Although the answer to that question would be a strong NO across communities & subcultures who employ AI in their daily life, I tend to differ slightly here as a core systems thinker.

Take for instance, the subject of Collaborative Resonance. Stemming from the understanding of an AI model that shares the same name, it allows multiple such AI models to seamless collaborate, share, debate, interact & reach a consensus as for any given topic.

Now, thinking about the terminology / nomenclature wholly from a PM’s lens there’s so much hardship a PM goes through towards getting collaboration right amongst teams over their regular day’s workflow. And the progress teams / stakeholders make would be a correlative to how that rationale / the reasoning resonates.

Product management has always been subject to a lot of criticism from all other teams within the org. in as much as leadership as well. And that could be owed to many a misconception that people carry about the craft. Pushbacks are pretty common & there’s no PM who could put up their hand and quote that they have never faced it over their whole career.

One of the biggest myths in product management is that people resist change because they dislike additional work. In reality, most teams are remarkably willing to go the extra mile, provided they understand why the effort matters. Resistance seldom stems from laziness; it stems from a lack of connection. When an initiative feels detached from an individual’s goals, team success, customer value, the organization’s broader mission, it quickly begins to resemble just another task on an already overflowing to-do list.

As Product Managers, our role extends far beyond defining roadmaps & prioritizing features. We are responsible for creating alignment around purpose. Every process we introduce, every experiment we run & every strategic shift we champion must answer a simple but powerful question for every stakeholder: “Why should I care?”'

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If people can see themselves in the outcome, they’ll contribute with conviction. If they can’t, they’ll still show up, but only out of obligation. Compliance may deliver activity but only correlation would inspire ownership. People rarely resist work. They resist work that they don’t see themselves in & don’t see the value in. If they can’t connect the effort to a meaningful outcome for themselves, the customer, or the organization they may comply at best & disengage at worst. And it’d again come down to the team members being bombarded by a lengthy list of requests that don’t really correlate to (because they NEVER did in the first place) throwing the onus back of the PM for every minute step / twist & turn of the execution.

Let’s see how this plays out over a practical scenario, shall we?

Scenario: Introducing Customer Interviews

Imagine you’ve recently joined a SaaS company as a Product Manager. After analysing churn, you realize the team has been building features based almost entirely on leadership opinions. You propose that every squad conduct five customer interviews before every major feature. And the reaction is immediate & you face pushbacks from every nook & corner.

At first glance, it looks like everyone is resisting customer-centricity. They’re not. They’re resisting what they perceive to be additional work with an uncertain payoff.

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Each stakeholder would be silently asking a different question stemming from a deeper state of confusion…

• Engineering:

  • “How does this help me ship better software?”

• Design:

  • “Does this invalidate the research I’ve already done?”

• Sales:

  • “How will this hurt my customer relationships?”

• Leadership:

  • “What business metric would improve if we do this?”

Your proposal just doesn’t take off because everyone heard increased effort, while no one heard greater value / more bang to the buck.

Instead this is how a seasoned PM would navigate it.

So, instead of merely saying:

- “We need everyone to conduct more customer interviews.”

& stopping there, they tend to reframe it as suited to each stakeholder / team member.

Now the conversation is about reducing rework here which Engineering would gleefully accept 9.9 out of 10 times.

Now it’s about better design quality & better utility of their time to avoid any sort of design debt here, which no designer / design manager would ever think away from, not even the freshmen.

Now the phrases conversion, retention and customer relationships happen to be bread & butter for the Sales teams. It would certainly spike their interest enforcing them to have an engaging dialogue or two – the precursor for good collaboration.

Although it happens to be the very same thing the PM is saying, all of a sudden, the leadership is enforced to think about it in terms of ROI because of the manner it was propositioned in. The narrative here is directly to do with the goal & talks of eliminating some methods so that you get there faster – which is what good leaders almost always care about.

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The Most Important PM Lesson:

The most effective PMs don’t convince people to work harder. They help people see why the work matters to them. When stakeholders can connect an initiative to their own goals, resistance fades & ownership emerges.

People don’t resist effort. They resist effort without meaning.

Your job as a Product Manager isn’t merely to align roadmaps—it’s to align incentives & narratives to outcomes. That’s where real influence begins.

The magic that customers experience at the front end is often supported by a backend that can be surprisingly chaotic. Kitchens can be messy, storage areas cluttered, processes inconsistent & operational discipline far from perfect. The customer, however, rarely sees any of it. They only experience the final outcome - the meal that arrives neatly plated at their table.

What’s fascinating is that some businesses are confident enough to pull back the curtain entirely. They invite customers behind the scenes to observe how the operation really works right from ingredient sourcing & inventory management to food preparation, quality checks, & ultimately, service delivery.

One notable example is the McDonald’s Kitchen Tour, where visitors are taken through the entire operational journey of the restaurant. Rather than hiding their processes, they showcase them. The experience offers a rare glimpse into the machinery behind the customer experience, demonstrating how a seemingly simple meal is the result of hundreds of interconnected decisions, systems & processes working in harmony. As we’ll see, there’s an important lesson here that extends far beyond restaurants.

As part of its global “Open Doors“ initiative launched in 2009, McDonald’s has been inviting customers behind the counter to see first-hand how their food is sourced, stored, prepared & served. Visitors could tour storage facilities, grilling stations, fry counters & even observe the company’s “Made For You“ process which is a system designed to begin food preparation only after an order is placed, eliminating the need for pre-cooking.

The message was remarkably simple: “We have nothing to hide.”

• Fresh ingredients

• Well-defined processes

• Consistent quality standards

• Minimal direct human handling

From order placement to food delivery, every step is intentionally laid out transparent.

But don’t you think this raises an interesting question…

→ The answer lies in one word: “TRUST”!!

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Opening the doors to customers is far more than a marketing exercise for McDonald’s. It is a tangible demonstration of confidence in the systems, processes & standards that power the business. Rather than asking customers to trust the brand’s claims, such an act allows them to literally verify those claims for themselves.

And that changes everything. Once customers witness the operation first-hand, uncertainty begins to disappear. They no longer rely solely on advertisements, packaging, or brand messaging to form an opinion. Instead, they draw confidence from their own observations. The result is a deeper, more durable form of trust - one built on transparency rather than persuasion.

This principle extends well beyond the restaurant industry. It’s the same reason many premium restaurants operate open kitchens, allowing diners to watch chefs prepare their meals in real time.

“When visibility garners confidence & transparency seamlessly reduces skepticism”

The broader lesson for product leaders is equally powerful.

One of the most effective ways to build trust is through the product itself - a concept often referred to as Product-Led Trust (PLT). Modern buyers place significantly more faith in first-hand experiences than in marketing narratives. When a product transparently demonstrates its value, quality, reliability & operational integrity, it naturally reduces friction in the buying journey. Trust, in that sense, becomes a product feature. And products that make trust visible often find that conversion becomes easier, adoption accelerates & sales cycles shorten, not because customers were convinced, but because they no longer have reasons to doubt.

Putting PLT into Practice

If trust is a product feature, then building it cannot be left to marketing alone. It needs to be intentionally designed into the user experience.

Here are five practical ways to embed Product-Led Trust (PLT) into your product strategy.

Step 1: Deliver Immediate TTV

Trust begins when users experience the value for themselves.

For years, product teams have focused on reducing Time-to-Value. Today, reducing it isn’t enough. In an increasingly crowded market, the goal should be immediate Time-to-Value. Users have more alternatives than ever before & far less patience to explore them. This makes onboarding one of the most critical experiences in your product.

Every workflow, onboarding funnel & first-use experience should be engineered to answer a single question as quickly as possible - Why should I continue using this product?

The faster users experience a meaningful outcome, the faster trust begins to form.

Step 2: Lead with Transparency

Nothing erodes trust faster than hidden conditions.

Complicated pricing structures, surprise paywalls, mandatory credit card requirements & convoluted cancellation policies create friction long before users experience value.

Instead, allow users to evaluate your product on its merits. Offer meaningful free trials, showcase high-value capabilities early & create opportunities for users to achieve quick wins within their first few minutes of engagement.

The objective isn’t simply to let users try the product, it’s to allow them to independently validate promises you’re making.

Trust grows when customers discover that the product performs exactly as advertised.

Step 3: Amplify Customer Proof

Regardless of how markets evolve, one signal continues to outperform almost every other trust-building mechanism: customer validation.

Prospective users are naturally skeptical of product claims. But they’re far less skeptical of people who have already solved similar problems using the product. This is where customer testimonials, case studies, reviews & the insights gained via feedback become invaluable. The most compelling examples aren’t generic success stories but highly contextual narratives that help prospects see themselves in similar situations.

Even better, surface these trust signals directly within the product journey. Display relevant reviews, customer outcomes, or success stories near critical decision points & CTAs where users are evaluating whether / not to move forward.

A well-placed customer story carries more persuasive power than pages of feature descriptions or performance metrics.

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Step 4: Rewarding & Advocating Loyalty

Loyalty is rarely a one-way relationship.

While organizations often expect loyalty from customers, the strongest brands demonstrate loyalty first by consistently delivering on their promises & rewarding continued engagement.

Recognition programs, referral incentives, milestone rewards, usage streaks, community status levels & exclusive benefits can all reinforce positive behavior while strengthening customer affinity. The impact becomes even greater when these rewards are made publicly visible. Profile badges, achievement levels, community rankings or status indicators create a transparent signal that engagement & contribution are valued.

Beyond rewarding existing users, they also create aspirational pathways for prospective users by clearly demonstrating that meaningful participation is recognized & celebrated.

Step 5: Proactively Invest in Customer Success

Product-led growth does not eliminate the need for customer support. If anything, it changes its role. The most successful PLG organizations understand that support is not merely a cost center, it is a trust-building mechanism.

Modern AI systems & agentic workflows can automate a significant portion of customer interactions, enabling lean support teams to operate at scale. However, automation should enhance the customer experience, not replace human accountability altogether.

Most users still live by the understanding that any help major / minor is just around whenever they need it.

Whether through AI-powered assistance, self-service resources, community forums, or a dedicated customer success team, the goal remains the same: reduce uncertainty & increase confidence.

Because ultimately, trust isn’t built through a single interaction. It’s reinforced through every touchpoint a customer has with your product long after the initial onboarding experience.

Case Study: Applying Product-Led Trust in an SMB SaaS Business

Product-Led Trust is not a standalone initiative, a marketing campaign, or a growth hack. It is the cumulative outcome of consistently delivering value, operating transparently, amplifying customer voices, rewarding loyalty & supporting users throughout their journey. When done well, trust stops being something you ask customers for, it becomes something your product earns.

Consider a SaaS company serving Small Medium Businesses (SMBs).

While SMB buyers share certain characteristics with traditional B2B customers, their buying behavior often resembles that of consumers more than large enterprises. They operate with lean teams, tighter budgets & limited time. Lengthy evaluation cycles, extensive onboarding efforts & delayed value realization can quickly turn even a promising solution into a perceived risk.

As a result, TRUST becomes a decisive factor in the adoption journey.

Most SMB customers aren’t merely asking, “Does this product work?”.

They are asking, “Can this product solve my problem today without creating additional workload or overheads for me?”

This is where PLT can become a meaningful competitive advantage. Let’s look at how an SMB-focused SaaS product can operationalize PLT across the customer journey with the very 5 steps mentioned above…

Step 1: Deliver Immediate TTV

For SMB customers, the first few minutes often determine whether they continue evaluating the product or abandon it altogether.

1.1 The “First Five Minutes” Principle

The onboarding experience should guide users toward a meaningful outcome as quickly as possible. Rather than asking customers to navigate lengthy setup processes, focus on helping them achieve an immediate win.

Examples include:

• Generating their first report

• Creating their first invoice

• Sending their first campaign

• Automating their first workflow

The faster users experience value, the faster trust begins to form.

1.2 Eliminate Blank-Slate Anxiety

One of the most common reasons for early drop-off is uncertainty around where to begin.

Pre-built templates, sample projects, default configurations & intelligent data pre-population can dramatically reduce this friction. Instead of presenting users with an empty workspace, present them with a working solution that can be customized as needed.

1.3 Guide Users Contextually

Modern users expect guidance within the product itself.

Interactive walkthroughs, contextual tooltips, onboarding checklists & embedded video tutorials help users discover value without forcing them to leave the application or navigate extensive documentation.

The best onboarding experiences don’t teach users how the product works. They help users accomplish what they came to do.

Step 2: Lead with Transparency

Trust thrives when uncertainty is minimized.

2.1 Provide Data Portability

Customers should feel confident that their data belongs to them.

Simple import & export capabilities signal that the business is prioritizing customer success over customer lock-in. Ironically, the easier it is for customers to leave, the more likely they are to stay.

2.2 Make Pricing Predictable

Few things erode trust faster than unclear pricing.

Clearly communicate what each plan includes, what limitations exist & what customers can expect as they scale. Transparent pricing reduces decision friction & prevents unpleasant surprises later in the relationship.

2.3 Remove Commitment Anxiety

Requiring credit card information before users experience value can create unnecessary resistance.

Allowing prospects to explore the product without an upfront financial commitment communicates confidence in the offering. It screams out a simple yet powerful message loudly: “Experience the value first. Pay only when you are convinced.”

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Step 3: Amplify Customer Proof

People trust people. For SMB buyers, customer validation often carries more weight than feature lists, benchmark reports or marketing claims.

3.1 Surface Social Proof Early

Reviews, ratings, customer quotes & success metrics should be woven throughout the product experience, not hidden away on a separate testimonials page.

The closer social proof is placed to a conversion decision, the more influential it becomes.

3.2 Showcase Contextual Success Stories

Generic testimonials are useful but specific testimonials are powerful.

A statement like, “Company XYZ reduced invoice processing time by 60% using this workflow.” helps prospects visualize similar outcomes within their own businesses.

Best case studies don’t simply celebrate customer success, they help future customers imagine their own.

Step 4: Rewarding & Advocating Loyalty

Trust deepens when customers feel recognized.

4.1 Create Visible Recognition Systems

Loyalty programs, referral incentives, usage milestones & customer achievements can all strengthen engagement while reinforcing positive product behavior.

Visible indicators such as profile badges, achievement levels, customer tiers or referral rankings make recognition tangible.

4.2 Turn Success into Social Currency

When customers are publicly acknowledged for their contributions, referrals, expertise or engagement, they become advocates rather than merely users.

The effect extends beyond the individual being recognized. It signals to the broader community that meaningful participation is valued & rewarded.

Done well, loyalty programs become trust accelerators.

Step 5: Invest in Proactive Customer Success

Even the most intuitive products encounter edge cases, blockers & moments of user confusion. The difference between retention & churn often comes down to how quickly those moments are resolved.

5.1 Identify Friction Before Customers Leave

Modern analytics & AI-powered support systems can detect stalled onboarding flows, incomplete setup journeys, declining usage patterns & unresolved issues long before customers decide to churn.

The opportunity lies in intervening early.

5.2 Combine Automation with Human Expertise

AI agents can handle a significant portion of support interactions, but there are moments where human intervention remains invaluable.

Whether it’s resolving a complex issue, clarifying a workflow or helping a customer achieve a desired outcome, responsive customer success teams reinforce confidence in the product & the company behind it.

“Customers don’t expect perfection. They expect partnership.”

And knowing that someone is available when things go wrong often becomes a trust signal in itself.

Conclusion:

Product-Led Trust is not merely a growth strategy—it’s a risk-reduction strategy. When customers experience value quickly, understand exactly what they’re signing up for, see proof from similar businesses, receive recognition for engagement & know support is readily available, trust becomes a natural outcome. When trust becomes a natural outcome, adoption, retention, expansion & advocacy tend to follow.

Just remember these steps:

The BACKDROP:

The year was 2006 & this was way before my career in IT / software could start. I had the habit of critiquing advertisements & I don’t have the foggiest idea as to when something of a fleeting pass-time hobby back then turned into a full-blown passion over a period of time…

I was on a holiday in the mountains of southern India with a few of my friends & we were at a diner waiting for our order. I saw a Coca Cola print advert hanging on the wall & expressed my deep reservations rather strongly quashing the element of celebrity endorsements for products where it gets driven to a point where one doesn’t even know whether they are buying the product for its actual worth / value addition or because they see their favorite celebrity looking all glam & hep (at times bordering sleazy – remember the Slice advert featuring Katrina Kaif).

And as I said that, one of the friends thrusted a bottle of coke right up to me on my table & challenged me with, “Ok, let’s see how you advertise this product now without involving any celebrity”.

Although the competitive side of me took that up as an immediate challenge & came up with a short copywrite bordering on the lines of “this is your reason to relish scorching tropical / sub-tropical weathers” (a bit of localization in there as well), I have grown beyond that point to perceive & believe that there indeed could be more than one perspective to product endorsements after-all. At the end of the day it is the metrics like Revenues that hold a mirror to any idea discussed in the boardrooms which is why ROI, CBA, the RISK:REWARD ratio would drag everything down to reality forcing one to objectively analyze what would work & where the money ought to go.

Marketing, persuasion, branding, politics, leadership, sales, social media, product adoption - beneath all of them sits one central question:

• Why do they BUY?

followed by a few others like:

• What do people think?

• How do people change their minds?

• How do they make decisions?

For decades, businesses assumed persuasion was mostly about presenting better arguments. If your product was superior, people would naturally choose it. But reality has proven that it rarely works that way.

• Consumers buy expensive shoes because a celebrity wears them

• People tend to trust charismatic founders with weak products

• A beautifully packaged product often outsells a technically superior alternative

• A confident speaker can persuade audiences even with shallow arguments

This is exactly the side of human behavior the Elaboration Likelihood Model (ELM) underlines & tries to explain.

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Developed in the 1980s by psychologists Richard E. Petty and John Cacioppo, ELM became one of the most influential theories in persuasion psychology. It explains how people process persuasive messages and why some messages create lasting attitude change while others create only temporary influence.

At its core, ELM proposes something deceptively simple & yet hard to believe:

Understanding this distinction is one of the most powerful advantages a marketer, product leader, cofounder, communicator or negotiator can possess.

Here’s a break down of the model in depth, how it works in the real world inclusive of a case study that makes the framework easy to apply.

What is ELM?

The Elaboration Likelihood Model (ELM) tries to explain how persuasion happens through 2 different routes namely the Central Route & the Peripheral Route.

The word elaboration here could simply refer to the amount of thinking a person does about a message shared over any marketing asset. The model argues that persuasion depends heavily on how much of a mental effort is needed & how much the audience is willing to invest. If people are highly motivated / deeply interested, they process information carefully. Otherwise they could be distracted, uninterested, overloaded, emotional, act indifferent to or rely on shortcuts instead.

1. Central Route of Persuasion

The central route occurs when people think carefully & critically about information before forming an opinion. The evaluation tends to take the course of:

• Facts

• Evidence

• Logic

• Trade-offs

• Data

• Credibility of arguments

• Long-term implications

Some of the questions that are most likely to arise are:

• Is this actually true?

• Does the product solve my problem?

• What are the pros & cons?

• Is the evidence convincing?

• What risks exist?

Because the audience has more skin in the game & is highly involved here, deeply processing information, persuasion through this route usually results in:

• Much stronger beliefs

• An attitude change that’s long-lasting

• Higher resistance to counterarguments

• More stable decision-making

In simple terms, if people think deeply & tend to agree with you, the persuasion tends to stick on for a really long term.

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2. Peripheral Route of Persuasion

The peripheral route occurs when people do not invest much cognitive effort into evaluating a message. Instead of deeply analyzing arguments, they rely on quick cues or mental shortcuts, some of which may be:

• Charm / Appeal

• Wittiness

• Popularity

• Celebrity endorsements

• Packaging

• Social proof

• Emotional appeal

• Repetition

The audience is not carefully analyzing logic / rationale building up into the advertisement, let alone analyzing the product itself. They are merely reacting to signals around the message used in the advert, the tone & its perkiness or some other element that they visually / mentally perceive as soothing.

Let’s now dive into a case study with a pretty common example that’d resonate with most towards understanding these 2 routes of influence:

CASE STUDY: BUYING A HOUSE

1. CENTRAL ROUTE

When buying a house, what do most people consider important? What parameters to they come down hard on with their analysis? Although some of them could be totally subjective to geography, some parameters that most analyze broadly are:

• Location

• Price

• Finance

• Appreciation likelihood

• Build quality

• Amenities

• Accessibility

Most tend to spend weeks or even months in some cases researching because the decision carries high consequences. Merely coming up with catchy slogan may not be enough to persuade them.

2. PERIPHERAL ROUTE

Research studies has proven that most people do not get into stuff like Finance, build quality when they set out to purchasing a house. They rather visualize or pay heed to one or all of these parameters:

• Coziness

• Luxurious / Grandeur

• Illusion of Spaciousness

• Possession date

• Builder profile

• Social Proof (Celebrities living there)

• Lifestyle aspirations (sunsets, view from the balcony, clubhouse parties)

The Most Important Question Now…

So now that you’ve understood the brilliance of a model like the ELM & given the 2 routes which one would you now stick to as a product / marketing person?

You ought to have landed one important realization here. There’s no visible guarantee as to how a person would perceive a message shown to them over an advert. It is quite possible that the very same person can use either route depending on the parameters they consider / perceive as important. And to each their own obviously. A highly analytical engineer may deeply research laptops but buy shampoo or ice-cream impulsively. A careful investor may still choose restaurants based on aesthetics or locality when the spread on offer could drop pretty lower or even get ignored. Human beings constantly tend to shift between deep reasoning & mental shortcuts, which is why persuasion ought to depend not only on the message itself but also on:

• Motivation

• Attention

• Cognitive ability

• Emotional state

• Context &

• Relevance

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The whole point is you don’t really know how & what people use to arrive at the decisions. Which route do they use could be a question that goes unanswered. But at the end of it all, what ought to matter is whether you as a product team are tapping into all those channels.

The more personally important something feels, the more central-route processing happens. But OTOH, if a message seems too technical, confusing, fast or overwhelming they may default to peripheral cues.

When attitudes formed through the central route are much harder to change as people feel they arrived at the conclusion themselves through reasoning the peripheral-route persuasion often fades quickly because a celebrity endorsement may only manage to create a temporary excitement.

A common misunderstanding is assuming peripheral persuasion is “bad” or “weak.” NO. It is not. Modern digital ecosystems are practically built around peripheral cues & one is always under pressure to generate great engaging content as most online decisions tend to happen rapidly. In attention-scarce environments, peripheral persuasion often dominates the central route.

ELM in the AI Age

Given the AI era one is witnessing an exodus of products mushrooming all throughout the world. Situations as of today dramatically amplify peripheral persuasion as users face an information overload. As a result, platforms tend to reward instant emotional hooks, visual appeal, viral cues, short-form engagement & social validation.

But you know what the interesting part is? High-ticket or high-risk decisions still trigger central-route processing. People may discover products through peripheral cues but mostly convert through spells of central reasoning.

For ex.

A founder may first see a SaaS product through a LinkedIn post that catches their eye for some reason.

But then they would dive into multiple spells of evaluation over parameters like pricing, integrations, demos, case studies & ROI before they end up subscribing / taking a trial.

This is why it is imperative for product teams to combine & use both those routes strategically doing away with the “which one is better” or “which one do we choose” debate. In business, product management, leadership, branding, marketing & even over everyday conversations, ELM offers a powerful lens into how humans truly make decisions, leaving us with what is perhaps the most important lesson:

⚠️DISCLAIMER: This perspective is intentionally scoped to founders & leadership teams operating across early-stage startups. It is not meant to be generalized beyond that context. Building in a startup environment requires a conscious departure from corporate muscle memory. 

What worked in structured, scaled organizations often needs to be unlearned, re-evaluated & adapted to a setting defined by speed, ambiguity & constant iteration. Processes that deliver outsized value in one context don’t automatically translate to success over another, especially when constraints, stakes & pace of decision-making could be fundamentally different.

There’s little debate that teams adopting Agile ways of working have, in many cases, unlocked higher levels of execution efficiency & accountability. What’s more notable is how Agile has evolved beyond its origins rooted in software development. Design, marketing & other XfN teams have increasingly adopted its principles, structuring workflows, improving visibility & creating tighter feedback loops bringing coherence to otherwise fragmented processes. The resultant is stronger collaboration & a more predictable cadence of delivery.

At its core, the value proposition is straightforward: rapid iteration, evidence-based decision-making, the ability to adapt in real-time. When applied well, these principles enable teams to stay aligned with market signals & continuously refine what they deliver, grounded not in assumptions but in measurable outcomes.

But the real tension emerges when a methodology that delivers an outsized value in one part of the organization is applied indiscriminately elsewhere. And what works exceptionally well for execution teams doesn’t necessarily translate to founder workflows… which raises a fair question:

• Should early-stage founders be leaning into Agile with the same level of rigor that other teams at large corporates do?

In practice, I’ve seen the opposite effect. When cofounders attempt to institutionalize strict Agile practices too early, it can introduce friction where speed & fluidity are far more critical.

Agile - at its core, is designed to bring structure, consistency & predictability particularly in environments like engineering where the standardization enables new team members to onboard quickly & contribute effectively from day one. That level of rigor is valuable when scaling execution.

However, the founder’s mandate in the early stages is fundamentally different. It is less about optimizing delivery & more about discovering what to build, iterating on the business model, navigating uncertainty at pace. Over-indexing on process at this stage could divert attention from exploration to orchestration.

Consider a 10-person startup where a cofounder is heavily invested in setting up Agile ceremonies, frameworks & governance. The opportunity cost could really sting. The time that could have gone into customer discovery, rapid experimentation or strategic pivots gets absorbed by process overhead. In a phase where learning velocity is the only true advantage, that trade-off can prove to be pretty expensive.

I’ve seen multiple instances where an early affinity for process (particularly Agile) in its rigid form has inadvertently slowed down founder-led momentum. And that’s dangerous indeed.

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A few of those patterns I feel are totally worth calling out here…

1. Process Over Speed

Anyone who has operated in an early-stage startup understands the inherent restlessness of that environment. The priority is constant discovery, testing ideas, identifying the right path forward & validating assumptions in real time. When the pressure is to find PMF quickly, introducing structured process frameworks too early could become a distraction rather than an enabler.

Resource constraints further sharpen this reality. Founders don’t have the luxury of spreading focus thin. They need to concentrate effort on the few initiatives that can unlock disproportionate impact. That often means narrowing in on a single compelling feature, refining positioning, experimenting with distribution & shaping a GTM motion driving those early revenue signals. Every hour & dollar needs to compound toward learning what truly resonates with the market.

Over-indexing on Agile at this stage can inadvertently shift attention from outcomes to mechanics. Teams may start optimizing for internal metrics like velocity or sprint completion, mistaking activity for progress. The risk is building a feature factory where one is shipping consistently alright but without a clear line of sight to customer value or market relevance. In such scenarios speed doesn’t create advantage but simply accelerates misalignment. For founders, the question isn’t how fast the team is moving, but whether they’re moving in the right direction. Until there is clarity on PMF, the emphasis should remain on discovery, sharp iteration & meaningful validation but never on perfecting processes. Execution efficiency matters, but only after you’re confident you’re building something worth executing.

2. Lack of True Requirements

Agile, by design, thrives in environments where there is a reasonable degree of clarity - clear problem statements, well-defined user stories, a prioritized backlog informed by meaningful research. It introduces dynamism, alignment & execution discipline, particularly for teams that are already operating with a shared understanding of goals & direction. But that assumption doesn’t always hold in the early stages of a startup.

When the overarching strategy is still taking shape, when long-term vision, mid-term priorities & even near-term goals seem to be in flux, process alone cannot compensate for a lack of clarity. Alignment frameworks are only as effective as the direction they are aligning toward. Without that, they risk becoming performative rather than productive.

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Early-stage founders often operate in a state of continuous ambiguity. Hypotheses evolve rapidly, decisions are revisited frequently & what feels like the right direction one day can be invalidated by new insights gained on the next. It’s not uncommon to see significant pivots within days, driven by emerging signals from users, markets, or stakeholders. In such environments the premium is on adaptability not orchestration.

In that context, leaning heavily into Agile rituals like sprint planning, role definitions, structured ceremonies could get misaligned with the need of the hour. The risk isn’t just overhead; it’s reduced responsiveness. Startups win by their ability to change direction quickly, to dismantle & rebuild without friction, to pursue new opportunities with minimal inertia. Process becomes a force multiplier when implemented at the right time / stage. But applying it prematurely can constrain the very flexibility that early-stage founders depend on. There’s a time to formalize & optimize. But until then, preserving speed, creativity, freedom to pivot should take precedence.

3. Resource & Structure Constraints

Agile tends to deliver the most value in environments that have reached a certain level of maturity, where teams are large enough, roles are clearly delineated & there’s sufficient context to support structured planning & execution. That naturally raises the question: should formal role definitions / process rigor be among the top priorities for an early-stage founder?

In smaller teams, some degree of structure can certainly help bring order to chaos. But the needs of a 5–10 person team are fundamentally different from those of a 200-person org. Early-stage startups often rely on individuals wearing multiple hats, with fluid responsibilities & rapid context switching. Imposing rigid roles / processes in such an environment can feel forced & in many cases, counterproductive.

That’s not to say Agile principles don’t have relevance. The truth is far from it. Selectively adopting elements like prioritizing individuals & interactions over processes & tools could prove to be pretty valuable. But attempting to operationalize a full-fledged Agile framework across the organization at this stage often introduces unnecessary complexity without commensurate benefit.

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There’s a tendency to equate process with progress, investing time in tools, documentation, workflow management systems in the hope of creating alignment. In reality, this can become administrative overhead that diverts attention from higher-leverage activities. Maintaining detailed boards, enforcing ceremonies, formalizing ownership structures are important, but typically at stage demanded by scale. In the early days, the scarcest resource isn’t process discipline. It ought to be strategic clarity. Founder attention is better spent on shaping direction, understanding the market & making high-quality bets. Process should support that journey but never strike a competition with it.

4. Premature Technical Debt

Agile frameworks introduce constructs like sprints, velocity for a reason. They create accountability, establish a delivery cadence, ensure teams are consistently moving toward defined outcomes. In larger (more mature) organizations, this discipline helps drive ownership at every level & keeps execution predictable. But those benefits rely on a key precondition: clarity & team maturity.

In early-stage startups, that context often doesn’t exist. The goal isn’t to optimize delivery throughput but to discover what’s worth delivering in the first place. Imposing pressure to maintain sprint velocity or adhere to rigid timelines can misalign incentives, pushing teams to prioritize / fixate on the cadence rather than meaningful impact.

Founders at this stage are not operating a feature factory. The objective isn’t to release on a weekly rhythm, but to learn quickly, iterate thoughtfully, refine the product based on real signals from the market. Introducing artificial urgency through timeboxed sprints can create unintended consequences, including rushed decisions & mounting technical debt, both of which are expensive to unwind when resources are already constrained.

In fact, optimizing too early for speed of delivery can be counterproductive if it compromises quality or clarity. Rework, refactoring & course correction consume time that early-stage teams can’t afford to lose. At this stage, time is best invested in getting the fundamentals right namely - problem definition, user understanding & solution fitment. Process should be in service of outcomes, not the other way around. For founders, the priority is building a product that meaningfully solves a problem for a clearly defined user segment. Any framework that detracts from that goal irrespective of its effectiveness in other contexts ought to be applied with a lot of caution.

In Summary… :

Early-stage founders ought to focus on MVPs, launch quickly, learn from real users, & iterate fast. Prioritize insight & adaptability over perfect execution or rigid process.

What matters most is open communication, rapid experimentation & sharp user-driven analysis.

A founder’s time at an early-stage start-up is best spent on immersive research, identifying high-potential segments & refining problem-solution fitment.

Structured Agile processes could have its place later, much later in fact…

⚠️FAIR WARNING: 

Although this post could be tuned to an early-stage start-up cofounder...
THE possibility of a wider application & fitment to -
a growth-stage start-up / a large MNC -
CANNOT be ignored.

During a recent conversation with a cofounder, I encountered a perspective that left me genuinely surprised, certainly not in a positive way. While I firmly believe that founders must place trust in their teams, the notion of stepping so far back that leadership becomes largely disengaged has never & still doesn’t sit well with me. To me, leadership isn’t about retreating into the background while hoping momentum sustains itself; it’s about remaining close enough to the ground to sense the pulse of progress & steer as & when required.

Trust, in any high-performing organization, is non-negotiable. Teams must be empowered to move forward, experiment & deliver meaningful outcomes. Yet trust should never translate into blind delegation. Even when a team’s collective experience is substantial, leadership still has a responsibility to stay anchored in the realities of execution, observing progress from end-to-end, connecting the dots, transforming insights into a compelling narrative that keeps the org. aligned & moving forward one step at a time towards progress.

To be clear, this has nothing to do with micromanagement. In fact, the two are fundamentally different. Great leaders tend to keep a steady line of sight into how things are unfolding, tracking progress with intent, distilling signals from the noise, using those insights to motivate teams, sharpen direction & encourage everyone to go the extra mile when it matters most.

“Micromanagement suffocates progress but thoughtful oversight fuels it”

You’ve likely heard the phrase: “Leadership is less about the title and more about the results”. I totally subscribe to that. Titles may define authority, but impact is what ultimately defines leadership. And in any serious conversation about impact, the underlying language makes all the difference. The most credible language leaders can speak is the language of metrics & data.

Yet, time & again, we see organizations that appear disciplined on the surface, where processes are getting documented religiously, reviews are held spic-and-span, dashboards are updated regularly with the frontline metrics dutifully getting reported. And despite all that rigor, performance stalls or begins to drift apart in the worst case.

Which raises a fundamental set of questions:

• Where does the real gap lie?

• Why do orgs still struggle when they claim to follow “world-class processes”?

IME, the answer often sits quietly within the very processes’ organizations take pride in. The issue is rarely the existence of process, it rather boils down to how it gets defined & more importantly - what it is anchored to. That is also where the PROCESS-METRICS GAP lies.

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When processes are designed, they ought to be tied to the right metrics. Too often, organizations default to internal indicators like, efficiency ratios, internal productivity measures or satisfaction scores. While these can be useful signals at the team level, they never tell the full story.

The real test of a process lies in how well it moves external outcomes. Metrics such as C-SAT, revenue growth, retention & market share hold up a far clearer mirror to the organization’s true performance. When processes are aligned with these external indicators, they stop being administrative rituals & start becoming genuine drivers of impact.

A seasoned leader rarely needs long to surface the truth. It begins with asking the right questions, demanding the right data, quickly distilling the insight that actually matters. Reports aren’t just numbers on a page, they are signals. The real skill lies in reading between the lines: understanding why certain metrics are highlighted, why others are quietly absent & what those choices reveal about the underlying reality.

This is where leadership distinguishes itself. It often starts with a single, well-placed question—followed by a few sharper ones as the situation demands. Clarity emerges not from volume, but from precision. Leaders are entrusted with authority for a reason: to exercise sound judgment, probe where necessary, ensure that the organization sees the truth of its performance clearly, honestly devoid any sort of distortion. 📊

For ex: Take the case of an org. like Mr. Rooter. 

They provide a variety of plumbing services in the USA. 

Internally, at the team-level they may track a host of metrics...
which may make total sense to them, like say:
        - TAT (Turn Around Time) for servicing
        - Frequency of availability
        - Monthly attendance of plumbers
        - No. of plumbers with access to modern tools

But notice how tracking them doesn’t directly concern any client...
although some metrics could carry a faint overlap!!

Irrespective of how much time the leadership spends on these...
there may be no real tangible change to the CX (customer experience).

Ergo, the GAP between the process & the metrics widens taking them -
miles away from tracking real impact that matters...

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The Causation:

What causes the gap? The reasons could be multiple although these are known to be common & repetitive across teams / orgs:

Leaders ought to be in touch with the teams over every step / milestone (at least the major ones if not the minor ones). Setting the narrative is just the beginning & never could be considered the end.

Bridging the GAP:

It is true that process & metrics are more like the wheels & the dashboard of a vehicle. One could just blindly drive the vehicle without much heed to the speedometer & the odometers. But professional racers do track their wheels ensure that they are well-maintained whilst also paying a lot of heed to the speeds at various parts of the track, especially at the chicanes when the vehicle gets to one of it & how quickly they accelerate thereof.

Akin to that very analogy, leaders ought to define the right process & also pay attention to the metrics periodically measuring, checking & ensuring they are on the right track so as to be able to proactively make the necessary changes on one’s feet without losing much time & wasting much effort. So, being conscious about it & identifying the gaps whilst proactively building action plans to bridging them becomes an ongoing part of the job & an inherent responsibility of any leader.

Adopting these 5 steps have worked like a charm for me.

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→ STEP 1 – Start with the Goal

Seasoned leaders bring sharp clarity to outcomes - this is table stakes. But clarity on what must be achieved is only the beginning. Equally critical is their command over how those outcomes are realized: translating long-term ambition into a structured sequence of priorities, breaking them down into actionable milestones & creating a clear path that teams can execute against with discipline & alignment.

2 important action items resulting out of this step would be:

• What is our goal here?

• What would it take for us to reach that goal?

→ STEP 2 – Map the Processes

What it takes to achieve the goal must serve as the blueprint for deeper operational rigor, deconstructing the objective into clearly defined workflow steps. Once articulated, these steps should be institutionalized into a cohesive process that aligns XfN teams with explicit ownership, accountability & interdependencies. The outcome is a well-defined process map documented, structured & anchored in measurable checkpoints that enable consistent execution & governance.

A few crucial questions that ought to be answered at this level are:

• Is the process definition strong & would it suffice in getting to the goal?

• What is the team’s accountability (both individually & collectively)?

→ STEP 3 – Spell Out Process-Centric Metrics

Leaders are ultimately accountable for outcomes & that is non-negotiable. However, true leadership extends beyond outcome ownership to a disciplined understanding of the metrics that govern the underlying processes. This requires a deliberate shift away from vanity indicators toward a focused set of high-signal metrics that genuinely reflect progress & impact. By clearly defining & prioritizing these measures, leaders create a unifying narrative, aligning stakeholders & teams around what truly matters, driving coherent, outcome-oriented execution.

Some questions that would help regain perspective over the metrics here would be:

• Are the metrics clearly mapped? Which metrics represent what processes?

• Which one of those metrics are primary & ought to earmarked?

→ STEP 4 – Pair Metrics with Context

Clarity on strategy & initiatives, while essential, is not sufficient. Leaders are not operating in the day-to-day trenches & executional excellence depends on how effectively intent is translated on the ground. This is where well-defined processes & the right metrics must be woven into a coherent narrative for teams. By anchoring teams in this context, leaders enable them to derive more granular, execution-level metrics ensuring effort is appropriately directed, cohesion is strengthened & collective energy is channeled toward outcomes that truly matter.

One question a leader ought to ask & track repeatedly is:

• What metrics are teams really tracking / prioritizing? Do they add up to the high-level metrics defined as a part of the process?

→ STEP 5 – Recalibrate

In a market defined by abundant choice & rapidly evolving preferences, customer needs can shift, often unpredictably. Standing still is not a viable option. Leaders must maintain a vigilant, data-informed lens, continuously extracting meaningful insights to detect early signals of change. Acting on these signals with speed & precision enables timely recalibration of strategy, refinement of initiatives & realignment of processes & metrics ensuring sustained relevance & competitive advantage.

• Meeting periodically with the stakeholders towards brainstorming the current strategic direction as aligned to the goals vis-à-vis the other market players does make perfect sense here

Conclusion:

This here is your cheat code if you happen to be a leader / cofounder of a Startup:

When the conditions that could render an org. or a team sub-par is deeply subjective & also listless, IME the one thing that’s strange enough & pretty common across Start-ups (at least some of them) is how it all boils down to the vision & its dissemination amongst the teams. Now, when is one the subject of vision I realize how the terms Org. Vision & Product Vision could be confusing & does manage to put many off as well. Let’s begin by getting that clout out of the way…

When the vision of the org. is the ultimatum there also ought to be no doubt that it supersedes all else including the product vision. In fact, there could be multiple layers forming the core of org. strategy before one can traverse to the product vision from the org. vision.

Take the very example of Google there. “To organize the world’s info & make it largely usable” spans a pretty wide digital net, in fact everything under the sun (/ the observable universe). But going from there to a product like Google Health (2008) took approximately 10 years from the date of inception of Google (1998) itself as much as that could hold for any other Google product launched over the years. And that’s perfectly fine. Branching into a specifically nuanced area towards envisioning a product that can solve for problem(s) could happen at any stage but the product vision aligning with the org. vision would mean lower probability of chaos & confusion perpetuating.

NOTE: Irrespective of whether it is the Org. vision or the Product vision, it is imperative that it sticks on for a significant period of time & doesn’t keep changing frequently although it could still be subject to change due to a market-drift. So, there is nothing written in stone.

Time Allocation

How much time does one devote to arrive at a workable vision? (and I face this question a lot over my engagements with cofounders)

Consensus across industry experts quote that a healthy org. would usually allot ~40% of their work-week towards cementing the vision when whether or not one is actually doing so today is totally debatable. Given a 50-hour work week that constitutes ~20 hours for the vision.

Yes, that’s a fair deal of time given how one could be looking at 20 hours for the vision over a whole quarter or two given how the other initiatives / functions in the pie (refer pie chart below) do take center-stage over the subsequent weeks. And it shouldn’t come to you as a surprise that the decision makers in your org. spend that much of time on the discussion when you may be totally unaware given how you aren’t really involved in that discussion.

At this stage if you happen to be filled with questions like:

• Would that time slice really suffice?

• Would repetition do any good as for cascading the vision & is that even needed?

• And more importantly, should leaders / cofounders have meetings with the major stakeholders centered around the vision more often?

then you may have already got the gist of this article.

“Experience teaches us that the oversight leadership is often associated with is rarely about the intensity (quantity); it is more about the impact & the influence (quality)”

The number of hours spent discussing vision or the frequency of review meetings matters far less than the rigor of the thinking applied within them. Anchoring the vision is important, but what truly determines impact is how it is interrogated, reinforced & translated into action.

Across the lifecycle of any product, challenges inevitably surface that trace back to the clarity or ambiguity of the vision. Misalignment rarely announces itself loudly at first; it manifests subtly in trade-offs, prioritization debates & incremental decisions that drift from intent. That is precisely why deliberate alignment early on ought to be non-negotiable. Perfection is unrealistic. Errors are inevitable. But the timing of the errors often tends to define their cost.

Mistakes made early are tuition; mistakes discovered late are penalties. The earlier a misjudgment is surfaced, the lower the cost of correction — financially, operationally of course culturally. As products scale, so does the cost of its correction. A disciplined leader therefore continuously evaluates direction, pressure-tests assumptions & intervenes when trajectory diverges from intent.

Owning the vision is not ceremonial, it is operational. It requires constant calibration of initiatives against the magnitude of the outcomes they are expected to produce. That calibration is not static; it varies by product type, market maturity & cycle time. A B2B robotics platform, for instance, will demand a longer strategic cadence than a B2C gaming product operating in rapid iteration loops. The tempo differs but the obligation persists.

…which raises an important question:

→ Should communication of directional shifts be frequent?

→ Yes, absolutely welcome, but they should NEVER be reactive.

Communication must be consistent, transparent & contextual. Teams may oppose constant change but they thrive on constant clarity. When adjustments are made, they must understand not only what is changing, but why & how it reinforces the overarching vision.

Ultimately, leadership comes down to ensuring:

• - coherence at scale

• - that vision rubs off as direction

• - that discipline further sustains it

• - timely communication protects it thereof

And, quality always outweighs quantity.

Now, here’s some more food for thought:

When roadmaps get presented at a regular cadence, why aren’t there enough sessions that stress on the vision?

Not required, you think?

The common understanding is the vision happens to be fixed once it gets formulated (often behind closed doors involving the leaders) & isn’t subject to / not inclined to change like other artefacts, for instance: a roadmap. And common belief is it is not really necessary to hold these meetings / briefings towards ensuring team alignment.

Well, yes. Totally agreed. But a leader ought to focus on a few things here:

Vision is often treated as a starting ceremony, articulated at off-sites, embedded into decks & then assumed to be self-sustaining as strategies & roadmaps unfold. In many organizations, it is perceived as a one-time declaration.

And that means continuously assessing whether teams are truly advancing toward the intended future & not just shipping against their own plan. It requires rigor in asking:

• Are we genuinely on trajectory toward the vision, or merely busy executing?

• Do the scale & ambition of our initiatives match the magnitude of the outcomes we seek?

• Is incremental effort sufficient? Or do we need bold inflections to elevate energy, clarity & conviction across the org.?

This evaluative lens is not occasional work. It is a full-time mandate. Vision must be extrapolated into measurable signals. Assumptions must be recalibrated. Effort must be weighed against impact. And when momentum dips or drift emerges, the leader intervenes, not with noise, but with clarity. This is why the phrase visionary leadership endures.

Because true vision is not simply imagined…

• It is governed

• It is protected

• It is continually aligned to execution

And that stewardship is what separates declarative leadership from transformative leadership.

Vision is where alignment truly begins. While some argue that mission is the starting point, over my experiences I’ve so learnt that it is best for the mission to be owned by the cofounder — the individual who carries the conviction behind the idea & assumes full accountability for setting it in motion. The vision mobilizes the organization. It translates intent into direction.

Cofounders / senior leaders cannot afford to merely articulate the narrative & step away. Governance does not end at strategy decks or roadmap reviews. There is a less glamorous but far more consequential transformation that must occur in a leader’s workflow — one that receives far less attention than strategy formulation.

“Exceptional leaders remain deeply engaged, they stay close to stakeholders, they continuously gather signal from noise, synthesize updates, calibrate assumptions & reassess trade-offs”

Every effort, every initiative, every metric is examined through the lens of the original vision. They evaluate whether projected outcomes justify the deployed effort. They interrogate gaps as & when they are found towards understanding friction points / blockers. They pressure-test forecasts. They measure trajectory against ambition.

Time & more importantly, timing — is unforgiving. Once lost, it cannot be reclaimed. Leadership, therefore, is not merely about crafting strategy or modeling projections. It is about consistently assessing the “yield curve” of team effort against strategic intent — ensuring that energy is being converted into meaningful progress at the right velocity.

And this is never episodic. It is CONTINUOUS, RELENTLESS, RHYTHMIC akin to the blood circulation in any living being, it must be persistent — because the moment it slows, the organization will too.

• February 2026 marks the culmination of the 4^th year of TPW (The Product Web) & what started out as a small experiment (inspired by some big names in product management) has now turned into a full-blown consultancy today

• When I started off writing I thought I’d hang my boots up post hitting the 100-article landmark but looking back, the interactions over my mentoring sessions transformed into insurmountable inspiration eventually leading to a deluge of thoughts that had to be structured for the greater good of PMs world over…

• As much as I have mentored PMs I have also had a few opportunities to mentor product leaders (VP, CPO levels) which I was hesitant to accept initially but eventually turned out to be the best thing ever, given the quantum of learning both ways (I took in just as much as I gave over those engagements) they were a win-win

After dishing out:

• 200+ articles non-stop - week after week…

• 2000+ meaningful on-topic interactions with readers, subscribers…

• ~1,000 mentoring engagements vide PMs, Leaders across domains & the globe

• advising 10+ start-ups across stages (inception - growth)

the one thing I can heartfully say as I prepare to now shift my focus from here is:

“Thank you for the opportunity!

I underline this as I have all throughout my journey at :

– “Four years of hands-on 1:1 mentoring have compounded my learning in ways that even a permanent product or leadership role at an MNC would have struggled to match”

‼️ IMPORTANT ANNOUNCEMENT ‼️:

The number of incoming requests for my strategic work has tripled over the past quarter & this is something that I have been yearning (/ manifesting) for, for years now, which also was partly the rationale behind conceiving itself…

• I shall be focusing more on my strategic engagements henceforth:

  • So, when the shift in focus would now mean me pivoting onto topics that are closer to strategy - the troubles, the nuances of formulating & of course deploying it successfully, the chaos, the urgency, the hustle, the daily-grind, the humdrum of top management (CXOs, Cofounders…) EXECs, which also means that I may not be that regular here as I was up until now, although I’d do my best to keep this going

• If you want to get in touch with me:

  • you could drop me an e-mail / follow me on Facebook (CHECK LINKS BELOW)

Some useful links:

• #PREPUP Series (posts aimed at helping PMs tackle behavioral questions):

  • PREP-UP SERIES (071/100)

  • PREP-UP SERIES (057/100)

• Few Popular Threads / Case Studies

  • The Elevated Trapdoor

  • Building Team Charter (KPI Trees)

  • Effective Onboarding Strategies for Better Retention

  • Building Relationships is a Crucial PM Trait

• The Socials

  • Facebook page:

    • TPW - Facebook

  • E-mail:

    • mailto: bgp.inv@gmail.com

  • LinkedIn:

    • Guru Prasad

  • Twitter (and this is where it all got started for me)

    • @BgpInv

PREFACE: 

When the ideas expressed here in the article may come across as pretty extreme to a certain set of people, whether the world would get there someday soon is totally debatable.

It is true that product managers come from really eclectic backgrounds encompassing a mix of skills they may have mastered over their experience, boldly underlining the quote “anyone can be a product manager” all the more. Although product roles demand PMs to possess a diverse set of skills with each of the org. functions right from Sales, Support, Marketing to Development, Technology & Design, the real question is:

• Is there any one particular skill / a combination of skills pertaining to any of the org. functions that can be touted as the lethal combination when combined with the mandatory skills one would usually associate with product manager?

Well! Around a decade back the answer to that question used to be a humble NO.

But with changing times, the advent of AI & how those tools have taken center-stage today disrupting the market space eating into the workflow of every org. function listed above, the answer to that question seems to have changed somewhat to a YES over the recent years.

And there’s a specific reason why I say that. Let me explain.

• AI has made content generation, lead generation & the process of going from a mere prospect to a qualified lead simpler, removing quite a number of blockers from the workflow of an average marketing guy

• AI has made some L-1, L-2 issues totally resolvable without any human intervention whatsoever thanks only to NLP & Chat support, not to mention some features like auto-heal that have an upper hand as for L-3 as well

• AI has made coding look ridiculously simple given the advent of disruptive tech like Vibe Coding for instance, almost taking a significant step towards neutralizing the whole coding skill itself making the average tech interview that needed one to remember syntaxes from the 2000s look like a total joke today

• AI has made Sales more doable as one is presented with a whole bunch of ideas as for those sales pitches given how an elevator pitch or a pretty detailed pitch could be generated in a jiffy with just an apt query (/ prompt)

• AI has also made inroads into the average Designer’s workflow arming them with the right kind of tools towards generating better boilerplates if not detailed & precise content at a click whilst giving them ample time to focus on bigger problems that are mid-way between mapping strategy to execution

With AI taking over most of the workflow & boosting productivity manifold vis-à-vis a skilled person, there ought to be no second thoughts over the skills of a product manager changing with time as well.

NOTE:

Just FYI, PM interviews have changed to a level where one is asked to use a Vibe Coding tool to generate something tangible mirroring the solution to a problem over those preliminary rounds.

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Yes, it is true that PM roles could be getting more hands-on with Tech, at least in some contingents. But as for current & future times, could that be touted as the GOTO skill that could prove to be a lethal combination when factored in with the usual product skills?

Firstly, when one refers to product skills the one major thing it could stand for is undeniably - Product Sense. And that happens to cover the Why & the What of the product. What are we building & why are we building it?

If you give it some thought, you’d realize that it needs someone who can champion the user’s needs which obviously demands a detailed understanding of the problems of the market & the craft of turning them into opportunities shaping & making products beyond great. So, some skills over the top here would comprise of - Empathy, Market research, Business acumen, Creativity & User behavior.

But what skills when combined with product skills would go on to suffice & qualify as a lethal combination?

Let’s explore product skills as tied to the skills over individual org functions one-by-one, section-wise.

1. CUSTOMER SUPPORT & PRODUCT

One of the primary skills someone from Support teams would bring into product would be “USER EMPATHY”, which just manages to scratch the surface as for the skill a product manager. When the role encompasses some problem solving, the whole point of it being reactive makes it look retrograde when pitted against skills demanded by product roles across the board.

• Would that qualify as a lethal combination?

  • NO, absolutely NOT!

• Why?

  • Because that still doesn’t have anything at all to do with one of the most important areas of product management – which is product strategy

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2. CUSTOMER SUCCESS / SALES & PRODUCT

Growth models like PLG mandates the presence of a team like CS (Customer Success) given how SaaS products are accessible to everyone on a Trail basis & it becomes imperative that someone from the org. monitors those sessions, sniffs out those problems / blockers that users (/ users-to-be) are faced up with, solve them within the least possible time helping them realize the value for a start, hooking them on, followed by interacting, building a relationship & moving them users up the ladder gradually signing them up for more premium features optimizing revenues thereof.

• When that sure is a skill area that could have a lot of parallel with the responsibilities usually listed under product roles would that qualify as a lethal combination?

  • It is an important transferable skill alright, that’s still a NO!

• Why?

  • Because it deals with the workflow post the product’s release & doesn’t touch upon the strategic part of it which happens to be quintessential when we are on the subject of a LETHAL COMBINATION

3. MARKETING & PRODUCT

There are tons of things that both individually & collectively quantify the success of the product post the build & the scaling. One of them happens to be Marketing the product, getting the masses aware, building content that can be of relevance to the problems that resonate with them largely enticing them to advance through the funnel & that could be vide a sign-up, engagement, adding items to the cart & clicking on check-out, in other words – enticing them towards trying the product / one of those features. Statistically speaking, this also stands as one of the weakest links when someone in Tech is looking to make that move to product.

• That’s no doubt an important skill alright but taking nothing away from it…

  • It still can’t be touted as a lethal combination in the parlance of product management…

• Why?

  • Because although it deals with understanding & factoring in user behavior which happens to be an essential aspect of product, it doesn’t have anything to do with product strategy & also someone from marketing may not be well-versed with things that happen over the build phase as well

4. TECH / DEVELOPMENT & PRODUCT

It is only fair enough to say that the product would cease to exist sans the efforts of the development teams given how they are tasked with the cycles governing the building & timely releases of features. A pretty sought-after skill nevertheless, as it has been since the turn of the millennium with how Java as a language took over the whole internet / web products space, it may not be altogether wrong to say that the onus on it has witnessed a minor dip given the advent of AI tools eclipsing a major portion of the skill set a developer is identified with.

• Taking nothing away from development. In today’s world of AI…

  • It is most likely to fail to qualify as a lethal combination as for product management…

• Why?

  • DEVs may have most of the areas covered & could also manage to tick off a few checkboxes over the behavioral understanding bit, but if you look at products that are labeled world-class you’d notice that it is all about the UX, Usability eventually coming to terms with how that could constitute areas outside the purview of pure-breed development while still carrying a healthy overlap with technology

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5. DESIGN & PRODUCT

One major misconception that has been alive although waning away slowly but has somehow been carried for years now is how Design only deals with the look & feel of the product - the Presentation layer so to speak. But as one gains experience / gets to interact, collaborate with more senior designers they come to terms with how that may not altogether be true as Design goes deeper than bone, deeper than what’s visible on screen, deeper than the usability.

UX is primary & of course pretty basic a requirement too. A perfectly functioning product that solves a problem for the user is more or less the average expectation most of the market would carry. That happens to be a given, any day.

• But, would that really suffice especially when one is talking about blinding adoption numbers & hypergrowth?

  • NO! And I am sure you are with me on this one here

• Why?

  • Because products ought to go above & beyond the collective average expectation of the users if they are to get any closer to enticing them & hooking them on, but there ought to be something of a driving factor that gets users excited about using products on a regular basis, more so when there seems to be no dearth of them alternatives from the other market players in the world today across any domain / sub-domain

“Great design lives beyond pixels & screens—it takes shape in the depth of problem representation finding its soul in the conceptualization of the solution”

Remember that the onus lies in the manner in which the problem is solved, the steps in the workflow specifically designed towards reducing a significant portion of the user’s burden, which could encapsulate the smoothness with which the individual components interact with each other in the background.

• So, back to our question now - can the design skills qualify as a lethal combination as for product management given today’s parlance…?

  • A sure & certain YES but with a few preconditions!

• Why & how so?

  • When true-breed design explores the depth of the problem encompassing market, user & also competitor research to begin with, enumerating them problems, factoring in user behavior, playing a primitive role in framing the problem statement, conceptualizing solution alternatives, designing the solution from scratch & making it more interesting for the users is what design roles have evolved to be over the recent years

  • Whilst of course employing the relevant AI to further build the product, envisioning ways / means to take them to the market & scaling them thereof could land into the product manager’s porch

A truly lethal combination indeed.

20 years back not too many people / teams worried / paid excessive heed to how their users are finding them given how it was early days for the concept of the internet & it was yet to sink in. But today, that very parameter has seen a significant amount of affinity & it also has transformed into something of a default. Identifying & attributing (formally known as ATTRIBUTION) the source of conversions is one of the major & mandatory aspects in the parlance of SaaS products as the core of the business workflow lies on the web & that information can help further channelize all marketing efforts towards getting more bang for the buck, optimizing marketing ROIs paving the way for “windfall gains”.

One significantly important change in the way teams strategize & operate today as opposed to the yester years is in the very definition of attribution itself. Earlier (as early as 2008-10s AFAIK) although product teams did pay heed to the source of conversion, they pinned on the last touchpoint in the whole stack of interactions a user may have had over landing on a page / clicking on BUY which is defined by MTA (Multi Touch Attribution). But factoring in the whole customer / user journey towards analyzing & decoding the psychology of the users arriving at the all-important blueprint of the user behavior is where most product teams stand as of today. Given the 2025/26s there’s no topic that can exist sans the mention of AI. And attribution isn’t far behind as we shall witness over the remainder of this write-up.

Primarily, if you have had any experience building software products (however old / from whatever era) you would agree with me on the idea of automating the whole ATTRIBUTION process.

• How easy is it for someone (/ a team) to go tracking / back-tracking the innumerous clicks, enumerating them all, analyzing common patterns & arriving at a significant chain of events that lead to conversion?

• Can you envision those massive datasets one ought to be dealing with…?

• And what about doing that time & again like clockwork?

AI can leverage ML algorithms to analyze complex, multi-channel customer journeys that go beyond simple first/last-touch points helping uncover a few hidden truths, accurately assigning significant weightage to each of those interactions. Of course, dealing with massive datasets to discern those patterns, use them as input for predictive modelling, being able to detect & drop the insignificant steps towards arriving at real-time insights leading to smarter decision-making across the entire customer lifecycle happens to be a given here.

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AI for Attribution

Before diving into the AI tools here’s a comprehensive list of the benefits AI can add to the domain of attribution:

There are ample AI models & tools that marketing teams employ towards enhancing their productivity, getting more bang for the buck. And here are a few of them you / your teams should explore & incorporate if ROI optimization feels like a burden beyond what you can bear.

→ Algorithmic Models

Some algorithmic models you have to be aware of include:

1. MARKOV CHAINS FOR JOURNEY MAPPING

Markov Chains envisions & starts off by treating the whole customer journey as possessing a series of states like say (Advert, Email, Website, Social, Conversion, Drop-off) with varied probabilities of moving from one state to another depending on the influencing factors.

So, the probability of the users advancing to the next step would depend entirely on the current step & not the past history, which sounds true largely although some exceptions could exist.

A user could drop-off at any of the stages with literally no control over it, which is what the algorithm tries to factor in by way of a concept called the “Removal Effect” where it tries to predict the likelihood of conversion after dropping one of the stages from the workflow. So, the percentage of the drop would then lead to attributing the right amount of onus onto the given channel / stage.

For ex: If removing E-mail from the steps in the workflow above results in a 21% conversion drop then it could be clear that E-mail as a channel would deservedly have an attribution of that number.

2. SHAPLEY VALUE FOR FAIR CREDIT DISTRIBUTION

SHAPELY tries to gauge & arrive at the fair contribution of each stage / channel towards influencing the final outcome assuming that all the channels had participated. It does so by considering all P&C of orders in which the channels could show up over the journey (Email → Organic → Paid Search or Organic → Paid Search → Email) measuring the value each of them adds when they join.

Assuming the total conversion value is $100, Shapely would credit the attribution to each stage like so:

There are no assumptions (no room for it in fact) & favoritism is also done away with here. It is just pure contribution that’s valued & that’s that.

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→ AI Attribution Tools:

Here are some AI tools you cannot afford to look away from if your prime focus happens to be the optimization of ROI of your MTA in 2026:

1. USERMAVEN

If you happen to be looking for GDPR compliant & CCPA sensitive attribution stacks USERMAVEN could be just the tool for you. It puts privacy & security first while focusing on attribution that still offers depth & has some sting in it as for being true-breed multi-touch. It happens to be one of the most popular attribution tools out there & it boasts of:

• Attribution by pattern detection

• Smarter predictions to uncovering customer journey

• GDPR compliant & CCPA sensitive

• Privacy Centric

2. ROCKERBOX

ROCKERBOX offers true breed MTA across digital + offline channels, you name it - email, ads, podcasts, TV etc. & it could be best suited for teams who are dealing with omnichannel marketing & can use a host of actionable insights at a budget friendly price. Some features it boasts of are:

• - Smart credit allocation

• - 100% customization of models

• - Real-time reporting

• - “What-if” analysis

3. MEASURED

Measured just like the name suggests would empower you with decisiveness by addressing one universal problem which is the effectiveness of a given campaign. It is known to be best suited for paid social campaigns (for instance: YouTube). It offers:

• - Incrementality testing

• - Media-mix modelling

• - Cross-channel analysis

4. DREAMDATA

If it happens to be complete journey-mapping for B2B orgs. covering every phase of it right from leads to deals Dreamdata could be the ticket. Given the longer cycle of conversions in B2B this tool becomes the ideal choice for such teams who are pinning on ABM (Account Based Marketing). As for its features:

• - Full-blown AI pipeline

• - Impeccable insights on the whole journey

• - Revenue generating touchpoints

5. WINDSOR.AI

Windsor.AI offers Algorithmic MTA & employs MARKOV model discussed earlier. It solves one major problem which is to enable attribution sans the use of Cookies unlike the most popular tools used right now. It would be better suited for Mid to Large teams so a Start-up may not find this ideal although there are always exceptions. It comes with:

• Predictive budget optimizations

• Predictive attribution driven by ML algorithms

• Robust channel blending

• Cookie-less attribution

• Deep integrations to other platforms (Google Ads, Amazon, Shopify etc.)

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6. TRIPLEWHALE

Triple Whale comes with a prime focus on revenue-centric attribution & it specifically targets the D2C, eCommerce businesses with a specific focus on brands affiliated & running on Shopify.

• Revenue centric model

• Real-time dashboards

• Cross-channel revenue tracking

7. COMETLY

COMETLY is another tool that offers real time cross-channel attribution with the liberty to choose your attribution model giving you the freedom to operate with stuff that has worked for you. It is known to be suited mainly for the ones who are into Performance Marketing & are looking to factor in real-time insights accurate up to the minute. It comes with:

• AI driven Traceability

• Transparent journey visualization

• Detailed performance tracking

• Auto-Sync across other tools like HubSpot

• Customizable dashboards

• Integration with Ad platforms

NOTE: 

While on the topic of MTA there are HUBSPOT ATTRIBUTION & ADOBE MIX MODELER as well for you to explore as they come with data-driven attribution models & leverage AI-ML over large datasets. But they could be best suited to large MNCs who are already using the ecosystem of tools provided by ADOBE & HUBSPOT.

→ Choosing the Right Tool

The whole toss in choosing the right tool would have obviously close correlation to the kind / size of org. When some of these tools mentioned above could be more suited to Start-Ups / SMEs, there are some that suite the style of work one would associate with large MNCs / enterprises.

Here’s a visual that could act more like a rubric in choosing the right one for your org:

→ Into the Future of AI & Attribution

The speed of evolution of a domain like Attribution is not only limited to the advancements in the underlying technology. There’s also a lot riding on the way we make our decisions towards choosing & buying products online. May be things would evolve & there would be a more standardized way to check the authenticity of products aiding / influencing our decision to buy.

Also, on the subject of technological advancements merely saying AI is evolving does sound like an understatement. There could be new ways to peg user behavior to leading to better insights, the integration of newer platforms using up the data on hand juggling those privacy & INFOSEC (information security) aspects seems more likely.

If you happen to be off from the internet for a couple of weeks today, getting back could give you the jitters over the number of AI tools that have been trending compared to where you left off last & how most of your peers are talking about some hotshot new tool that never even existed before. When all that ought to be taken in with a grain of salt, there’s no doubt that you ought to keep an eye open to the advancements more like what a TECHNOLOGY ADVISOR (a role I reckon could be pretty BIG in the days to come) would do.

For more contextual understanding, assume you are a PM at an org. that builds products in the Sustainability domain & you happen to be dealing with a problem that has to do with the real-time estimation of Carbon-emissions from a certain hyperlocal geography earmarked for data collation & analysis. Enlisting the sources that are responsible for C-emissions would be quite a task needing you to run quite a number of errands, the complication of the algorithm could turn out to be pretty shocking if you happen to plot it over the BIG-O(n) notation.

Take SCOPE-3 Emissions for instance. That refers to the emissions from indirect sources. One can’t ignore the possibility of tons of vehicles that stop / pass by a hyperlocal area fueled by the logistics / supply chain requirements of factory hangers / manufacturing units. When factoring that in would only be practical one may have to depend on & acquire it from third-parties trusting their accuracy.

So, if you were to represent the equation mathematically, you would land a realization around the factors / elements / variables not being all that straightforward given their dynamic nature enforcing you to label them as constants / variables whose values could be tied to situational complexities. It is only pragmatic to perceive that situations may be prone to change as they could induce a degree of uncertainty & diving deep into those calculations expecting to crack the code & arrive at perfect prediction time & again could prove to be a futile waste. And the fact that such uncertainties could stem from a situation / source least expected does lead to the concept of Knightian Uncertainty.

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Named after the economist Frank H. Knight who distinguished between RISK that points to “MEASURABLE UNCERTAINTY” and TRUE UNCERTAINTY that cannot be quantified / measured, it could be typically encountered across domains / job roles that have to do with innovation or technology. The uncertainty / unpredictability could pose quite a real threat given how one may be thinking / envisioning something that’s path-breaking & disruptively innovative, venturing into an entirely new problem area across a new product where nobody has ever managed to set foot.

⚠️ FAIR WARNING: 

One of the gravest of sins that is commonly committed across the board (both startups & MNCs included) is to try & call the market / go ahead with the build based on assumptions that are fleeting, which is no real means to tackle the uncertainty. If anything, one is just managing some hodgepodge, multiplying the uncertainty manifold alongside their own troubles thus end up digging their own graves.

Talking of a more relatable problem in today’s world of Tech & AI, imagine a start-up developing a revolutionary AI logistics product that relies on UAV (Unmanned Aerial Vehicle) / Drones towards facilitating faster deliveries. When there is a significant value addition in launching such a product in today’s time blindly ticking off the DESIRABILITY, it could still face severe challenges at the legal, logistic, security levels (flying over some high security zones) posing more than a visible threat to the idea denting the overall FEASIBILITY of the product when the VIABILITY could still get cleared in most cases. In such situations, of course the proof of the pudding lies in the eating.

“The best way to test out new Tech products (especially physical ones) is to plan a miniscule pretotype (NOT TO BE CONFUSED WITH PROTOTYPE) – something of stripped-down version launch, test it thoroughly gauging / tracking metrics that have to do with overall adoption, factor those learnings in & allow the product to course-correct gradually & iteratively”

Although it is possible that the uncertainty may phase out over a period of time given how the whole ecosystem itself changes / adapts to newer stuff / tech, that could prove to be the worst route a product org. could take given how it would put them in a retrograde, rendering their approach reactive (when they ought to be proactive) taking them miles away from being the flagbearers of innovation. Such orgs. may find themselves at a constant battle between waiting for data to take the right decisions & spearheading innovation launching products that can entice & capture the imagination of the target markets with the former being the most probable result.

So, is there a way out of this?

Well, I’m so glad you asked.

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There are ample real-world scenarios that make it rather impossible to precisely assign probabilities to the favorable outcomes given the loose correlation between the historical patterns exhibited by the data & the future course the product ought to take. Such limitations often call for some out-of-the-box thinking towards keeping pace with the innovative mindset – a trait often demanded by those job roles as a prerequisite.

The reason most decision makers find themselves in a catch-22 is because they try to retrofit the data they have on hand to lead them towards strategic clarity & that may not always work.

Well! There is surely more than one way to peel a banana. When factoring in the Knightian uncertainty towards landing sure shot laser-sharp decision-making is totally Utopian, it does help induce some pragmatism whilst improving focus, rendering teams more flexible & resilient to any surprises that may crop up via the situations.

“As a classic investment principle & also rule of thumb, one way to manage & tackle risk is to peg it to the inherent reward both in short & long-term”

How can you navigate the uncertainty?

When the uncertainty could come bundled in with a situation offering absolutely no escape rendering most helpless & hitting a point of no return, there are a few methods one could rely on towards navigating them effectively, when the effectiveness could be relative to the experience one possesses.

“What do we have to do next?” happens to be a common question that anyone framing strategy would pop albeit repeatedly too. Uncertainty when factored in ought to lead to better strategizing so as to be more fluid & prepared in situations one has very little control over. Although hiring experienced product managers who don’t just carry a theoretical understanding but are well-versed over the application of principles & nuances constituting the very essence of Product Sense does go without saying, there are these traits one ought to be in total command of:

1) Fixed Vision, Flexible Roadmap

Having a fixed vision would mean being totally clear on the long-term goal of the product but at the same time being more flexible as for the roadmap so as to factor in the uncertainty, be prepared for those surprises the markets could throw disguised as dynamic changes. Going in with a FEATURELESS ROADMAP could work like a charm in such cases. Although this wouldn’t shield one entirely from some Black Swan Events the flexibility would suffice to keep one on their toes, improving the preparedness towards tackling the situational complications.

2) Scoping the Depth

There are ample tools like the Business Case Canvas that can help explore the depth of the situations, enumerate those nuances & get into analyzing the nitty-gritty before marching ahead with the formulation of the strategy thus offering enough flexibility & arming one with the required amount of clarity as well. When some may opine that immersive research / long-term strategy like SIMULATED TEST MARKETING could be apt, there’s a lot of semblance that a sharp product manager with an impeccable product sense could bring here.

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3) Focusing on Experimentation

With uncertainty looming large, the need to be flexible would call for a product strategy that’s oriented towards experimentation & in small pockets as well. Taking baby steps towards that end goal, building in public, learning & course correcting based on the feedback received would work pretty well in such scenarios irrespective of product-types / domains / org-types. Launching small & building on that thereof as suggested by any classic Agile manual ought to be the way forward in these situations.

4) Waiting for Clarity

As for common knowledge, waiting for data towards reaching the right bout of insight & helping reach a state of clarity could be the most natural thing to do in any situation of uncertainty which is also attuned to human nature, but sadly that fails miserably when you happen to be a PM who is hired to spearhead innovation & is entrusted towards taking products / features to the market & scaling them thereof. Such scenarios could surely pose steep challenges for many PMs as they would feel terribly pressurized to come up with something tangible even in cases where the data seems to be totally lacking, putting their decision-making skills to the sword. Most times, this waiting for clarity doesn’t even qualify as an option given how it could be seen as a retrograde move in the parlance for innovation.

Remember:

Although conventional thinking would suggest that one bides time, delays the decision until one has the right bout of insight, taking that route would more often than not prove to be detrimental for a product manager. That would never is a viable option for a PM. So, using up one’s experience, reading the situation (and that includes everything from the market / users to the competition, the advancements in technology) carefully, apply product sense to solve for the problems whilst strategizing & looking for the best way towards landing something tangible in front of the users ASAP, testing them thoroughly LIVE on-field ought to be the default route.

Suggested Further Reading:

Let’s kick-off with an analogy.

I’m sure you’ve heard of people talking about geniuses of the sporting world – the way they think, operate & end up on the winning side more often than not, at times from situations that seem totally dire & impossible is what gets them to stand out. Usually associated with an experienced sportsperson if the terms “he is a footballing genius” or “he has an amazing footballing brain” you happen to hear from the commentary box left you wondering what exactly constitutes a <sporting brain> you may not be alone. Something that’s straight out of a coaching manual where they transform ordinary people into habitual winners, these terms could be representative of the power to read the game, factor in situational complexities & chart out plans that can eventually lead one to victories.

• What do you think a <sporting brain> really is?

• What makes them so perfect? Is it merely the experience?

But not all players experienced are known to be sporting geniuses, are they?

If you deep dive into how they (their brains) function, you’d realize how most of these parameters are commonly applicable across sports.

If you observe, there’s one key element that gets such genius players to standout & that is DETAILING. Detailing goes above & beyond mere awareness. It of course encompasses a supreme degree of awareness alright but also involves a high degree of consciousness about the whole environment, the situation & reading its subtlety well in advance, being well informed of the nuances, the know-how of exactly which lever to pull so as to maximize a certain metric, optimize for a goal steering oneself towards a position of advantage thereof.

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But all of that doesn’t necessarily have to happen over the flick of a switch. If anything, there’s tons of hardships, failures, wrong moves that one endures before one gets perfect at this craft & builds the skill.

Product could have a lot in parallel as well. In fact, this is one place where all those skills could come into play again.

Narrative:

Over one of my recent mentoring sessions @ TPW (The Product Web) I happened to ask an experienced product manager who was aspiring to be a product leader soon about a product sense question. You know the one that asks them to pick a favorite product & then get down to the strategic side of working towards a given goal. The lack of structure & thinking in the answer surprised me to the core.

Post that when I tried to point out the areas of improvement & the importance of coming out with a structured response, the response I received startled me all the more. The person said, “I am a bit rustic I know. I need to brush these areas up prior to appearing for interviews & I can use your help with that”. And the whole point is, you just get one shot at the question. You may not get a second crack at it at all. No second chances here.

So, if an experienced product manager who is holding a product position at a product org. in the USA can come up with this response, just imagine where you may stand in comparison. Don’t get me wrong. I am not saying that it is so tough & would be an uphill climb, but all that I am saying is one can still go off on tangents while playing product roles (demand of the job role) & lose touch of the basics.

“If there is anything more important than building a product brain it is to keep polishing / nurturing it constantly, getting better at it iteratively so as to get more objective & structured with the thinking”

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Building a Product Brain🧠?

Building a product brain of course comes by tons of learning, pragmatic exposure to situations of varied pressure & toughness where of course practice makes one perfect. One may not be entirely wrong to think that a large portion of building a product brain involves a mastery over product sense. But building a product brain could involve a bit more than that, like for instance nuanced thinking & practical application of concepts / theories. Someone with a product brain would be deeply analytical to begin with whilst leaving no stone unturned when it comes to exploring each & every nuance of the problem space, enumerating major problems, coming up with alternatives to solve those them whilst operating within the confines of the scope at all times.

“It is not just about WHAT you say as a product manager but the WAY you say it, the narrative that carries more weightage”

For ex: Say a PM who has built a product brain & is operating at META right now. Supposing they are tasked with improving engagement by 10%. Not only would they talk of the best ideas over a roadmap towards getting to the goal, they would also have some crisp & practical steps towards planning it all step-wise & taking it ahead. So, they won’t just stop at quoting a way like say video shorts, they would also glean into those analytics to tie it to the demographics, user behaviors & plan the whole feed in advance, thinking about a few challenges over implementing them & their real-time adoption patterns vis-à-vis the other choices the audiences have at their disposal right now.

Let’s now break down the steps towards building a product brain.

1) Thoroughly Conversant

Being well-read is one thing but being thoroughly conversant, totally aware about everything right from the subject of product management as a whole including all of these:

• Awareness of Concepts, methodologies although is perceived to be mandatory, the acumen to decisively & consciously apply them towards solving a problem is what really matters more often than not;

• Knowledge is mandatory alright & imperative at a basic level but the pragmatic ability to decipher the right piece of knowledge befitting a given scenario always scores higher;

• Being customer-obsessed outweighs customer-centricity given how the former lot would begin their thinking by prioritizing the needs of their customers, making a ruddy habit out of it

• Ability to glean the right quantum of insight by hinging on the right bit of data is something that adds semblance to the quality of being thoroughly conversant;

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2) Deeply Analytical

Although many believe that the power to analyze something deeply comes as a blessing / gift building the skill may not be that difficult as it could be down to some practice, learning & course correcting along the way. So, building this quality could be essentially down to:

• Looking at the world from an Analytical Lens does help a lot given how one could be deeply critical about every parameter, digging right into the details towards gaining a thorough understanding of the situation / environment, being totally detail-oriented;

• Asking the right questions towards delving deeper into problem areas, helping zero-in on the right one inducing a degree of objectivity into one’s thinking, stumbling upon a few nuances & exploring each of them in depth could lead to a lot of clarity;

• Being comfortable in the problem space would need one to do away with any sort of bias towards solutions as they would need to develop & actively practice customer obsession rooting it deeply into every inch of their workflow;

• The problem-solving ability comprises of many layers given how one could be dealing with complexities induced from various sources & the trick here lies in blending the right quantum of creativity & technology towards envisioning solutions that not just resonate but stick with the users leading to multi-fold conversions thereof;

3) Growth Mindset

When PMs are entrusted with the job of taking the product & the teams towards those goals it is only fair that they build those muscles that can help them think, envision & steer everyone involved. Building a growth mindset is largely down to:

• Business acumen happens to be one of the basic factors that contribute to a growth mindset as that often forms a solid base given how one can really think from the perspective of the health of a business / an org. in general or a product in particular;

• Breaking free off one’s comfort zone could also be a precursor to building a growth mindset as one common trait amongst PMs who are successful are they tend to deprioritize comfort pushing their limits above & beyond conventional boundaries refusing to take anything lying down which could also mean being open to any kind of feedback;

• Being goal-oriented would mean being focused entirely on the immediate goals that matter to the product / the org., ruthlessly downvoting ideas if they are misaligned however great they are whilst possessing a mentality that don’t know how to stop & keeps questioning the status quo with what’s called the “alright, what next?” mindset that knows how to turn those challenges into opportunities;

• Timing the market calling it accurately that encompasses an understanding of the whole ecosystem of products, the user behaviors & their motivations, using a mastery over numbers (top-line / bottom-line) to glean insights into the overall market direction knowing what would work & channelizing all energies towards it;

4) Unparalleled Execution

PM ought to be great at execution is an understatement. That’s an expectation that comes attached with the job given how no JD in the world would explicitly call that trait out. And here’s how one can achieve unparalleled execution skills:

• Envisioning roadblocks / blockers is just a part of the game as that ought to be combined with the skill of coming up with alternatives towards tackling them;

• Prior experience in taking products from 0-1 in any capacity (Design / Development / Marketing) could add brownie points as one would then be conversant with the hardships, blockers, workarounds towards getting out of that rut & using that knowhow to steer teams, influencing them & collaborating with them towards reaching the outcomes;

• Using the position of influence towards lending oversight ought to be a given here as PMs may not really be the ones designing / building / marketing the product & all that they are required to do is to lead stakeholders / teams towards focusing on their quantum of outputs whilst stitching it to the high-level outcomes;

• Holistic ownership is another important trait as PMs often are known to own the outcomes stemming from the workflow of the teams & those individual members, so being aware of the work breakdown ought to lead to a sense of overall accountability using which a shared understanding & alignment can be built;

5) Rinse & Repeat

• Periodic review / retrospect just so that you stay in touch with your craft, keep learning the new stuff incorporating it into your armory of skills whilst erasing out the redundancies;

PROLOGUE:

I thought long & hard about topics to write about as I close-out one & kick-off another exciting year on TPW (The Product Web). But nothing really stood in comparison to the topic of competencies, you know – the skills that product roles largely demand. And this post isn’t just meant for the aspirants. You will find it relevant to you if you happen to be actively playing a product role as this could be extrapolated to target your next big move to product leadership.

Although some skills could be deeply specific to an org. given the stage they are in or the nuanced knowledge needed over a certain domain to operate in product roles, the skill set demanded is more or less the same at a generic level. And Ravi Mehta (@ravi_mehta) had dropped this visual on the very topic of Product Competencies quite some time back. I shall be taking that as a cue as for this article here.

Take a look at each of those sections & you’d see how most of them skills could be acquired over any job that hierarchically ranks lower than a product manager. Ok, acquired could be something of an overstatement. But one surely can’t deny the exposure to these aspects over roles that have to do with Design / Engineering / Support / Marketing / Sales.

For instance, team leadership. One could be entitled to leading a team (although as small as 2-4) as they are promoted to a Team Leader’s role from an SDE role where they are all an integral part of an Agile Scrum team. The same thing could be possible with someone who is playing a customer support role wherein a promotion owing to a few years of experience under one’s belt could put them in-charge of a small team. The exposure they gain there at times could just be enough to get a hang of the basic skills required although that may barely scratch the surface as for the skill-levels a product role would demand.

• Aren’t skills acquired over a junior management level (like say ‘Team Lead’) deemed fit enough for a product role?

• Why is there still a visibly large gap as for most aspirants given almost the same skills demanded across product roles?

• What changes that dynamic so much over a product role & why?

I shall dive into each of those sections from the elaborate visual above exploring the depth of those transferable skills & the subtle changes in them, their nuances, their dynamics & more importantly what proportion of them can be acquired over previous roles that have nothing at all to do with product management. And I shall also highlight a few inherent skill gaps that one ought to focus on bridging.

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SECTION - 1) PRODUCT EXECUTION

1. Feature Specification

Caught in the labyrinth of the solution space like a software engineer / business analyst whose diary may essentially involve the mandatory interface with the users, the understanding of the problem eventually leading to an enumeration of the features is only but natural. Given the context of each feature, the detailed specification (SPECs) would then take center-stage towards helping the engineers / designers progress with the build / development phase.

2. Product Delivery

Engineers, Designers, Ops, CS & Support often get involved at various stages of delivery requiring them to leverage their experience across deciding, planning, preparing & executing / implementing the deliveries of features / products. There could be stringent norms that govern these rollouts tied to time-tested strategies that have worked in favor of the teams & orgs. Engineers, Designers are tasked with checking in all assets collaborating with the Ops teams towards ensuring a smoother rollout whilst also gauging a few important metrics as deemed fit when CS (Customer Success) & Support teams could be the first ones bearing the brunt of a piece of code / feature / product not functioning according to SPECs owing to which they collaborate with internal teams to get things back into motion. The onus here is on user interfacing / client interaction & maintaining a good customer relationship.

3. Product QA

Testing the product / the feature prior to release feels so basic & primitive given how software engineering has put a significant emphasis on that from decade tops. And yet, there are cases of bugs being reported across products post-release even today as much as they used to happen years back, although thankfully the severity of the bugs seemed to have taken a rightful downturn owing to a certain degree of automation across QA & the rise of automated testing tools like Selenium, Cypress, Playwright etc. Although the responsibilities have drifted from a classic testing / QA role to developers / SRE (site reliability engineers) taking control today, there is no denying the role it plays in delivering stable features / products & in the times to come. Also, not to forget the role empathy plays in handling the users, their expectations & requests.

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SECTION - 2) CUSTOMER INSIGHT

4. Fluency with Data

One of the most crucial skills one can acquire outside of a product role that provides a direct advantage is the familiarity & fluency as for dealing with data. As developers / designers most may be too concerned about their deliverables / outputs but some smart ones thoroughly understand the importance of that user interface whilst also being totally oriented towards the data. Although the Ops team could have seamless access to the LIVE user data, there’s a sense of consciousness built around those usage metrics that one could develop & factor into their workflows. For if one removes those numbers, analytics, metrics from products & all that would be left behind may be mere guesswork.

5. VoC (Voice of the Customer)

Although solution teams rely on the market fronted teams towards accessing the VoC there are teams who use the nuances of the Agile manifesto towards conducting those VoC programs towards helping gain insight into aspects that are ranked higher in importance as for the users. Also, someone from CS (customer success) team could be more hands-on with not just conducting such programs but also deriving insights & making sense of it all leading to better decisions. Some situations here could often call for a tactical genius in pulling such campaigns off proving they can attain more bang for the buck.

6. UED (User Experience Design)

It is all psychological & imperative for any product to house a good designer / design team given the impetus on UX. And it’s a great trait if designers are starting off their thinking right from the elements that essentially add up to the visual appeal. And that of course may not be possible without delving into & analyzing those end user journeys, mapping out behavioral heuristics, innovating tirelessly over the best delivery by any means necessary contributing meaningfully towards user delight. If all that sounds more tactical & less strategic, it is because that’s the way it is.

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SECTION - 3) PRODUCT STRATEGY

7. Business Outcome Ownership

Not everyone operating in a team would be aware of the end goals, the final outcomes so to speak & if you have ever been working in a professional environment especially large MNCs you would certainly know what I am referring to. Typically, one gets the download from their respective stakeholders / reporting managers & plans out their share of the work focusing entirely on that at all times. But that very thing could act as a curse if you are looking at product roles when that could still work like a charm over an IC role.

8. Product Vision & Road mapping

Although at times in startups where engineers / designers / marketing / sales people could find themselves invited into one of those strategic exercises like road mapping or building a product vision, these discussions are usually above & beyond the ones operating in IC roles. Even at places where they are invited their participation would be towards providing essential & specific inputs about their jobs rather than taking an active part in framing either of the vision / strategy / roadmap.

9. Strategic Impact

Contrarian to common belief, although gauging / understanding the impact of a given strategy looks like it is quite an ask especially from someone in an IC role, it isn’t altogether impossible to break it down to the elements towards making sense of it all. Most who are IC contributors right from Marketing, Sales, Devs, Designers are usually handed descriptions of what to do (/ build) over their workflows but the other part of the truth also is that one can’t build anything out of thin air / fleeting thoughts. One obviously needs to be provided with the right understanding, the context & one also can take a liberty to pop more questions if one isn’t altogether sorted over it.

SECTION - 4) INFLUENCING PEOPLE

10. Stakeholder Management

Open cultures at startups have enabled a certain degree of exposure to stakeholders given how one may be forced to an interaction with them over gaining clarity or a perspective in, working in a multi-stakeholder setting with seamless XfN collaboration could still be limited to / deeply oriented towards one’s quantum of work, like say a Designer / Developer collaborating with the Sales & Marketing guys for more inputs. When direct stakeholder management could be pretty far fetched an idea for anyone in an IC role, the ones with some bit of junior management / team leading experience could carry some exposure here. Scrum masters for instance could be working with multiple stakeholders & would have ample chances to learn the tricks of trade as for managing them efficiently.

11. Team Leadership

Being able to work well in a team is pretty basic an ask today across roles, org. types & someone with leadership skills would thrive in such diverse environments. But taking of any teams like Design, Development, Support, Customer Success, Sales, Marketing there is more than a possibility of visualizing a Team Lead position where someone with a few years of experience under their belt could be tasked with basics over goals, tasks, progress monitoring, issue resolution the precursor towards building, maintaining a great camaraderie. But the fact of the matter is it could be all be bent towards Outputs, Tasks, Deliverables etc.

12. Managing Up

If there’s anything common about any of us it is that we had to be reporting into a manager / leader right from the start of our careers & most of us still do even to date as that’s just the way most of our jobs work. “Managing up” could call for a deep understanding of the manager, their expectations, the protocols established for communication towards building a brand of trust & that could be true of any IC role the ones with some junior-management experience could have a better hang of dealing with their own managers. But the reason that could all fall apart is the dynamic changes & variables that get appended to the equation when it comes to a product role, let alone a product leader’s role.

If you are familiar with business analysis or have ever been playing one such IT Business Analyst’s role at a large IT / ITES org. you’d surely know the importance of diving into the “RESISTANCE TO CHANGE” documenting it as an integral part of that Change Management process. Fair enough, business analysts are people who are known / hired to drive change towards making things better & are expected to do so rather continuously. And that doesn’t sit well with the users owing to how even a small change could be perceived as a painful process leading to unending cycles learning / unlearning / relearning eventually triggering one of the oldest & primitive reactions linked to the tendency of us humans which is to stand up against & entirely oppose the change without paying any heed to whether or not the change would really benefit us. So, there’s always been a love-hate relationship between the users & those analysts.

But fast forward to today where AI products are taking the users by a storm given the shorter cadence of releases & the competition going neck-to-neck, the cruciality of measuring whether or not users are ready cannot be ignored. Also, given how AI products / features are just thrown out there in the open bearing those fancy colorful labels that go “Hey! Try me for FREE TODAY”, something of an assessment to analyze the readiness of the users to adapt does make a lot of sense, serving product teams with the much-needed clarity not just from the standpoint of blockers but also the effort those CS teams would have to put in towards improving sign-ups / conversions.

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Gauging Users with a Readiness Scorecard

A readiness scorecard is a progress report highlighting the overall acceptance levels of the users in adopting to a new piece of technology, segmenting it over multiple headers right from their mindset, skill levels, intensity of training needed & the ease of use.

NOTE: Color coding is strongly recommended towards representing the sum of the parts, highlighting the criticality of each & every aspect intern contributing to the overall score.

Let’s dive into the sections & each of the parameters that go into the scorecard.

Scorecard - The Elements:

1) Awareness Levels

The collective awareness levels the users have over a given domain or a problem & their percept in which technology is employed to solve those problems does make a huge difference in their adoption patterns.

For instance: It’d be a hard nut to crack if you have to push the advanced AI features of Canva on to someone who has been designing in CorelDraw around 2 decades back as there’s a good chance that they may be unaware of their capabilities (rather rare you’d think given today’s timeline but still very possible).

So, some parameters that you should be measuring here are:

• Understanding of the new feature/product

• Gravitation of the change

• Perception of the benefits specific to their case

• Perception of the overall value the feature would add

• Inquisitiveness of the users

• Usage metrics during trials

2) Motivation Levels

The actual reason, the main central motivation that drives the users towards thinking beyond what they currently use could play a vital role in influencing the end decision to adopt to anything new, more so if that motivation is innate & doesn’t stem from external factors / decisions.

For instance: It could be a cakewalk to introduce & onboard users on to a tool like SketchWow from those traditional PPTs & slides given how the former does a neat job of visually uplifting the content.

Gauging a few of these can certainly help establish the motivation:

• Users are comfortable with changes in workflow

• Users exhibit low anxiety about new tools

• Past change experiences in the org were smooth

• The feature solves a real user pain point

• Users perceive urgency or value in changing now

• Drop-off rates have been low during onboarding

• Adoption is not entirely mooted by stakeholders

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3) Complexity & Skill Levels

When some products / features could bear some degree of complexity given the nature of their workflow, there is no denying the fact that using some of them do demand users to gain a certain skill level before they hit a comfort zone in spite of being thoroughly aware of the value it can add.

For ex: Using a few of those products bearing robotic interfaces does demand substantial training before the users feel comfortable & use it regularly. And using it may not be as simple as what’s depicted over those video walkthroughs.

You ought to be able to tick these off at first:

• Users are able to learn the new feature quickly

• Prior experience with similar tools exists

• Users feel confident exploring new interfaces

• Users possess the technical skills required to operate

• Time required to adopt feels reasonable

4) Resistance Levels

The resistance of the users to adopt a newer way of work or a new solution could bring out all their insecurities given how it could involve a significant learning curve & a cycle time. But even otherwise the resistance from the users could be pretty stiff sometimes making it a hard nut to crack.

For ex: Users who are using the simple calculator application on their machines could resist the move strongly if the solution team tries to remove the access to the application in spite of automating it towards making it easier.

Making these checks are thoroughly recommended:

• Users believe benefits outweigh the learning effort

• The feature clearly improves productivity

• Value proposition is obvious and compelling

• First-use experience offers quick wins

• UI/UX is intuitive and easy to use

• Error rates / frustration are low

5) Confidence Levels

Building solutions, launching features / products seamlessly could be a cakewalk for most teams & although they tend to do it like clockwork, the confidence the users have in the solution being shipped does make a world of a difference as that could eventually be the reason it sticks or falls apart.

For ex: With AI tools rampant as of today although an org. would want to make headwinds in incorporating the new tech, the users could be gripped with fear given how they may feel like they are stepping into totally alien territory.

You could run these checks to gauge the confidence of the users:

• Users trust the product/brand

• Users don’t feel any insecurity

• Product reliability is high historically

• New feature fits into existing workflow

• Integrates well with the other tools

• Training resources are available and accessible

• Onboarding flows and documentation are strong

• Users have been given time to adapt

• Reduces friction instead of adding to it

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Score Card - Sense-making:

Each of those pointers mentioned across those five sections could be rated either via color coding or using a number scale like: [1 = Not Ready, 5 = Fully Ready] like shown below in the Article Assets section.

Making sense of the scorecard - although different orgs. could employ a varied level of stringency, it is highly recommended that you ensure a score above 80% if you are looking at a number scale, aggregating it like so:

• 4.0–5.0: 🚀 Fully Ready

• 3.0–3.9: 👍 Ready With Support

• 2.0–29: ⚠️ Needs Preparation

• < 2.0: ❌ Not Ready — Requires More Work…

And if you are looking at color-coding then ensure you get a minimum of 4 greens overall - preferably FULLY READY if not MANAGEABLE.

Article Assets:

1) Readiness Scorecard - ABSTRACT:

Now, a high-level view of such a scorecard could look like this:

2) Readiness Scorecard - DETAILED:

And a detailed / thoroughly segmented view of the scorecard ought to look something like this covering each & every of of those points exhaustively bearing a marking against each of them:

I’m sure you must have come across this as product managers. There are committees formed at some orgs. where any of the team members (& not necessarily PMs) can submit their ideas towards bettering the product / feature which is akin to dropping suggestions at a banking kiosk / an ATM. When that could work as a blessing in some cases given how the perspective of an onlooker could get factored in sans any bias, it could lead to more problems as one could bite off more than they can chew. And this trend seems to be rampant at some early stage startups where one could be short of ideas to progress - blame it on the lack of research / knowhow.

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Amongst PMs & strategic managers the ability to execute ideas by aligning teams seamlessly towards goals could be one of the most overlooked skill. Because on the flip side one may be dealing with tons of ideas without having a clue as to get to that goal.

Here’s the link to the original Facebook post from TPW’s.

What exactly is Idea Hoarding?

In some extreme cases people may lose sleep over collating ideas & waking up intermittently from their sleep to jot down an idea / crucial thought that struck them. Here are a few reasons why this happens:

Why is Idea Hoarding dangerous?

You may be right in thinking “what damage can a heap of ideas really do?”. It is just a thought after all. But, if you get into the mechanics of time & effort invested on generating those heaps of ideas that come with a success factor of a measly 10% one is surely starting at a major problem. Collating ideas either in an organized or disorganized fashion although is perceived to act in favor could turn into a huge disfavor when one tracks the productivity & progress. And of course, the mental clutter, overwhelming feeling & getting stuck in a rut that come with it could prove to be more than dangerous.

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“The world of an idea hoarder is absolutely terrific & perfect akin to a square peg in a square hole but sadly that’s miles away from the reality of the world”

Ideas tend to look amazing on paper or in just plain thought. But the hurdles one faces over breaking the final outcome into major / minor goals, building tangible action plans & executing them could be so gruesome that many may get stuck & just choose to hang their boots up, turn around & bolt, which is why it becomes all the more crucial to develop a thinking that’s centered around execution.

Strategies to overcome Idea Hoarding

When the problems around idea hoarding are very real, all may not be lost yet as there are many ways to overcome them. The one thing that splits the great from the ordinary is their immersive ability to analyze everything (especially ideas) from the standpoint of taking it to the market, to penetrate those segments targeting the right audience, get more closer to the real-world, hypothesize, talk to a few prospective users if need be, enumerate & analyze all those last-mile problems envisioning ways to overcome each of them.

So, let’s go stepwise here:

STEP 1: CENTRALIZED COLLATION

Idea curation could be a pretty tiresome process & social proof dictates that many have lost sleep over the exercise. The reason is there’s no single designated space where ideas strike people. The universal truth & also a belief that’s largely true is – the best ideas strike you in the loo. 😄 When there’s no denying that, the actual truth is the best of ideas strike you when you are at peace & that would mean both physical & mental peace.

The first step is as simple as curating the ideas, putting them all at one place. You’d do well to organize them as well. Map them like a SEMANTIC NET & that could also help you structure nuanced thoughts around those ideas pretty well.

To make it more meaningful you could use color & size to distinguish / sort those ideas / thoughts in order of significance. FYI, I have used the following color coding for my work:

• GREEN – HIGH SIGNIFICANCE – Good to Go

• ORANGE – MEDIUM SIGNIFICANCE – Needs refining, should be relooked into

• YELLOW – LOW SIGNIFICANCE – Can be skipped for now

STEP 2: IMMERSIVE RESEARCH

You would agree with this all the more if you have the ability to generate ideas seamlessly. If your ideas look like “yesterday’s news” it is because you aren’t the only one ideating over a certain market space. There’s a good chance that those so-called brilliant ideas you have today may have crossed someone else’s minds quite some time ago, which is where research ought to come in.

Good research could be dampening for you when you realize that it has already been taken but that could also save you thousands of dollars given the eye opener it would turn out to be.

Click here to read more about IMMERSION

It is not that you can’t build an org. / a successful business if you happen to be a late entrant. It is just that your research ought to span all those quadrants, get the right kind of inputs towards helping you curate something that can resonate with the markets TODAY.

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STEP 3: RELEVANCE MAPPING

Not all ideas could work out well for a given situation, in fact if you have any experience generating ideas for products / features you would agree with me when I say most of them ideas could end up looking like randomly sprayed spots of paint of varied sizes on a brick wall. Sorting them based on the relevance & what matters right now could help clear a lot of clutter & get more objective lending more semblance to the whole idea generation exercise.

Also, remember ideas have stages, stubs & parts, a whole lifecycle.

[Check the SUGGESTED READING section at the end of this article]

Mapping the ideas based on the relevance to the current market scenario / trends could be done over multiple methods but it is imperative that all those methods involve the future users of the product in question. Although most resort to some sort of brainstorming done across stages so as to sort, re-sort cyclically until they believe that ideas are totally refined & are good to go, there’s a lot of semblance the opinions of the users could add to this exercise. All one needs to do is ask them the right questions or at times merely observing them could do a huge favor.

STEP 4: EXECUTION STAGES

Down to the last step which is also the very stub of this article. All ideas look good on paper but the execution is when most realize that they were hinging on a dummy or hit a realization that their ideas were totally outlandish. For instance: the one easy solution for traffic today in most urban jungles is to airlift people & drop them at their destinations – something like an air taxi. Some cities have already tried this on a small experimental scale. But, when that scores highly on DESIRABILITY, the VIABILITY may run into a wall when the FEASIBILITY could be practically inexistent as for most cities.

There are ample tools that you could use to span & test the depth of your ideas. One such tool that I have relied on extensively & advocated is the Business Case Canvas by Alex Osterwalder.

The canvas is surely a great place for people / teams who are actively taking part in strategy to get their heads down & analyze each & every aspect of execution right from the value the product would add to more practical aspects like the partnerships & resources that would be needed to the customer segments, the pricing models & the revenue streams.

Suggested reading:

• Is Your Idea Strong Enough

  https://theproductweb.substack.com/p/is-your-idea-strong-enough

• Catch-22

  https://theproductweb.substack.com/p/catch-22

• Ideating Within Scope

  https://theproductweb.substack.com/p/how-does-one-ideate-within-scope

• Lifecycle of an Idea - PART 1

  https://theproductweb.substack.com/p/lifecycle-of-an-idea-part-i

• Lifecycle of an Idea - PART 1

  https://theproductweb.substack.com/p/lifecycle-of-an-idea-part-ii

I am sure you have come across this question (or something similar). Having been forced to make a choice by clicking on one of those options towards proceeding with the normal usage of a tool would have been quite a frustrating experience & some who have had coding experience might have gone with - “Damn the modal dialog box man!”.

Marketing has more to do with the emotions than anything else. Which is also why asking people about the most recent AD makes a lot of sense.

Emotions merely are a response-to-stimuli, a result / an aftermath of some action(s) & if one happens to deep-dive into the nitty-gritty of those emotions one’d learn that there’s just so much more to it than meets the eye, all of it happening in a fraction of a second, aggregated to influence the decision in the end.

User behavior is everything in product & one may never be able to master the art / craft of building great products if one happens to factor a part of it in, let alone turning a blind eye to it entirely. The pain is real when teams design features / craft marketing campaigns / build products based on what they perceive as “valuable insight” only to posthumously blame it on “poor research”.

There are 2 main problems that arise with a research method like surveys:

1) - The Authenticity of responses & 

2) - The lack of depth in exploring, capturing those nuances of problems

It’d be great if we can spend time literally wiring the brains of the users towards helping build a core understanding of how they tend to function, what they accept / reject & why, steering clear of all the cognitive biases.

But “is that even possible?” is the question!!

Well. Turns out there is a way.

Neuroscience segregates the response-to-stimuli as pertaining to the CNS (Central Nervous System) & suggests the use of a few techniques that can help break it down & decipher how those reactions get triggered in the first place, arming teams with precision accurate insight. That’s the specialty of Neuromarketing – relatively a newer term to most although it happens to be 2 decades old.

Sounds complicated, but it isn’t in reality.

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Neuromarketing

1.1) The Concept

Neuromarketing is the selective application of principles / techniques of neuroscience towards researching & identifying the best of marketing strategies. It starts off with establishing consumer behavior by studying brain activity, mapping physiological responses to subconscious decision-making processes & could be effectively employed to optimize marketing campaigns. This could be achieved via various techniques some basic, some advanced & more sophisticated.

1.1.1) BASIC METHODS:

• Eyeball Tracking

  The practice of keeping a tab on the user’s eyes, tracking them constantly as they are looking at a particular product / a page, it could convey a lot about their interests

• Color Psychology

  Usage of colors across multiple instances (run like A /B Tests) towards helping identify an optimal color coding that resonates with the audience & proves to be a winning combination

1.1.2) ADVANCED METHODS:

• EEG (Electroencephalogram)

  Advanced method that physically wires an incumbent towards mapping their brain signals & deciphering how they make choices under various circumstances right from absolute clarity to total chaos

• fMRI (Functional Magnetic Resonance Imaging)

  Uses a special version of the MRI machine to track subtle changes in the blood flow of the incumbent & one also measures the blood-oxygen levels towards gauging responses to certain stimuli

• MEG (Magnetic Electroencephalogram)

  Measures the changes in the magnetic field arising out of the electrical activity undertaken in the brain

1.2) Applications of Neuromarketing

Neuromarketing has seen a widespread application across many areas beyond traditional product marketing. Some of the popular ones being:

1.2.1) Research: Alongside traditional research techniques neuromarketing could be employed to effectively unlock those main drivers that aid the decision-making process subconsciously

1.2.2) Copywriting: Identifying language patterns, pinning on emotional triggers, crafting high top tier narratives & using a brand of persuasive messaging does have a higher probability of resonating with the audiences

1.2.3) Branding: Effort put in towards analyzing the associations audiences exhibit with visual elements like logos / taglines help foster a stronger brand image

1.2.4) Logo: Evaluating the response to the typography - font color, layout, formatting, size, shape & how they combine with the other design elements would be a great way to ensure better resonance

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1.2.5) Digital Marketing: Studying data & analyzing patterns in the reactions, choices, responses to posts, campaigns, advertisements, CTAs & the other UI elements towards crafting specifically targeted strategies

1.2.6) Product Design: Understanding & deeply assessing the workflows would lead to a better knowledge of the user’s preferences which could then aid the whole design process

1.2.7) Sensory Elements: Studying responses various shapes, colors & materials towards ensuring the packaging appeals to buyers at a subconscious level whilst also ticking off the ergonomics would lead to an unparalleled appeal both visual & physical

1.2.8) UX Design: Factoring the preferences of the users towards designing intuitive & satisfying interactions & user flows whilst also designing a few visual experiments towards gauging their appeal / satisfaction getting into the nitty-gritty of the design & UX/UI elements

1.3) The AI Era

Traditionally the research set-up required the presence of a volunteer whose consent was obtained prior & was physically wired for an average of 30 minutes towards studying those electromagnetic signals emitted from their brains. And that did work like a Godsend for physical products (like for instance: Coca Cola used it to gauge reactions towards the bottle shape, size etc.). But how easy would that be when it is an internet product & your user is someone from a distant geography, miles away?

That’s where the AI & its algorithmic power kicks in. The whole complication of data collation, analysis & inference could be automated making it look like a cakewalk. Be it the implementation of techniques like Brainwave activity & imaging, Eyeball tracking, Facial coding, Physiological responses like Galvanic Skin Response (GSR) for instance, Heart-rate monitoring, Biometrics via cameras & other physical devices (wearables) towards monitoring the users tapping into reactions, all done without breaking into sweat - with their consent of course.

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“The best part about AI & its application in Neuromarketing is how every bit of insight is direct & tied to the major / minor metrics, which also means doing away with questions that force the users to put their feelings / emotions into words, like: [How did this (x, y, z) make you feel?] for instance”

NOTE: GSR would need a special kind of a device & although unavailable right now across the best of wearable devices inclusive Apple, Samsung, it could be a thing of the future.

1.4) Key Applications of AI + Neuromarketing

1.4.1) Sentiment Analysis: With the effective use of Natural Language Processing (NLP) one could analyze a lot about the sentiments of users towards a product, be it the recognition of common patterns pertaining to emotions or the use of some strong / coarse language over the social media comments, all of them can be seamlessly factored in with AI.

1.4.2) Emotional analysis: One of the most underrated & overlooked elements of behavioral research is the emotions that users go through, be it their subtle reactions, change of expressions tapping into facial recognition & the effective use of biometric data blended with AI could prove to be a Godsend in terms of arriving at the emotional state of the user as pertaining to some stimuli.

1.4.3) Intuitive analysis: AI makes predicting the likes / dislikes of a user / user group by studying their subconscious states vide asking a few relevant questions & analyzing their reactions. What used to be a laborious process that took weeks can now be achieved in a matter of minutes.

1.4.4) Awareness analysis: Bringing up a few elements on screen & asking the user to respond would be a great way to gauge their level of awareness over a given domain / subdomain / a niche topic & AI makes all of that possible vide designing campaigns / questionnaire that feels more real given the effective utilization of the HCI (Human Computer Interface).

1.4.5) Responsiveness: The user’s attention to detail would be a correlative of their emotional involvement & with the effective use of AI tools one could automatically measure the elements that capture their interest, narrowing it down to some specific element / graphic on screen present it on a dashboard for the benefit of the teams.

1.4.6) Aggregation: Sophistication in AI tools could help future users pick & choose the most significant elements that they think matter to them & feed it to the machine towards helping arrive at how & why users made those decisions, which could then serve as perfect input to the marketing teams towards optimizing their content.

Also, supposing there was an org. holding monopoly today (some examples listed hereunder), the period they tend to stay on in that pole position seems to have witnessed a major drop as well.

Consider an org. like Alibaba. Although known to be giant online retailer they have witnessed a radical shift if you consider a few ASPAC nations owing to how some local players were quick to envision & build something of an alternative to it. And that seems to have kicked off a major wave of adoption locally, when whether they are better or not in comparison to the ones who started off first & had a first-mover-advantage is a debate for another day.

But the bottom line is that competition somewhere rubs off into a healthy rivalry forcing orgs to invest, envision, innovate & lead towards a better future both from the user’s & their own standpoints. When a world without competition is imaginary / utopian, there could be no doubt that the strategic moves of one such org. that is actively a part of the competition does something extravagant towards gaining market share, much like the Prisoner’s Dilemma.

The Concept:

Prisoner’s dilemma stems as a classic application of Game Theory in Operations Research. It talks of 2 subjects being arrested for a crime, interrogated in seclusion, having no means whatsoever to communicate with each other. So, they have 2 choices broadly. They can either choose to:

1. Don’t testify, keep silent (OR)

2. Betray the other by testifying

The consequence of which would be:

1. Both of them get convicted with short sentences (OR)

2. One of them leaves scot-free (OR)

3. Both of them get convicted with a moderate - long sentence depending on the level of offence

So, the rationale behind each of them prisoner’s thoughts would be:

1. If one of them prisoners chooses to keep silent, then the other choosing to betray would lead to freedom for one – OPTIMAL (best for one)

2. If both of them betray, they both attract a moderate – long sentence – SUBOPTIMAL (worst for both & best for none)

Given this scenario it would be best for the prisoners to assume that the other may have betrayed & plan their future course of action accordingly.

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The Applications

The Prisoner’s Dilemma finds widespread application even to date & that isn’t limited to Technology alone. There are multiple other teams this could apply to, underlining the need for leaders to be aware, cautious & mentor teams steering them towards alignment & ensuring they are getting the best outcomes out of them at all times.

1.0 - Technology & AI Adoption

It is a creator’s market out there today as is evident from the vast majority of them who have made a unique name for themselves. And the availability & accessibility of such Tech tools (specially AI-based) don’t seem to have any kind of dearth. When there is undoubtedly a huge value addition to the productivity of the teams, there is a downside risk as well & the prisoner’s dilemma could kick in sabotaging efforts & straying teams away from the final outcomes if they aren’t monitored & mentored rightly.

1.1 - Onboarding Strategy:

Many product orgs operating specifically in the technology infrastructure vertical could face this dilemma on an ongoing basis. Given the pace of technology advancements & everlasting need for better computing power the PaaS, iPaaS orgs. could find themselves caught up with 2 choices broadly:

• To be early adopters & march ahead with the upgrade

  (OR)

• To wait, watch & plan the future course based on the others in the market

1.2 - Rollout Strategy:

Development efforts may get bridled at times puncturing the motivation of the tech teams when the rollout strategies could get dictated by some external factors that bear a strong influence. Getting caught with the “rollout whatever possible but make it quick” gunning for the first-mover advantage irrespective of how brief that could be does come at a pretty steep cost as one may be foregoing crucial cycles of testing, feedback, mending / repairing, course correcting the product / feature.

There are a few biases & loopholes one may be overlooking if they are gripped by fear of the advantage a competitor would gain.

1.3 - Innovation:

There’s no org. that wants to be left behind in the race, which is why they develop strategies oriented towards innovation & also invest heavily in latest tech like Artificial Intelligence (AI). But that’s also where the prisoner’s dilemma could kick in. Only if aggressive spending can ensure revenues & profit margins but alas, that’s not the case at all. Giving in & blindly jumping into such a fire could easily mark one up for failure.

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2.0 - Marketing

When the question “do I have to invest in marketing?” seems really spurious today, making one almost sound like a caveman, the question “how much more do I have to put into marketing?” seems relevant for ages to come. It’s the theory of relativity all over again. If one of the competitors is pouring truckloads of money into marketing, the others would never be comfortable sitting it out. The Prisoner’s dilemma would kick in & disrupt the thinking more so common across oligopolies where an org’s strategy tends to negatively impact its rivals.

2.1 - Marketing & Content Strategy:

The richness & relevance of the content is paramount given the way marketing works & teams tend to channelize those efforts. When the whole idea is to leave a mark in the audience’s minds, that could obviously affect the content strategy as well. One of the orgs. investing heavily on research & deciphering a particular route / earmarking a given channel as default, triggering reflexive reactions amongst other market players is not alien at all & stands as a classic example of the prisoner’s dilemma.

2.2 - Ensuing Price Wars:

There are many instances of rival orgs offering almost similar if not the exact same product. Given such a scenario they all need to come to some sort of an understanding / an agreement / some regulation (I know some of you may be surprised here) around pricing their prime products towards creating healthy market conditions for all. Having said that every org. could have their own way around incentivizing the purchases so as to create a drag & if all of them decide to cut prices the suffering could be inevitable for all.

2.3 - Marketing Budgets:

Looking at a campaign it doesn’t take much for someone with marketing experience to decode the $ expenses they may have incurred. Most prices are transparent today & that adds to the accuracy of budgeting as well. The prisoner’s dilemma affects orgs. here in terms of estimating the other’s measures vis-à-vis their success. If one of them has shown an increase in marketing spend, one could be absolutely sure that the others may just follow suit, which may also lead to canceling out each other’s efforts if one isn’t playing their cards right.

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The Escape Route(s)

When most orgs. tend to follow suit giving in to the prisoner’s dilemma here are a few to combat it.

1. Bat for Differentiation

Focusing & channelizing product development efforts towards building something unique that not just solves a problem but also entices them & sticks with the users via better UX, better quality does go a long way in adoption. Remember, that’s what one ought to be after sans any compromise whatsoever. And the one thing that always manages to attract the users is the value & when that could be tied to the price as well, there’s more than one instance where a higher price for great products are justified.

So, asking oneself / the teams the value addition incorporating a new technology would bring or how a certain marketing spend is justified ought to be a good start towards keeping the prisoner’s dilemma at bay.

2. Find Strategic Alignment

Good leaders know how to use narratives to align all internal teams with KPIs and finding harmony via that route ought to be paramount. Encouraging teams to understand & live by those shared goals, adhere to a collaborative culture that hinges on proactive communication, brainstorming towards eliminating ambiguity & getting more objective does provide those necessary safety nets to stop an org. from falling trap to the prisoner’s dilemma.

The answer to the question – “Are all the internal teams aligned over how we plan to channelize our efforts & take the feature(s) / the product ahead given the current scheme of things without worrying about where we stand vis-à-vis the competition?” although looks pretty simple could run into a few complications given how it may not be a one-time affair. The cadence of the question is as important as a positive & favorable answer.

3. Be The Fast Follower

Although it is possible that an org. is lagging the competition in terms of marketing efforts / the onboarding of a new piece of software / some cutting-edge technology, it could still make a lot of sense if one is already sorted over a strategy, as in if that’s a part of a larger plan or a structured roadmap. Remember, everyone could have a share of the market which is all the more true of oligopolies. So, the strategic direction that the competition is getting into may not necessarily be fool-proof when it comes to scoring high on growth numbers. And of course, keep an eye on the competition you must.

Reassessing those strategic moves of the competition towards understanding & comprehensively mapping out their potential ought to be imperative, which could be as simple as finding the answer to a question like “What would be our growth projections if we were to follow suit but strategically oriented towards some crucial initiative (A)?”.

Backstory:

Consulting with a bunch of leaders & the cofounder of a startup not too long ago, I was hit up with a problem that’s not unique in any sense of the word. Over one of the conversations the cofounder opened with:

“We seem to have everything in order but never seem to hit that peak when it comes to execution. That’s something deeply worrying for me as a cofounder & multiple attempts to combat it have turned out to be futile. Not sure where we are going wrong though!”

A classic case for a consultant, you would think. 

But let me tell you that the problems either directly or indirectly linked to strategy formulation across any domain could be much easier to solve than the kind described here. 
IME, these are laborious & come with a daunting lead time. It could suck up weeks of time before one can ascend the 1st STEP of solutioning & building those action items. The number of interviews a consultant would have to sift through in this scenario is likely to see an astronomical rise & playing hide-and-seek with the stakeholders over slot-availability is very likely.

With AI taking driver’s seat cutting down TAT (Turn Around Time) by a whopping 75+% solving many tactical problems like engineering, design & the related whilst slowly stepping into the strategic sphere as well, one may think that the major issues faced by teams may not have anything at all to do with execution. But, that’s far from the truth really. With disruption rampant & tech adoption becoming more of a mandate than a choice the challenges just seem to have jumped a few quadrants.

The major worries almost a decade back were:

1. What should the architecture look like?

2. What are my choices of platforms / languages / tech stack?

3. What other tools should I employ?

As opposed to the execution teams being faced up with one major worry today:

• How do I integrate this into my workflow?

The major areas of risk have undergone a paradigm shift. But that doesn’t mean today’s teams are operating sans any sort of risk. There are risks & some are critical demanding immediate attention.

Here are 3 major risks product teams ought to be battling out in 2025 & beyond:

RISK 1: TECH OVER-RELIANCE

Over reliance on anything is bad as we already know it. Then how is the over reliance on AI even justified?

On the same lines: https://www.facebook.com/share/p/1AZ4wt7Bib/

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Relying too much on AI to solve every problem could prove to be more of a curse than a blessing. If one already knows how these LLMs function, they’d also be aware of its limitations & know where to draw the line. But psychologically, the virality & outreach of the technology, the popularity given by the adoption numbers & most important of all - the dopamine (the feel-good-factor) seems to sweep many off their feet as they then begin to hinge of AI for everything under the sun. [It may not be long before they stop thinking entirely].

I’d like to term it THE DISRUPTION BIAS because the first thing one thinks of is to come up with the best prompt to feed to their favorite LLM. And, that’s also where their thinking seems to hit an end.

The results AI is dishing out ought to be taken with a grain of salt especially when the query has anything to do with strategy.

Imagine someone asking AI something like, “best investment strategy for windfall gains in the upcoming quarter”. Scary!

One could ask AI for “best market for a product targeting obesity”. And the result would be a few great options ranked in descending order saving one hours of research.

When the former has too many variables that could change dynamically making it practically impossible to get a right answer one ought to understand that AI relies heavily on market voices & transcripts already available in the form of news articles or opinions (a select few of them being proprietary) influencing the end result, the latter is merely a report extraction exercise aggregating numbers furnished by proprietary sources.

Some deterrents to emphasize on:

• Have we spent enough time discussing the problem(s) this week / over a given cadence of meetings?

  • Underlines the importance of teams spending time brainstorming real-world situations, events, pain points, problems

• How would we solve this problem supposing we didn’t have any AI around us?

  • Ensures ideation & encourages natural free-flowing thoughts directed at the problems with a focus on user empathy, user needs & conceptualization

• How many times has AI / AI tools crept into strategic discussions this week?

  • Shows that AI tools haven’t interrupted the strategic discussions

NOTE: Question (3) would be applicable to some extreme cases where teams just don’t seem to think beyond AI, not that they can’t / they aren’t capable in any sense of the word.

RISK 2: INTERNAL MISALIGNMENT

Team alignment is a problem for sure as it could be natural for people coming from diverse backgrounds with different experiences to possess varied beliefs that they would prefer sticking to rather aggressively some times. It is common for team members to run into clashes on ideologies & egos, which is largely tackled. But lack of alignment between the teams, people turning a blind eye to the meaning of the phrase “team” operating in silos like they’re on their own showing no sense of collaboration happens to be a bigger problem. And lack of alignment stemming from Tech or the lack of awareness of it is a major risk in today’s scenario.

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Think about it. When sales seem to be driven entirely by the number-game ($ Revenues) & the viewership game (# Impressions) motivating the marketing unit the narrative would obviously be set towards those specific quadrants. Squabbling endlessly over what’s right could seem like it is the order of the day. Alignment would be a pretty far-fetched idea, let alone, user empathy, focusing on the most significant problems & build the right stuff.

There’s a reason why someone created a function like product management & defined its purpose largely around orchestrating all the other functions & driving stakeholders, teams alike towards those outcomes, meticulously planning & lending their oversight towards helping the teams take baby steps aggregating them towards achieving those goals. And the manner in which product management seems to have evolved over the years stands testimony to its cruciality, its importance, its value.

Yes, building stuff is a cakewalk today, thanks to the AI tools moving designers / developers away from their actual strengths vide prompt engineering, vibe coding, web designing, user flow automation. That’s all the more reason for major stakeholders / managers to circle around & voluntarily call out to the others, running their thoughts towards checking (cross-checking if need be) for alignment across the problem & its annals, the solution & its parts periodically. It’s more like a driver looking at the map intermittently so that he doesn’t stray away from the end goal & can make quick & fine adjustments towards getting back on track if he’s led astray.

There’s an absolute dire need to push each & every team member in any org. irrespective of hierarchy towards learning (not mastering) disruptive technology, the capabilities of AI & what the future holds.

That way, those assumptions can be done away with & even the ones who aren’t hands-on with technology everyday can perceive the scope, the capability of the Tech, its application befitting their situation & of course its limitations. That’s the major & evident gap between leaders, management & the other team members & also the alignment most orgs could do with as of today.

Some deterrents to emphasize on:

• How many of our managers / leaders are using AI tools & can go beyond listing out its capabilities, limitations?

  • Ensures almost equal (if not equal) understanding of the Tech

• Are our sales, marketing, support teams trained on basics of AI?

  • Makes a strong case for that much-needed alignment as of today

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RISK 3: STRATEGIC INCONSISTENCY

Poor road-mapping happens due to lack of immersion over the research, earmarking problems that may give out the “humungous” vibe but sit poorly with the target markets, pursuing areas that seem good on paper but score pretty low when it comes to sustained growth potential over the longer-term. Also, the debate between do we think of the long term or focus on now adds more fuel to the fire.

Blame it on the oscillating focus between the long & the short terms, questions like which route should we take, should we shelve or forego the most evident one now towards pulling something magnanimous in the long-term? What should it be?

Building a winning feature & then going off the grid, blanking out entirely or dishing out features that don’t resonate with the market at all seems like a dire string of events that are typical of a madman’s diary. But you would be amazed at the no. of times this has happened in the recent past as much as it continues to happen as we speak now.

AI is evolving as we speak. And it stands proven that one ought to be able to factor the value addition it could add, earmark areas of application & use it wisely towards building the best experiences for the users. That’s the key.

The statement “AI will help us grow” is like saying “A website will help us grow”. There’s some truth in both those statements alright, but that’s not the sole truth as there’s so much hidden beneath that surface. “How you leverage the tech & what you come up with it?” are much more important questions to address. The usage / the application ought to be relative to the need & not driven by any other external factor whatsoever & especially a big NO if that’s driven by FOMO.

Some important deterrents to implement:

• Are the adoption patterns of recent rollouts hinting at a drop if there’s no AI implemented?

  • Clears up the air on where the market stands on the inclusion of AI

• Is the inclusion of AI really adding value to the users?

  • The metrics clearly help emphasize the value addition to the users

Talk of old times, there are a few adverts that have stuck with you all throughout those decades as they continue to. Although each could have their own reasons for that, some of the common ones are:

• Impeccable copies – some of those lines the copywriters have used are still stuck in our heads

• Personality – the towering presence of a pretty famous / well-known celebrity

• Location – the spot / location of the Ad-shoot which then takes its name after the brand & the Ad

Here’s a bit of nostalgia for my readers from the Indian origin. Wherever you are in whatever corner of the world, there’s no way you can deny the knowledge of these. Just one look at each of those images in the collage & you would have no trouble recollecting the brands, be it the girl dancing her way into the ground from the podium with that chocolate bar in her hand or the guy using super-glue to catch fish surprising the other guy who is using a conventional fishing rod set up.

It surely is aggrandization alright as for the narrative in most cases. But then, one ought to give in & just accept the fact that they have occupied a certain corner in our brain managing to stick on for all these years when some of those brands / products have become synonymous to the functional area they serve. I am sure you would agree that growing up there was a time when you wanted some gum for that crafts project at school, walked up to the store & asked for FEVICOL rather than GUM.

But marketing itself has come a long way today & is much more evolved in comparison to that. And changing times have brought about a lot of changes in the way we go about things whilst also inducing a lot of newer methods, techniques & terminologies that are proven to be super-effective. Today, as we speak, things are getting more subjective, channelized & although one is looking at market as a whole one is also looking to zone-in, segregate, segment the market suitably at the same time so as to craft specific strategies that help resonate with the audience in the first place, then penetrate leaving a lasting impression thereof – the term for which is PERSONALIZATION. And albeit in a similar vein, personalization applied in the B2B context could be termed ABM (Account Based Marketing).

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And a methodology that has gained prominence & is worth a mention here is F.I.R.E.

The acronym F.I.R.E stands for FIT, INTENT, RECENCY, ENGAGEMENT which are also the main pillars of account-based marketing (ABM) that help prioritize & target those right accounts. Right accounts in this context means the accounts that are prime & exhibit a higher likelihood of conversion. After all nobody wants to be shooting in the dark, do they? And more so, when the average cycle time in B2B could run for a few odd months.

1. F - FIT

The process here usually starts off with an evaluation of how well a given account matches the ICP (ideal customer profile) & it ought to tick these 3 major boxes:

Someone would click BUY & will be willing to purchase something ONLY if they can clearly establish a need although some of those needs could be tied to extravagant factors at times (for instance: FOMO – as in, my friend has that pair of sneakers but I don’t, so I ought to get one). But, having said that, products or services ought to stick in the heads of that sample space representative of the immediate target market in particular for which one needs to leverage that content strategy well ensuring they strike some degree of harmony to begin with & subsequently rely on repetition towards making some room thereof.

So, as for ABM the targeting process would involve scanning through companies & being able to profile them well based on a few important criteria, some of which could be:

• Company Size – the number of employees in account, as this would help determine basic things like contract size & term which could lead to more clarity on the efforts needed towards enablement across the journey, like for instance: maintenance

• Business Vertical – the nature of business(es) they are into could hint a lot at their requirements & also their usage patterns

• Geography – with the strategic location of the country one could draw a lot of parallel & derive insights from the other accounts that are being served already

• Point of Contact – the person in-charge, their profile & other important details like say interests, passion, behavior if factored in could help in formulating relevant content strategies that not just resonate but stay on for long

• Employees – the average employee profile although the standard deviation could be significantly large here would help niche-in & build use cases that are specific to problems typical of a given team

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2. I - Intent

Getting your hands dirty with charting out those customer journey maps to measure the degree of active interest partaken by a given org. in your product or service category goes a long way in defining the trajectory of success your org. in general & your sales teams in particular would experience. And that could be down to any of these:

The one metric that uniquely & unambiguously defines your success ought to a great place to start. Not necessarily website / landing page visits are bad as some consider them to be as the perception that one could land on a given page & still drop off from there isn’t altogether false. Although many would pin on vanity metrics like impressions / views / downloads (like say: prospectus / brochures) that could be good enough to represent some kind of an initial traction but may not prove to be quite enough to qualify as an ultimate success factor.

Talking of the ABM parlance, it is possible that many members from a variety of teams click on something they think is great when they are actively researching or looking for some solutions to their problems. But to be able to zero in on & qualify an action as a valid buying signal one could track & measure all of these:

• Strategic Triggers – An org. putting out a strategic announcement about their investments into a certain area like say, disruptive technology / AI or nanotechnology could be a great trigger & although meant to be an early signal it does help establish intent unambiguously

• Event Participation – The number of employees signing up for an upcoming event like say a Tech summit or a seminar could lend enough insight into what an org. perceives as important

• Content Engagement – Straightforward as it is, the inclination one shows towards a certain type of content when clubbed with the demographic data over the B2B sample space could not just lead to establishing interest but also indicate the depth of inclusion as well

• E-mail Trails – Oldest but still very effective, the tracking of the chain of emails sent & the turn of events post that [opened & CTA, opened & deleted, deleted without opening] could lead to ranking in order of interest, also a short survey questionnaire to gauge a thing or two about them shouldn’t be overlooked

3. R – Recency

The time one takes to act could largely vary & more so when the average cycle time to a sale is significantly large, which is why it could be great to pin on the time elapsed since the most recent interaction with a certain account & that could be done across these contingents:

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Face it. The nearer one is towards the bottom of that funnel, the increased likelihood of them falling through & that’s also where pipeline enablement strategies could come in handy. When the cycle time swells there could be significant doubts over the interest levels / intent unless that happens to be very recent. The place where most teams / orgs lose out on is when they choose to stay put post evincing a favorable action or manage to establish that initial wave of interest. That ought to be a change to engage a little more with those prospects, hand them a few more pieces of information as relevant to the problems they are facing, which could help them put it all together & finish the puzzle so to speak.

They may not have given the final go-ahead & it could be far away from closure but that doesn’t mean it is all over. They could still be in the right headspace to engage & that ought to be enough to push more relevant material, talk to them if need be, understand a thing or two about their challenges & how the space has changed over time.

As for ABM, the crucial role recency plays could be underlined over these headers:

• In-market – Represents the audience that are already in the market, looking around, viewing, actively comparing products / services online, talking to a host of them would then lead to building something of a priority list

• Affinity lists – Being active & finding a place in those affinity lists the accounts although share common interest may still be at different stages in the buying journey, documenting & updating which does decide their further course of engagement

• Remarketing – Marking up a set of accounts for remarketing would simply mean the proven need for a solution alright but also a given blocker needing attention as it could be pretty crucial for further progress thereof

4. E – Engagement

The depth and breadth of the interaction & engagement varied groups of employees from any given account exhibit with your brand across channels could unanimously prove to be symbolic of their inclination to buy, with the probability largely proportional to their hierarchical position, measuring which is down to analyzing:

The likelihood of conversions may be higher if it happens to be a decision maker who is bestowed with enough power to steer the teams & call the shots, which is why most teams work their way by building different persona as the [USER PERSONA] could differ from the [BUYER PERSONA] over B2B. I’m sure you would agree that the benefits & endless results one could achieve by onboarding to an AI tool is more likely to entice an engineer or a designer when the Head of Design or the Software Engineering Manager or even the CTO would pay more heed to the ROI, Cost-Benefit Analysis, the Productivity bump they can witness over adopting the tool. It is the same product one is talking about here but still to each their own when it comes to gauging its benefits.

And here is how ABM turns the heat up on the engagement front:

• Bucketing Persona – Building detailed user & buyer profiles is where it ought to start from branching out into the value addition to the individual users as that’s what it could ultimately boil down to & could also transform into a web of influence

• Identifying Needs & Relevance – The one using the product would want to know the value addition in terms of it reducing the time cycles & making them more productive which is why factoring in the right set of needs & using that to build relevant content becomes quintessential which could then be floated across multiple channels

“Is product management art or science⁉️ “

Across the length & breadth of your experience I’m sure you have heard of opinions & perceptions that tend to bracket skills defaulting them as more suited to a profession / a given position in the organizational hierarchy. Like for instance:

• You seem to have a flair for people’s perceptions – psychology as a subject & marketing as a profession may work like a charm for you

• You can keep your nerves calm & are good at influencing, getting the best out of people – you will surely make a great manager someday

• Stripping off electronic devices to the components & plugging them back in flawlessly to get them to work just as is – Wow, that’s an engineer in the making there

• Wow, those are some amazing sketches I see there – you should take up arts as a subject & perhaps graphic designing as a profession

Not to forget the most cliched of them all, something that most of us may have heard right from our childhood:

• Oh, you’re good in MATH – so you ought to take up engineering

Are those opinions all wrong?

No, not entirely. But they could largely be cliched.

One possessing the flair of digesting tons of information pertaining to the opinions of people could lead to a certain degree of insight at the basic level. But whether that would make them impeccable at marketing is quite a debatable topic & also quite a one-sided opinion.

Being good in MATH is such an elementary skill that could really find a very widespread application & open up handsome avenues. Equating that directly to Engineering (although not altogether wrong) could feel like one is limiting their options there.

It’s all down to those perspectives as you might have taken notice. And, UX is really no different. The same things could apply there as well. When someone who is a designer could look at UX as an art it could really differ if that happens to be a product manager or a technical architect.

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Let’s break this down further considering the case of Video games.

For someone playing video games in the early 90s, they are already excited & the drive could be innate given the lack of choice back then. So, building a basic UX with the focus entirely on the rules of the game might have worked well, like for instance: Packman.

These were the first on the block, one of its kind pre-GUI games & they came at an era when the gaming scene was literally inexistent. The focus of the user was more on the outcome as they wanted to do anything & everything possible to finish those games gunning for a high scores & go on breaking those records for fun.

But the post Road Rash & NFS era beginning from the mid-90s which focused on improved graphics & a better playing experience towards revolutionizing the gaming scene in a great way almost shaping the current era of games. Am sure every gamer out there is thanking their heavens for this drift happened back then (provided they are aware of the evolution).

One’d think that era of simplicity is long gone given the gaming industry today in 2025 where the UX of the games have improved so drastically that one doesn’t just talk of a pretty rich gaming experience which seemed largely restricted to those plush arcades 2 decades back but also boasts of experiences that are almost life-like, when sometimes bordering surreal as well.

But then there are still some classic games like Sudoku or the classic Wordle that focus more on the game strategy itself, impeding players to find innovative ways to finish it & bag that win (although Microsoft Sudoku is an exception in this regard).

Notice what’s happening there. When some games seem totally inspired by a few real-life sporting events occurring across the world some others deal entirely with the mind. Although some may be led to believe that former ones are totally sophisticated & offer a rich gaming experience that’s just the part truth in reality.

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Springing back to our subject of product management, is gaming experience entirely different from UX (user experience)?

Well, yes. UX is more generic when gaming experience is more specific to artifacts of the game.

The goal underlining the gaming (specifically those 3D games that are more lifelike) is to offer a pretty immersive & emotionally connectable experience relaying the real-life events making it as real & life-like as possible with miniscule deviations from the thematic that it is based upon.

When UX could be representative of a much wider perspective taking into account the other aspects that are entirely away from the thematic & the actual gaming experience like say, saving a game & reloading it or the ease with which you can choose the characters / players / avatars & keep track of multiple elements over a multi-player mode. Gaming experience is very specific when the UX is more generic & also multivariate in nature.

In case you are still having some trouble with its perception you could think of UX as some specific element of a product that evokes a sense of satisfaction from the users for a start, slowly moving stage-wise towards getting them to fall in love with it & then getting them hooked gradually, leading to a sense of accomplishment over every single session of usage transforming into a degree of loyalty.

The multivariate nature stems from the perceptions themselves. The way a product person looks at UX could differ from the perception of someone who is contributing on the tactical side of things like say a designer.

There are 3 levels that one could look at UX broadly from.

1. STRATEGIC LEVEL

The strategic level although indirect could play a crucial role in defining the UX. How any given strategy goes on to influence those elements / variables that would then define the UX could prove to be seminal for any product’s success.

You start off by looking at the problem statement itself - that crisp definition of the problem as pertaining to a given customer segment & then branch into something more detailed like say conceptual design – the strategic process focused on the high-level design of a given product.

And this could be further broken down into 2 parts:

1.1 The PROBLEM:

At a high-level in defining the overall strategy & setting the product off on the right direction, the problem statement is what makes all the difference. Picking out the right problems to solve, defining them in a pretty crisp manner acts as the cornerstone & goes on to define a product’s success.

Look at the manner in which problem statements are defined & it shouldn’t take any experienced personnel to tie that down to how it would make a difference to the users & what kind of experiences ought to define the solution as well.

1.2 The SOLUTION:

Trickling down to the solutioning portions there are ample ways to solve a problem. It is a proven fact that time teams take to choose a solution is always higher than them coming up with the alternatives. Really, there’s solution bias to factor in & brainstorm over which one of the alternatives could prove to be the best amongst the lot. Also, what ought to matter is NOT what the team members think (although that’s where most would start off) but it ought to be down to user perception.

And there are many ways & means of getting there. Look around & you are sure to find tons of methodologies / process / frameworks that some seem to swear by as the gospel truth. Be it design thinking that enforces & cements a structured approach towards stitching a camaraderie enabling seamless collaboration or the conceptual design that lays out the ground rules for further tactical solutioning, it all boils down to offering the best UX to the users.

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2. TACTICAL LEVEL

An extension of the strategic phase is the manner in which the intricacies of the solution gets defined & that is working towards the tactical side of things. There are multiple ways to solve problems & also multiple ways to design those experiences.

Look at any given product & you’d see how there is an element that makes it look elegant whilst also making it absolutely easy to use / operate. They both ought to function in tandem because if it happens to be just either one of them at best, that would still be effort getting wasted.

2.1 The ART:

The way a product looks undeniably has an emotional connect with the users & is an imperative piece of the UX pie & that could be summed up as the Visual design, the top-most layer of the design pyramid.

When one talks about design the common perception immediately points towards the look & feel, all those UI elements & the way they are organized, the color quotient used, those landing pages & the engagement quotient of the content displayed there. Each one of those artistic elements (& a whole lot of them beyond the scope of this write-up) carry a certain degree of importance, ignoring which could compromise the experience.

2.2 The SCIENCE:

But what’s also imperative is how the solution is built, its dynamism, its robustness, how light-weight the whole solution design is makes a huge difference in the UX & intern plays its part in defining the adoption levels of the product. There was a time when users patiently waited for 30-odd seconds for the changes to occur on screen as a result of their (clicking) action. Today one talks of information being available in abundance & at their fingertips all in a click & a jiffy.

For that to happen, there’s a lot of elements deeply rooted in science, engineering that comes to the foray. Talking of the aspect of robustness the visual element / art is what’s visible to the naked eye but there are layers underneath like say, interaction design, architectural design elements, database design that makes it all possible.

Products ought to tick 2 main boxes, it ought to solve a problem primarily & ought to lead to a sense of excitement every time the users get on to use it. And that’s the bottom line.

3. FUNCTIONAL LEVEL:

There are multiple teams that ought to come together, collaborate & find quick fixes to problems both major & minor if the products were to achieve even a diminutive margin of success. The trajectory of growth would depend on how those teams tend to function, what they do with the understanding of the Goal, the Final Outcome, the OKRs (Objectives & Key Results), how they chart out action plans towards inching to that goal step-wise.

Talking of these teams (aka Functions from the org’s standpoint) they could include every single one of them right from the ones framing the ground rules of the strategy (like say: Product Leadership) right up to the ones who are paying heed to those minor problems of the users (like say: Customer Success), proactively working towards weeding them out so that users could derive more value. Not to forget, the constant effort to keep a sharp lookout for feedback, analyzing it & factoring it into the process towards adding more value to the users.

3.1 The BoFu:

Post-sales, the journey between the decision to BUY & the VALUE REALIZATION may not really be as smooth as one perceives it to be, in fact it could be fraught with multiple problems across the funnel. Also, the fact that not all users are at the same level of expertise ought to be etched in the backs of the CS teams, solutioning teams & also the ones who are into servicing the clients / users full-time. Such BoFu (Bottom of the Funnel) blockers are a big NO-NO when one is prioritizing the UX.

What’s essential when solving for a blocker is quick action (aka quick-fix) that can immediately act upon & remove that friction point smoothening out the path towards helping users realize value. But, the importance of long-term value addition shouldn’t be overlooked in any sense of the word. Regressively digging into those issues towards unearthing more details, friction points, blockers, factoring that know-how into formulating crispier problem statements & lining that research up for the product teams to work out more solutions ought to be cyclical & ideally a never-ending quest to keep getting better.

3.2 The ToFu:

An existential crisis for a product organization is always going to be a deal-breaker. As an org. if one isn’t sure of how the users perceive them & their products that ought to point to a huge blocker internally, identifying which & nipping it in the bud is top draw. Educating the users about the UX & what they could expect with the product is quintessential.

I am sure you have heard of the phrase “Show them, don’t tell them”. When a picture they say is worth 1,000 words, what is a video worth? The extrapolation ought to be straightforward. Using those video walkthroughs, conducting seminars from time to time towards showing the users the best ways they can derive value out of the product is imperative given where the world stands today & the ease with which your product blends technology towards disrupting their workflow ought to be absolutely clear.

Do check out some more articles on the subject of UX:

• Whose Job is UX?

• Guide to making User Onboarding more Sustainable

• UXLG (User Experience Led Growth) is the Future

Apart from subjectively defined functions specific to their craft, one inherent trait that is common amongst these teams & goes without saying is the ability to resonate with the user groups which intern relies largely on how well they listen to them & understand the users / customers.

Listen to your customer, you must. But then the focus ought to sift through - what you learn & how fast you factor that into your scheme of things as they would play a major role in defining your growth trajectory irrespective of the type of org. you are. And, there are ample examples of this around us.

Take a look at an org. like DELL. Around 20 years back they had “listen to the customer” embedded as one of their golden rules acting as a major pillar of strength. In his book, Michael Dell talks of how they factored the VoC (Voice of the Customer) in & ended up shelving plans of a computer model they wanted to call Olympus, envisioned as a one-stop solution for multiple customer segments who pretty obviously would have had varied computing requirements right from the usual desktop PC to 24/7 gaming to high-end computing.

But, here’s some food for thought & also the soul essence of this write-up.

Why is there this perception that defaults or limits the [listening to the customer] only to some teams in an org.? Shouldn’t it be all teams who ought to be following that?

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The Usual Orientation Routine

Dictionary would define the word orientation as leaning, edging towards something, emphasizing, adjusting, finding your feet & settling into a rhythm towards achieving a given goal.

Talking of an organization orientation could run into multiple types. It could be covering something pretty basic as customer orientation which talks about a philosophy that puts the customer’s needs at the helm aligning all other teams thereof to it or something high-up like strategic orientation which refers to the fundamental approach an org. would take to get to their goals. Both bear a pretty rich significance & can never be overlooked.

Over my sessions with aspirants, product managers, leaders & cofounders I usually tend to underline the significance of orientation as I strongly believe that it could help shape the future of the teams & build a strong cultural base over the long run. After-all a lot of our jobs depend on the relationships we build internally with the stakeholders & the teams. When a mentee shares a problem over a LIVE session, I start by firing off a few questions to dig into those strategic bits & then gradually shift towards learning a thing or two about the depth of their customer orientation, zeroing in on crucial values the teams are rooted in & believe. It is very common for people high-up to possesses the knowhow given their position of influence & their clarity over the vision but whether or not that understanding has cascaded to the grassroots is often the talking point & what helps define the degree of alignment / harmony (or otherwise chaos).

Rethinking Orientation

Analogically, picture one of those tandems (long cycle – refer image below). No doubt, the one at the front seat would have a better view of the terrain & would be entrusted with the steering / direction function, when the ones at the back would just keep pedaling & at most times aimlessly. The follies of the guy at the front would have to be borne by the whole bunch of cyclists cascading all the way down to the person at the rear end, offering no escape route whatsoever.

Although it could be too much to expect that the cyclists at the back carry a detailed knowledge of all the happenings LIVE, they could always be empowered with the knowledge of the terrain, the destination & of course the timing requirements they ought to abide by towards channelizing all efforts & aligning well to the outcome.

That’s the power good orientation could bring about. Extrapolating the analogy to the teams in an organization, it could be a great idea to rethink the whole orientation towards planning the inclusion of the solutioning teams like Design, Tech / Development into [customer interfacing] so as to ensure every stakeholder in question has something substantial of a perspective they bring to the table, share it towards reducing the uncertainty & eliminating the need for blind assumptions.

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The Agile methodology gives ample room for the solutioning teams to interface with the user groups but the sad part is that could be on a totally different vein altogether given how the focus there is more towards coming up with the best way to solve the problems. Most times these problems are drafted & fed to the solutioning teams as inputs by their own major stakeholder (for ex: Design Lead / Head of Design / Software Engineering Manager / Principal Engineer) or by a specific team that’s responsible for all the research or in the worst case directly from the top – the leadership.

When that may look ok to a bystander, that could lead to severe ground level problems. The documents shared may barely touch upon the real pain point or it may fall short of what’s a good emotional representation of the user’s thoughts leaving things at the mercy of hunches & wild assumptions again. It stands proven that an F2F session directly with the concerned people that matter could help capture those emotions better, which one may easily miss out on as for the other forms of documentation or receiving inputs / getting the download.

OBSERVATION: Over my mock sessions when gauging capabilities, the commonness of this problem startled me.

[ A whopping 72% of them happened to pay very little heed to or in the worst case entirely skipped / overlooked the emotional aspect when they had to interview the users & more importantly document them later ]

Yes, there are many tools like the EM (Experience Mapping) & the USM (User Story Mapping) that could act as a quick-fix in these cases just as any experienced product person would advocate. But, there’s nothing like an interface with the user as that could be more direct & could provide a chance of covering nuances leaving no stone unturned in removing assumptions (at least those wild ones) from the picture.

⚠️FAIR WARNING: The solutioning teams interfacing with the users may not be always necessary if all the mandatory documents are thoughtfully prepared. But in case there still are questions lingering without any real answers forcing teams to make assumptions, it shouldn’t hurt to interface once with the users so as to clarify a few things directly. That could also open up a few doors that may have been left untouched over the previous iterations.

Here’s a comparison of the overall impact direct orientation with the users could have across teams, especially the ones who function over the tactical side of things:

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Building the Orientation Muscles

Now that you are sorted on the importance of direct orientation, here’s a stepwise guide to gradually move your teams from the age-old methods towards opening up avenues for greater clarity:

1. Goal

It ought to begin with an understanding of the high-level goals which then ought to cascade through to the short-term, mid-term, long-term goals. Also gaining clarity on the outcomes goes without saying here.

2. Research

Conduct thorough research towards building on those goals, understanding the situation, the environment, the variables in question ought to open up a rather cross-sectional view of things. Not to mention factoring in those emotions which obviously would demand a pretty high EQ (emotional quotient).

3. Documentation

Document all the understanding inclusive of the emotions over some tool like say the USM or an improved version of it thereof towards maintaining continuity to thought / ideas is such a crucial step. Beware the emotional understanding is everything & if that’s dropped, a lot of the originality would be lost.

4. Shared Access

Share the document internally with all the teams that matter so that they could spend time brainstorming internally towards building an understanding of the situation from the perspective of their craft whilst also getting a hang of their deliverables / outputs.

5. Gaps

The major stakeholders of the teams getting together to Identify those gaps (if any) in understanding is a great way to collaborate, bridge gaps & build a core understanding whilst also gain a holistic perspective of how everyone’s contribution would add up to the end goal. Also, one could arrive at a consensus of the assumptions, eliminating the ones that could be risky.

6. Re-emphasize

When brainstorming could lead to clarity it could also lead to many unanswered questions which may then demand further interfacing with the users. Enumerate them, make a checklist & clear them up with the users interviewing them as needed or observing their workflow over a LIVE session.

7. Update

Make it a point to update the documentation suitably so that the fresher perspectives & newer findings get factored in to redefine the problem & get appended to that requirement list.

Do Remember:

When direct orientation works like a blessing, please ensure your teams follow this like clockwork all throughout covering every one of those EPICs in the roadmap or every feature that they build. When the decision to interface with the users may not be simple, please remember that your success is all down to that understanding you build. So, you either facilitate teams in building that core understanding removing the element of doubt & doing away with wild assumptions so as to improve relevance & adoption thereof post-release or walk with a partial blindfold building something based on wild assumptions expecting it to resonate with the users.