate Response (24-48 hours):

• Create targeted content addressing specific pain points

• Develop comparison materials highlighting your advantages

• Prepare sales battlecards for competitive situations

• Train the customer success team on competitor weakness talking points

Medium-Term Strategy (1-4 weeks):

• Launch targeted advertising to competitors’ frustrated users

• Create case studies showing successful migrations from that competitor

• Develop integration tools or services to ease the switching process

• Partner with consultants helping companies migrate from competitors

Long-Term Positioning (1-6 months):

• Build product features directly addressing competitor limitations

• Position thought leadership content around competitor weaknesses

• Develop strategic partnerships that highlight competitive advantages

• Create customer advocacy programs featuring competitor switchers

Automation Tools for Scale

Reddit Enhancement Suite (RES)

Browser extension enabling advanced Reddit monitoring:

• Keyword highlighting for competitor mentions

• User tagging for tracking influential community members

• Advanced filtering for relevant discussions

• Dashboard customisation for intelligence gathering

Discord Bots for Monitoring

Custom bots can monitor server discussions:

• Keyword alerts for competitor mentions

• Sentiment analysis of user comments

• Automatic screenshot capture of relevant conversations

• Daily digest summaries of competitive intelligence

Browser Bookmarklets for Quick Capture

Simple JavaScript bookmarklets for rapid intelligence collection:

• One-click screenshot with URL capture

• Automatic copying of text with source attribution

• Quick note-taking overlay for forum discussions

• Batch saving of multiple posts to the intelligence database

Forum Intelligence, Ethics, and Best Practices

Respect Community Guidelines:

• Don’t spam communities with promotional content

• Avoid obvious corporate monitoring activities

• Contribute value to discussions when appropriate

• Respect user privacy and community norms

Maintain Professional Boundaries:

• Focus on product feedback, not personal information

• Use intelligence for competitive positioning, not sabotage

• Verify forum intelligence through multiple sources

• Keep monitoring activities transparent and ethical

Data Quality Standards:

• Screenshot original posts before they can be deleted

• Record timestamps and context for all intelligence

• Verify user authenticity when possible

• Cross-reference forum claims with other intelligence sources

The 30-Day Forum Intelligence Sprint

Week 1: Foundation Setup

• Identify relevant Reddit communities and Discord servers

• Set up Google Alerts for competitor monitoring

• Create an intelligence collection spreadsheet

• Establish a daily monitoring routine

Week 2: Pattern Recognition

• Analyse common complaint themes

• Track feature request patterns

• Monitor user sentiment trends

• Identify key community influencers

3rd Week: Competitive Response Development

• Create content addressing identified pain points

• Develop messaging highlighting competitive advantages

• Prepare sales materials for switching conversations

• Plan product roadmap adjustments based on insights

Week 4: Intelligence Integration

• Share findings with product and marketing teams

• Implement competitive positioning adjustments

• Launch targeted campaigns based on forum intelligence

• Establish an ongoing intelligence reporting process

The Unfair Advantage

Most companies ignore forum intelligence because it feels too informal or unreliable. Most prefer to spend $50,000 on an empty CI Software Platform and not use it.

This creates a massive opportunity for those willing to listen to real user conversations.

Your competitors are spending thousands on user research surveys while their customers are literally telling the internet exactly what’s wrong with their products. The intelligence is free, real-time, and incredibly detailed—you just need to know where to look.

While your competition analyses sanitised feedback forms, you’re reading raw customer emotions and immediate reactions. This information asymmetry translates directly into competitive advantage.

Start monitoring one competitor across three platforms. Spend 15 minutes daily reading what their users actually think. Within a month, you’ll understand their market position better than their own product team.

Your competitors’ customers are already telling you how to beat them. Time to start listening.

Let’s talk…

https://www.octopusintelligence.com/real-time-intelligence-from-reddit-discord-and-hacker-news/

How to Analyse a Competitor’s Content to Predict Their Product Strategy: Weekly Winning Strategies

You can predict your competitor’s next product move by tracking shifts in their content—especially SEO keywords, blog clusters, YouTube uploads, and webinars. Most companies leak their roadmap six months early, and they do it through content.

Competitor content isn’t “just marketing” – it’s a product strategy time capsule.

Marketers don’t publish in a vacuum. Everything from blog titles to guest webinars is tied to pipeline goals. And pipeline goals are tied to product bets. If you’re only tracking competitor pricing pages and feature updates, you’re late. The good stuff—early signals—shows up in content. Think about what they’re talking about, how often, where, and with whom. If you’re analysing content like a writer, you’re missing it. You need to read it like an analyst.

Humint is still the easiest, best and hardest approach.

What is the most effective way to analyse a competitor’s content to predict their product strategy? Talk to your competitors. Not in some secret agent way—but through smart, structured primary research. Human intelligence (Humint) remains the sharpest weapon in your competitive intelligence toolkit. Conversations with former employees, current partners, shared vendors, and even customer success reps who’ve switched jobs give you unfiltered insights that no tool or content crawler can match. You’ll hear product roadmaps disguised as offhand comments, sales pitches that hint at pre-launch features, and hiring moves that confirm what content only suggests.

That said, secondary signals still matter. Not everyone’s wired for outreach, and most intel stacks need both. And you know a competitor may not tell you what you want to know. They are funny like that. But we can do it for you, of course.

Blog posts, YouTube uploads, keyword shifts, and partner webinars leak early signals in plain sight. They need to be read through the right lens. Use content analysis to build your hypothesis, then validate it with humint. Think of secondary research as your radar, and humint as boots on the ground. You don’t need to choose between them. The edge comes when you combine both.

Example: How a vertical AI startup predicted a rival’s product pivot six months early

Take a Series A AI startup building workflow automation tools for the healthcare space. Let’s call them MediPrompt AI. Their closest rival, a well-funded US-based player called ChartPilot, was ahead in sales and brand recognition. But MediPrompt wanted to be first to dominate a niche—AI-powered compliance for outpatient clinics.

They didn’t just track product updates. They analysed ChartPilot’s blog cadence, SEO keyword themes, webinar co-hosts, and YouTube scripts.

Here’s what tipped them off:

• Blog clusters shifted from general workflow tips to in-depth guides on HIPAA workflows, PHI audit trails, and clinic onboarding.

• New keyword themes included “automated compliance reports,” “HIPAA risk scoring,” and “OCR integration” (a dead giveaway).

• Partner webinars emerged with niche vendors in the compliance tech space—companies ChartPilot hadn’t previously engaged with.

• YouTube uploads focused on integrations with healthcare risk management tools.

They mapped these signals. Within two weeks, they had a clear picture: ChartPilot was prepping a compliance product suite.

MediPrompt moved fast. They doubled down on their own compliance messaging, spun up a lightweight MVP focused on audit readiness, and launched a beta to 50 clinics. They didn’t win the entire market, but they carved out a defensible niche—and beat ChartPilot to market by four months.

How to reverse-engineer product intent from content

Let’s break down how to do this—repeatable, zero-fluff, real-world steps.

1. Start with topic cluster analysis

Use tools like Ahrefs, SEMrush, or SparkToro. Pull a six-month view of the competitor’s blog and filter by volume, publish date, and internal linking.

You’re looking for topic clusters—5 to 10 blog posts orbiting the same core idea. Example: If a SaaS company suddenly writes five posts about “automated billing workflows,” they’re likely preparing an integration or launching a billing product.

Watch for:

• Frequency increases on a topic

• Internal links from older content to new niche posts

• Titles that match product feature naming conventions

If they’re pushing a new theme every week, that’s no accident. Product marketing is warming up the ICP.

2. Track shifts in SEO keyword targeting

Plug their site into a keyword tracking tool. Then compare month-over-month shifts.

What you want to find:

• New keyword groups that weren’t targeted before

• Keywords aligned with problem-aware or solution-aware search intent

• Rankings for pages not supported by existing products

If a startup that sells B2B contract tools starts targeting “vendor risk management” and “third-party compliance,” they’re looking beyond contracts. That’s your cue.

3. Watch who they’re partnering with in content

Look at guest webinars, podcast appearances, and co-written articles. Ask:

• Who are they co-hosting with?

• Are those companies already established partners—or are they new categories?

• Are the hosts from marketing… or product?

The product team rarely attends webinars unless there is something significant happening. Their presence is a pre-launch tell.

Also: if they’re co-writing with industry vendors in a space they don’t yet serve, that’s not brand building—it’s product positioning.

4. Analyse YouTube content for pre-launch tutorials

YouTube uploads—especially demo-style walkthroughs—can’t lie. Sales-led organisations often soft-test new messaging through lightly scripted video series before committing to full-feature pages.

Check for:

• Product names or acronyms mentioned casually

• Use cases not covered in the current feature set

• Integrations with new categories of software

Even better: run transcripts through ChatGPT or Claude and summarise recurring phrases. If a term appears four or more times in 3 videos, it’s not filler. It’s a signal.

5. Measure velocity and density

It’s not just what they’re publishing—it’s how fast and how deep. Build a simple tracker:

When velocity and depth go up together, they’re laying the runway.

What this means for content, marketing, and product teams

Content teams should be your first-line intelligence unit. Give them CI training. Teach them to tag competitor mentions, flag new keyword themes, and extract backlinks from newly discovered industry sites.

Marketing analysts need to stop reporting on just engagement. Track competitor content as product telemetry. Set alerts for when they shift verticals or experience a spike in frequency.

Product teams should map these content patterns to GTM windows. If a competitor is ramping content, they’re probably 60–90 days out from launch. Use that window to either fast-follow or reposition.

Content reveals the strategy; no roadmap ever will

Most people still think of competitive analysis as a reaction game. It’s not. It’s a timing game.

And content is the most underrated signal in the stack. Why? Because it’s public. It’s real-time. And it’s tied directly to revenue goals.

If you’re waiting for the product page to update or the press release to be released, you’re already late.

Start reading content like a strategist, not a subscriber.

TL;DR:

• Competitor content reveals product strategy six months early

• Analyse blog clusters, keyword shifts, partner webinars, and YouTube uploads

• Track frequency, length, and themes to anticipate launches

• Use this intel to position early, fast-follow, or defend niche markets

• Content is the early warning system most companies ignore

Want a simple way to track competitor content signals? Here you go:

Tracking Template

Competitor Content Signal Tracker

Purpose: Predict your competitor’s next product launch within 60–90 days

Used by: GTM leads, content strategists, product marketers, and analysts

Step 1: Build your competitor list

Start narrow. Pick 3–5 direct or emerging competitors.

Include funded startups with fresh GTM energy, not just the big names.

Example:

Step 2: Weekly Content Capture

Track these five areas. Use manual checks or automate with RSS + Notion or Airtable.

Do this weekly. You want to catch inflexion points, not just volume.

Step 3: Monthly Signal Review

Sort your data by topic clusters. Look for shifts in frequency or keyword density.

If a topic appears across three or more content types within a 30-day window, flag it.

Step 4: Humint Layer (Optional but powerful)

For every flagged topic, pull in what you hear from:

• Shared vendors or consultants

• Former employees (watch LinkedIn job changes)

• Sales reps chatting at events or online

• Reddit/Slack communities (search old usernames)

• Job listings for PM or GTM roles

Add to your tracker:

This layer turns your content guess into a go-to-market prediction.

Predict the Launch Window

Use a simple rule of thumb:

From the first content spike to launch, 60–90 days.

If content + humint stack up, assume you’re 1–2 quarters out.

Use this to:

• Launch fast-follow features

• Preempt their messaging with your positioning

• Brief sales + CS to be ready with counter-narratives

• Own the topic before they fully enter.

Automation Stack

Want to scale this without wasting hours?

Use:

• Feedly Pro for blog + press release monitoring

• Fathom / Descript for YouTube auto-transcripts

• Ahrefs / SEMrush for keyword tracking

• Notion or Airtable to house the tracker

• Google Alerts for brand + keyword pings

• SparkToro for audience interest tracking

Let’s talk…

https://www.octopusintelligence.com/how-to-analyse-a-competitors-content-to-predict-their-product-strategy/

Think Backwards to Beat Your Competitors: The Strategy Move No One’s Using

Most strategy advice reads like a corporate memo to your subconscious: polite, predictable, and completely forgettable.

However, let’s be blunt—most strategic planning efforts are flawed. Not because leaders are dumb. Not because teams don’t care. It’s broken because everyone is addicted to forward-thinking. We’ve been trained to “set objectives,” “map a plan,” “track KPIs,” and “adjust based on outcomes.” That sounds logical—but it’s backwards. Literally.

Let’s show you why thinking backwards is how real competitor analysis and strategy actually works when things get serious. Especially when the market is moving fast, your competitors are executing quietly, and your assumptions are ageing like Man Utd’s back line.

The Alphabet Backwards Test

Try reciting the alphabet backwards. Or the 8 times table in reverse. It’s not just hard—it feels weird.

That’s because your brain has been trained on forward patterns since you were five. A to Z. 1 to 10. Start to finish. Unfortunately, most bring the same linear thinking into how they view markets, trends, and threats.

But markets aren’t linear. Competitors don’t play by your plan. And your strategy doesn’t exist in a vacuum. It exists within a complex web of incentives, blind spots, internal blockers, and shifting power dynamics.

That’s why you need to start at the end and think backwards. Not because it sounds clever, but because it works.

How Reverse Analysis Wakes You Up

Let’s say your goal is to win 30% of the market share in a new software category. That’s the finish line.

Now stop planning forwards.

Start backwards. Imagine you already own 30%. What had to happen for that to be real?

• What did your competitors do wrong that let you in?

• What bets did you make that paid off?

• What partnerships or distribution moves made the difference?

• What product features actually mattered to the buyer?

• What assumptions turned out to be false—yours or theirs?

Most importantly: what did your team need to believe that nobody else did?

This isn’t a new-age visualisation exercise. It’s raw strategic modelling. And it’s a more honest way to look at risk.

Because now you’re not asking “How do we get there?”—you’re asking “What would have to be true for this to happen?”

This kind of backwards logic exposes flaws in your plans faster than a spreadsheet ever could.

Competitive Hypothesis Thinking: Build From the End

You can apply this same reverse logic to competitive analysis.

Let’s say you’re watching a new startup that’s growing quietly. They don’t show up in headlines, they’re barely mentioned on LinkedIn—but you hear from two customers that they’re switching to them.

Now fast-forward. Imagine it’s 18 months from now. That startup just raised $25M, poached your head of sales, and took five of your largest accounts.

That’s the end.

Now walk backwards:

• What made them attractive to your clients?

• How did they find a wedge into your accounts?

• Which of your weaknesses did they exploit?

• What market signals did you miss?

• What early signs would’ve revealed this threat?

This isn’t paranoia—it’s preparedness. Most competitor research is just feature tracking and press release bingo. However, good analysis models plausible futures and works backwards to test what could make them a reality.

That’s what Amazon did with Kindle. They didn’t start with “Let’s build an e-reader.” They began with “The endgame is Amazon owning digital book distribution.” Then they reverse-engineered what that would require: a device, publisher deals, format control, and a massive head start. The strategy wasn’t built—it was revealed by working backwards.

Use It in Micro-Scenarios Too

This doesn’t only work at the strategic level. Try it in your next meeting.

Imagine the meeting is over. It was a success. You nailed the outcome.

Now reverse-engineer it.

• What questions did the stakeholders ask?

• What objections came up—and how did you handle them?

• What context did they need to get bought in?

• What landmines could’ve derailed it?

• What did you not say that helped you win trust?

This approach clears out your internal noise. It sharpens prep. It changes how you read the room.

And it works the same way when pitching to a board, launching a product, or entering a new market.

A Real-World Example: The Rise of Spellbook

Let’s talk about a company that did think backwards: Spellbook—the legal AI startup.

Launched less than two years ago, they didn’t just build another GPT wrapper for lawyers. They looked ahead at a future where lawyers would stop using Word altogether. They imagined that outcome and worked backwards.

To make that future real, they needed:

1. Deep integration with legal workflows.

2. Trust from lawyers who are historically slow to adopt tech.

3. A pricing model that worked for mid-market firms.

4. A reason for legal teams to bring them in-house.

Then they asked: “What would have to be true to make each of those steps possible?”

From that perspective, they developed specific features that felt native to the way law firms operate. Focused on user experience and integrations over press-hype or technical novelty.

They didn’t just “move fast and break things.” They visualised the future they wanted, then played backwards chess. And it worked. Over 2,000 legal teams signed up within 18 months.

You don’t need a billion-dollar vision. You just need to build a strategy from the back, not the front.

Strategy Without Backwards Thinking is Just Hope

When you build a strategy by going forward, you’re building on hope.

• You hope the market will respond.

• You hope your competitors will remain in place.

• And you hope the next move will work.

But when you build backwards from the future you want—or the threat you fear—you’re building on logic.

You’re pressure-testing assumptions. You’re preparing for resistance. And you’re reducing the gap between your strategy deck and the real world.

And in today’s market, that’s everything.

Because while most founders are busy reacting to headlines, the best operators are simulating the future.

In detail. In reverse.

Want Help Doing This?

This kind of thinking isn’t natural. It takes repetition, friction, and honest feedback.

At Octopus, we’ve a team of skilled analysts who excel at delivering this service to our clients. If you’re tired of building forward-facing strategies that crumble on contact, get in touch. We’ll help you work backwards to get ahead.

Let’s talk…

https://www.octopusintelligence.com/think-backwards-to-beat-your-competitors-the-strategy-move-no-ones-using/