This week’s newsletter is sponsored by GetWhys, a buyer intelligence and validation tool that pulls from a database of thousands of buyer interviews and your own messaging frameworks, plugs straight into AI tools your team already uses to generate content, and ensures that what you ship is grounded in deep customer insight, not your best guess (or AI’s). See it in action here.

Few companies have ridden the AI wave like n8n. The workflow automation platform raised a $180m Series C last October, backed by Accel and Nvidia’s venture arm, and a strategic investment from SAP in May doubled its valuation to $5.2bn. It’s one of the most popular projects in GitHub history, with a community that creates content faster than any marketing team could, and an enterprise team that has grown from 10 to 120 people in 18 months.

But what does product marketing look like inside a company at the centre of the AI movement, where PMMs build their own agents and the default approach to anything is to automate? I sat down with Lucas Nilsson, n8n’s founding enterprise product marketer, to find out.

A few things stood out for me from the chat. The suite of agents Lucas has built for the team - all named after Norse gods - including one that helps them ship 8-10 case studies a quarter. His refusal to make a trade-off between community and enterprise. And his point that AI makes product marketing more important, not less. Agents won’t just read the work PMMs create, they’ll make decisions based on it. And when more content across a business is made with AI, product marketing owns the foundational layer it all relies on.

Read on for the full interview.

You went from advising early-stage startups on product marketing to moving in-house at one of the most exciting companies in Europe. What was it about n8n that pulled you in?

I actually intended to stay a freelancer for a very long time. When I left my previous company, I really wanted to work for myself. I was mostly working with SMEs and early-stage startups, helping them come up with a pitch and a narrative that highlighted them well.

Then at some point I got an email from n8n asking if I was interested in becoming the founding PMM on the enterprise side. At first, my reaction was that I was actually not that interested. But I was hearing about n8n a lot, and I was already writing about the AI topic and how it’s influencing product marketing. So I thought, why not? Then I had a great interview process, and they offered me the position. And I first said no. I said: Guys, I love the company, I love the product, I love the culture, but I want to stay a freelancer. So I was actually a freelancer with them for a year before becoming a full-time employee again.

Then I realised that careers are made of phases. Sometimes you find the right opportunity and the right place to learn, or be at the forefront of something that is happening. At n8n I got lots of freedom. I can build what I think makes sense, and I’ve got almost all the resources I need for it.

You’ve got two main go-to-market motions: PLG, and then you’re building out an enterprise motion. How much do those two things need to have the same story?

At n8n, it’s two sides of the same coin. The vast majority of our enterprise customers started with a builder somewhere in the company who tried to automate something on their own. For enterprise deals, most of the time we already have a strong champion. When companies show up on a call, they’re not asking, what does your product do for me? It’s: how do I subscribe? How do we enable people to use it internally?

Now, do you speak about the same thing to a builder and to an enterprise buyer? Not necessarily. For enterprise customers, what matters is: is it compatible with my ecosystem? Is it safe? Can I observe it? But there’s one trade-off I don’t see us making: choosing between community and enterprise. That’s very difficult for a PMM, because positioning is all about making trade-offs. But we know our success comes from the community.

I imagine you’re quite exposed to the constant language changes happening in tech and AI. How do you think about category words and how to describe n8n?

I don’t know how many report reviews I’ve had from Gartner this year, but every time it’s for a different category. Product marketing’s role is to be a frame of clarity, because terms such as workflows or agents have so many different flavours. We’ve lived that ourselves: at n8n we had been calling something an agent that was actually closer to an agentic workflow - a workflow with an agent within. Now we’re releasing agents that are more autonomous, and we have to make sure that switch in language gets understood.

Everyone right now is releasing workflows and agents. They’re not really competitors except, perhaps, in a tiny niche. Everyone is building the same thing in a different way, from a different background. n8n comes from middleware: we’re connected to all your tools and built to handle complex projects. But how do you win when everyone is positioning on the same thing? Our advantage is that n8n got there first, so we don’t have to educate people about what the product is.

I was looking at Google Trends just for fun, and usage of the term “agent” has skyrocketed. But if you build an agent in n8n, in Claude, or in Notion, you get a different experience and a different outcome. So what do you focus on? What battle do you want to win? Because you can’t win all of them.

A lot of companies are wrestling with AI adoption internally. From that “Tokenmaxxing” trend, to those sobering up to the budget impact. How are you thinking about it?

The idea of Tokenmaxxing was: we need to use more AI, so let’s maximise spend on it. Just throwing money out of the window. The real question is how you solve AI adoption. That’s what we’re trying to solve at n8n. We want people to use more AI, but in the right way. Now, if you use MCP to connect Claude Code to n8n, or use our AI assistant in the product, you can just say: I want to automate this task. The AI asks questions, iterates, and creates the workflow for you.

Right now everyone is using agents for everything. And agents are amazing, I use them a lot, don’t get me wrong, but they’re not relevant for every single task. They’re costly, and while the price of tokens is decreasing, the price of AI agents keep increasing. Using Fable, you can easily spend a few thousand euros just trying to build an app or keep an agent running, and it compounds. Companies don’t have unlimited budgets. An automation that scans your email and sends you a recap might be quite expensive as an agent, for something a workflow can do. So there’s a question of what technology you use for what use case.

I’m a non-coder myself - definitely not a developer or an engineer - and I’ve built entire data pipeline automations, because AI helped me and iterated with me. I don’t think you need to build agents for everything. You have to mix approaches and use them where they make sense. Enterprise companies will realise this very soon.

What’s working for you from an AI tool perspective, outside of building within n8n? Are there tools that have become essential?

I have a trio of tools I created, which I launched internally this week. They’re all named after figures from Norse mythology.

The first one is called Odin. It’s a PMM hub that gathers our positioning, messaging, battle cards and sales decks, as well as our latest features. A salesperson can ask: I have a customer in this industry, what’s the right messaging for them? And get an answer directly. It can be used by humans, but more importantly, by agents. That’s where things get interesting, because PMMs have always been context engineers. Messaging, positioning, battle cards, market research - all of it is context engineering. And that layer is precisely what agents need to make the right decisions.

The second is focused on customer marketing. It’s an agent that spotlights which customers would make good case studies, using information about the product, revenue, contract and our relationship with them. It surfaces the best candidates, we organise an interview, and the case study is automatically generated. Right now the cadence is around 8-10 case studies a quarter.

The last one, which I just shipped, is a problem many companies are trying to crack: you’ve got thousands of sales calls, how do you make sense of them? We created a data pipeline that takes all the calls in our customer database and extracts the use cases being mentioned, the objections, the questions they ask, and who asked them. Then you can spin up an agent that can tell you: here are the questions directors of internal AI are asking in the finance industry at the discovery stage. And you get an answer rooted in data. It’s not going to do all the research for you, and it won’t substitute for human analysis.

It’s not realistic, or even desirable, to delegate decision making to AI. But if I want to create a thought leadership piece, I have 20,000 calls I can now use as inputs. That means that I can make sense of an incredible amount of data - which was not possible before. This is still product marketing work. But the realm of possibilities has changed, and the agency a PMM can now have using such powerful AI systems is incredible.

So your default, rather than finding a tool you can buy, is: let’s build something. Is that fair?

Most solutions on the market are useful, but not great, and they don’t work exactly how I want them to. By building, I can tailor something to our processes and the needs of our teams. Take Gong, the sales call platform, as an example. They have trackers, they have some information, but the level of detail and precision of their agent is not even close to what I’m expecting. I don’t care that a competitor has been mentioned. I care about how it has been mentioned. What’s the mindset of the customer? Are they trying to migrate away from it? Are we in competition with them? If you just do keyword research, you’re missing all of that. And one more perk of building: no procurement process. You need it, you build it.

And where is AI not so useful right now?

AI is amazing for collecting inputs, but it’s not necessarily good at making decisions. Sometimes I see first iterations of positioning or messaging work, even from Fable, and I look at it and it’s so bad. So bad. Even though it has amazing inputs.

But if you iterate with it, use it as a brainstorming tool and a way to query a large quantity of inputs, it’s incredibly powerful. It’s an extension of yourself. The problem with the conversation is that we only see AI as a replacement, whereas tools are extensions of human beings. Put an AI in charge and see how it goes - you’ll end up with an average output in the best cases. What it does well is raise the bar. It helps us as humans raise the bar.

PMMs by our nature are always looking for that differentiation story - how we can say something that cuts through. By the nature of these AI models, that’s a hard brief for them.

I started my career as a brand strategist. And I’ve always been impressed by the ability of brand strategists to spot a tiny signal and base a campaign on it. People look at it and go: wow, it resonates. All the best campaigns are based on a great insight. That’s still something AI will probably miss. Or it might find it, but drowned in hundreds of suggestions. It takes a marketer to spot it.

AI, when done well, makes great marketers better, but it also makes product marketing more important. That’s the conversation we should be having as product marketers. It’s amazing. Someone is finally reading all our work. All the positioning and messaging documents, the research. It needs to be done, and now it gets used by an agent. Finally!

Lucas is hiring: n8n is looking for a Staff Product Marketing Manager, Enterprise, live on PMMJobs now. And if you want roles like this landing in your inbox every Monday, you can sign up for the PMM Jobs weekly email here.

When it launched earlier this year I gave Anthropic’s latest product a go and came away feeling the same as I have about a lot of AI tools over the past couple of years. The idea is great, you know it’ll eventually work, but it doesn’t do the job just yet.

With a Claude product, though, you can be fairly confident it’ll work out eventually. And in the last few weeks, Claude Design has come out of research preview and into beta, it’s much more reliable, and I’ve started using it for some actual client work. So it feels like the right time to recommend that fellow PMMs give it a try.

As with Cowork, there are better experts out there when it comes to Claude more broadly. Ruben Hassid has the most thorough walkthrough, and the Claudia + AI substack has a great piece about setting up a design system.

This, specifically, is a guide to using Claude Design for product marketing work, based on my own experience with it over the past few months.

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This week’s newsletter is sponsored by Articos, which runs synthetic user research so you can test messaging and positioning on your audience before you ship it. You set the research goal, it interviews a panel of personas grounded in peer-reviewed behavioural science, and you receive clear recommendations in around half an hour. Validate your positioni…

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This week’s edition of The Product Marketer is sponsored by Articos, which runs synthetic user research so you can test messaging and positioning on your audience before you ship it. You set the research goal, it interviews a panel of personas grounded in peer-reviewed behavioural science, and you receive clear recommendations in around half an hour. Va…

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This is a companion guide - the discovery questions I ask, the structure of each document, and the prompts for the parts where I use AI.

The most useful way to use it is as a file. Attach it to Claude, ChatGPT or whichever AI tool you use, and the model will then have your way of working from the start. So when you pick up a new piece of positioning work, you’re not explaining the process from scratch every time. It knows the shape of the project and can guide you through it.

AI is good at synthesis, at finding patterns across a pile of interview notes, and at generating a hundred options when you need range rather than quality.

What it can’t do is the part that makes positioning really work:

• Driving the conversations

• Influencing stakeholders

• Shining a light on any disagreements

• Forcing the trade-offs

• Making sure the work is rolled out properly across the company

That’s the job of a PMM. Everything below is there to make the rest of it faster.

The process at a glance

The five positioning questions

Every positioning document should answer these, in this order.

1. Who is it for? Not “who buys today” but the overlap between the customers most valuable to you and the customers who get most value from you.

2. What is it? The market category. This determines which box the customer puts you in, what they compare you against, and what “good” looks like before you’ve said a word.

3. What does it compete against? If they don’t buy you, what do they do instead? It could be a like-for-like competitor, it could be manual work e.g. spreadsheets, or it could be sticking with the status quo and doing nothing.

4. What value does it deliver? Why someone is in market for a product at all. It doesn’t have to be unique to you. It has to be clearly valuable.

5. Why choose you? Differentiation. Must be true, compelling, provable, and hard for a competitor to claim with the same credibility.

The statement format:

For [target audience], [product] is a [market category] which provides [primary benefits]. Unlike [competitor framing], [product] [key differentiation].

The four tests.

Good positioning is clear (easy to understand and remember), differentiated (distinct in meaningful ways), credible (provable and true), and strategic (guides product, marketing and sales decisions).

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So it was a pleasure to sit down with David Tibbitts, Head of PMM at Notion for AI and Core, to hear about the early days of product marketing there and how their approach has evolved as the market has changed. It was also encouraging to hear how involved the CEO, Ivan, still is, and the emphasis on storytelling and getting to the heart of the customer problem was a reminder never to forget the basics.

I learned a lot in our conversation, and I hope you do too. Read on for the full interview.

One of the first things that made me pay attention to Notion, years ago, was an email from Ivan, all about how software sometimes feels like a pair of gloves. A human hook before it ever mentioned the product. Where did that instinct to be a bit different come from?

I’d forgotten how heavy-handed I used to be with the weird metaphors at the top of those Ivan emails, though we’ve reined it in a bit since. But at the time there was a real appetite to be different, and it wasn’t about driving open rates. It was a reaction to the sameness of the marketing we all consume.

Look through your inbox and it’s all written with such polish, like it was written by someone who graduated with an English degree. That isn’t differentiating. So Ivan’s challenge was always: how can this feel like a friend tapping you on the shoulder? How can an email from Notion feel more like the email you’d get from your mom?

Does Notion’s success make that harder now? Teams are using Notion as the reference for how to write marketing, and AI is trained on all of it.

I’d hope people still value the handcraftedness of it. I get the idea of wanting efficiencies; the body of a blog post, the bullet points of a use case. But it’s still so important to have a conversation with your team about what the story is.

I can’t count the times I’ve been in an exec alignment meeting and Ivan will pause the conversation and say: Stop, none of this matters. The only thing that matters is: What’s the story? What’s the thing that glues all of this together?

So how do you actually find the story for a launch, or when you’re reframing part of the product?

It won’t apply to every feature, but I always try to zoom out beyond our own product. Ivan’s really good at this. His question is usually: what’s in the zeitgeist right now?

A couple of years ago there was economic contraction. Money was tighter for customers, interest rates were going up. So we positioned Notion as a consolidation story: our AI is all-in-one, so why pay for a chatbot, a search tool and a meeting-notes tool when Notion does all three? One subscription instead of four.

Right now we’re in the token-maxing hangover; that era was very short. So we talk more about governance and spend controls. It’s a bit dry, but it’s what’s top of mind, and you make your product part of that conversation.

Is there a validation step, or is it gut?

It’s extremely vibes-based. Oftentimes, we’ll lead with intuition over data. If we’re being good and we have the time, we’ll run a quick messaging study on a platform called Wynter with results in a couple of days. But often we’ll skip even that and just trust our gut. It’s a speed thing: trying to move at the same pace as our competitors.

Take me back to the start. You didn’t join Notion as a product marketer.

No. My offer letter literally said “marketing and support.” I wanted to do marketing, but support was drowning in tickets, so the deal was: help support for twelve months, and then we’ll talk. Eventually I moved over when there were only two other people on marketing, and I didn’t really get a title. It was “David works on the marketing team now.”

Part of my job was taking things off my boss’s plate. One was release notes, which we published to a public Notion page rather than our website. And since none of us had PMM experience, I genuinely thought being a PMM was just writing the changelog.

With such a voracious community poring over every word, it felt like being Santa Claus. People write in saying “I love Notion, but I wish it could do these seventeen things,” and you get to show up and say: we heard you, it’s here, here’s how it makes your life better.

In a way you weren’t burdened by what PMM is “supposed” to be. Did that give you freedom?

I suppose so. For the first few years, PMM at Notion was focused on our own little echo chamber, the community, the power users. We over-indexed on social: how many likes did the launch post get on Twitter. And candidly that worked for a few years.

It worked right up until we came up to the chasm, which requires a completely different skill set. At the chasm it becomes: how do we make this make sense to people who haven’t watched thirteen hours of YouTube tutorials?

Moving up-market can feel a bit corporate internally. Was any of that hard?

The hardest part was resources. From the outside, Notion must have looked enormous and successful, but we were scaling headcount slowly and deliberately. You’ve got this community evangelising you for free with a feature-request list a mile long, and then you have to start making tough trade-offs.

Suddenly better iPad support gets deprioritised so you can build a SCIM API instead, and you think, we’re not getting any likes on Twitter for a SCIM API. But at the end of the day you prioritise the roadmap for the people keeping the lights on.

Notion is said to measure organisational health partly by the ability to say no. Did you say no a lot as a PMM?

If it’s a new capability, a pricing or packaging change, or a new AI feature, then marketing does not get to say no. As a PLG company, that’s the most important thing. What we say no to is everything else: the “make me a deck” requests, some events, internal stuff.

The one rule I’d give: unless there’s a real change-management component - pricing, packaging, or changing someone’s workflow - marketing should get out of engineering and product’s way and let them ship. Marketing should never be the blocker. When it lands, do a social post, talk to the community, watch for organic adoption. It’s no big deal to do the packaged launch - enablement, landing page, video, email - two, four, six weeks later.

Notion can be used for almost anything, it’s a blank canvas. How do you market unlimited use cases, and decide what to double down on?

This is the hardest thing about working at Notion. It can be all things to all people, which makes it nearly impossible to focus. For years we refused to, and just talked about the building blocks and everything each one could do.

Then we started looking harder at the metrics, especially win rate. We used to think marketing was a core persona, because marketers were our number-one hand-raisers. Then we dug into the data and the win rate was abysmal. They were interested, but it didn’t resonate.

For us, for several years now, the teams to focus on are engineering, product and design. They already have the mental model, and are excited by Notion databases rather than confused by them. They have the budget, and they’re the internal tastemakers, so adoption spreads. We call it the wedge: the people who get our foot in the door.

Now you own Notion’s AI story. What’s that been like?

There are a lot of parallels with the original Notion story. Notion had a wildly unsuccessful first launch. It was always meant to be “build your own software to solve your own problems,” a block-based approach. So 1.0 was marketed exactly like that, and nobody wanted it. It didn’t solve anyone’s pain. Ivan always says nobody wakes up wanting to build software, unless you’re a developer.

I describe it as vitamins versus painkillers. The 1.0 launch was a vitamin: no urgency, no problem people knew they had. It wasn’t until we repositioned as a team wiki, a viable Confluence replacement, that people went, oh, I do have that pain; we have Confluence but tell me why yours is better. And they discover everything else from there.

And you repeated that mistake with the first AI launch?

We did. For the GA of Notion AI, at the very start of 2023, I thought I was being clever with a messaging framework: work faster, think bigger, write better. Our minds were blown by everything that was possible and we couldn’t fit it on a page, so we zoomed right out. It basically said: Notion AI can do anything, isn’t that exciting?

For 99% of people that landed as: wait, what? Sounds cool, but what am I supposed to use it for? It wasn’t until a couple of years later that we packaged the AI up in an opinionated way. Being opinionated isn’t natural for us: we think of ourselves as making the building blocks. But when we packaged things like AI meeting notes and enterprise search, and built discrete workflows around a specific problem, that’s when it really took off.

What changed with the Q&A launch?

Our second AI launch was our retrieval product, which we called Q&A. Instead of describing the capability - Notion searches across your tools and gives you an answer - we put really specific questions front and centre, like “what’s on the web team’s Q3 roadmap?” We elevated those examples everywhere: the campaign, the announcement.

Those hyper-specific prompts are what created the light-bulb moment. You don’t create a light bulb for anyone except a power user by talking about the capability as an abstract concept.

Everything moves so fast now. How do you decide what to keep marketing versus chasing the next thing?

The whole industry changes every six months, if not faster, so there’s always a shiny new thing to support. But when you leave the building and talk to customers, you meet a great Notion customer who isn’t even using what we shipped two years ago. It’s moving too fast for some of them.

A concrete example: our AI meeting notes, the transcription tool. It’s included in the plan, and it lets customers displace their use of a single-purpose meeting notes tool. I worked the Notion booth at an AWS conference recently, and people would come up and say “I love Notion, we use it so heavily.” You’d ask, are you using AI meeting notes? “No, what’s that?” Even loyal, bought-in users had no idea it existed.

So you can’t put 100% of product marketing on the frontier. You have to go back and drive awareness of the products you know customers will love.

Finally, for a B2B product marketer who doesn’t have all the creative permissions someone at Notion has, what’s a rule of thumb they can take back to their own work?

The number one thing I filter all of my work against - every piece of copy, every strategy - is assuming the customer does not care about your product. Even a really active user who says nice things about you cares far more about themselves and their own problems.

So instead of talking about your product, your team, your roadmap, talk directly to the customer: their pain points, the environment they’re in. Never assume they care. Ivan is wonderful at reminding us: anchor yourself in the pain, rather than the product or the capability itself.

David Tibbitts is Head of Product Marketing for AI & Core at Notion. This interview is part of The Product Marketer’s series of conversations with the people shaping how great companies bring products to market.

For this week’s edition of The Product Marketer Plus, I went back over a few recent engagements to document my process.

One slightly contentious point to begin with. As an academic exercise, positioning is fairly straightforward. I could hand a founder or CMO a piece of paper with my questions on it and they could probably fill it in themselves, quickly and easily. The hard part is whether their answers match everyone else’s in the business, and whether what comes out is both true and compelling. Both are essential. Because together they’re what makes a good story, and it’s surprisingly difficult to tick both boxes.

I don’t think AI can do this. It can probably do the exercise. It can’t spend six weeks winning over the people who need to be on board, and we’re nowhere near a CMO telling the C-suite “this is our new positioning because Claude said it is.”

It’s also why I don’t offer a two-week turnaround. You need to sit with an idea for a few days, and you need the right meetings in the right sequence. See below for my step-by-step process - and if your company needs a fresh pair of eyes on its positioning, I’m always happy to chat.

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It was a good chance to dig in…

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It’s a company I’ve long admired, and from a product marketing perspective, one does have to wonder: how do you run a PMM function at that pace, across that many products and countries, without the quality of the work dropping?

So I sat down with Sophie Storey, Head of Product Marketing at Revolut. Sophie joined as the third PMM a few years ago. Today she leads 27 product marketers from Brazil to Spain to the UK.

A few things stood out from the chat. The team has landed on a success metric for product marketing that has actually stuck, including a novel “GTM Excellence” score. Sophie has systematised how a large, global team uses AI, and she’s clear-eyed about where it helps and where it doesn’t. She also reflected on what’s changed as the team has scaled - a reminder that the shape and remit of a PMM team is always evolving.

Check out the full interview below.

Let’s start with the stats. How big is the product marketing team at Revolut? And how is it structured?

We’re currently at 27 product marketers, and I’ve got 15 new roles open on my screen as we speak. That sounds like a lot, but for the number of products and the revenue overall, it’s still pretty lean. The model is one, maybe two PMMs per product department, plus a core PMM team that sits with me.

When I joined I was the third PMM. Since then we’ve moved from GTM-over-everything to owning the full arc, we look at product adoption and driving ongoing usage, not just the launch.

Most PMMs sit directly in their product departments. Everyone at Revolut has a line manager and a functional manager. Your line manager is usually the head of product, setting priorities and guiding the roadmap. The functional manager is me or someone on my team, looking after the quality of the work and whether you’re growing as a PMM. That split lets PMMs be embedded as strategic partners, while we keep the bar on the craft.

Where does PMM actually sit? Is brand under you, or separate?

The core PMM team sits in a creative department. It’s a bit of a legacy thing, but I like to say it’s diplomatic. We’re Switzerland, in the middle and honestly it’s the right place for PMM to sit. We’re not chasing sign-ups and we’re not owning the product roadmap, so we can hold the line on the customer story across both.

With that, we have a lot of creative designers clustered around the product departments, so every PMM team works with a visual designer, a 3D designer - motion where possible. We do the strategy up front, then very quickly get into what this actually looks like for customers. Most of us spend a lot of time in Figma. Brand identity sits within creative too, while the growth side of brand strategy and above-the-line execution sits in the growth department. We’ve gone from an agency model, with everyone requesting things and no PMM filter, to PMM owning the strategy before anything hits a designer’s desk.

What do you think lets Revolut ship at the pace it does?

It really comes back to the cultural values. Revolut is very clear about who it is and who it isn’t. Everyone is incredibly high agency, with a strong get-it-done mentality.

Even though we’re big now, with a lot of process and compliance as a bank, people bring a startup mentality: all hands on deck, small lean teams, a flat hierarchy. There’s a genuinely entrepreneurial streak to it. A flat hierarchy means nobody’s waiting for permission, so people treat their product like a business they own rather than a brief they’ve been handed. Nobody says “that’s not my job, I just do the product marketing bit.”

The way we work is that the KPI will be around product usage, and then we leave it to the individual PMM to decide how they want to go and drive that. You get a heck of a lot of autonomy. For the right people that’s exciting. For the wrong people it’s daunting. You’re not just shipping the product, you’re constantly looking at it through a business lens.

So there’s less soul-searching about what PMM should be measured on?

We’ve tried every possible combination of KPIs during my time here, and we always land in the same place: what is the purpose of PMM at Revolut? It’s two things. Are people using the product, and is the GTM excellent? So we’ve built the KPIs around that: new users to a product, driven by marketing, assessed against holdout groups. Then recurring users, because - for example - we don’t just want you to open a savings account, we want you to put money into it. And we look at the GPPU (Gross Profit Per User) uplift alongside that, the actual commercial impact. Attributing GPPU directly to PMM is something most teams in our discipline never crack, so building that with internal teams was a real unlock.

GTM excellence used to be the subjective bit, but with our data and ops team we’ve built a “GTM Excellence” score: click-through rate, overall conversions, and a low-weighted element of stakeholder feedback - almost an exec-level NPS. A lot of that model exists to stop us celebrating a big launch spike and then never looking at the product again until the next GTM. You want it out in the world, taking care of itself while you monitor it, so you can move on and fix another part of the funnel.

Does the rest of the business actually understand what product marketing is?

Across the business, yes, and that surprised me when I joined. I thought I’d be living in dashboards and SQL. But everyone here is so brilliant technically that while the dashboards are key, where we add the most value is the creativity. Within fintech I very rarely see work and think “wow, that’s inspiring.” You usually have to look further afield and be good at connecting the dots, and that value on creativity comes right from the top.

I’ve had the odd sceptical product person who hasn’t worked with PMM before. Generally you do one GTM with them and it’s fine. You just need that one, “let me prove it to you” moment. Now we’ve got so many examples, plus clear metrics, that I’ve never had to do much of the “what PMM is and isn’t” tour you have to do elsewhere.

You’ve been talking about AI in product marketing. What’s actually working, and what isn’t?

The honest summary is AI has raised the floor, not the ceiling. It takes the mechanical work off the team so we spend more time on the parts that actually differentiate us.

We experiment a lot. The strongest, most established example is a targeting model, built closely with the tech team, that gets us the right product to the right customer at the right time. We used to do that very manually, a lot of Boolean logic and SQL. The more interesting shift is that the model has flipped how we work. It doesn’t just match existing value props to customers, it surfaces clusters of customers it’s trying to serve where we’ve got nothing to dispatch. It turns the value proposition library into something we engineer against real audience gaps.

Day to day, there’s a lot of creative ideation and mocking things up in Figma Weave. And one of my favourites: value prop validation used to be slow and hard to do at scale, but with Maze and AI-moderated user testing, the kind where people actually speak back to you, I can validate globally within 24 hours. It’s far more valuable than surveys: you get the clips, hear the language people use, and might realise you’ve got a term slightly wrong.

What AI can’t do is the last mile of craft. The gap between what I picture, what I can get to purely using AI tools, and what our designers actually produce, especially with motion, is still miles apart. AI can get you a fast, passable version of almost anything, which is exactly why the passable version is now worthless. When everyone can generate their own, the work that stands out is the work someone has actually sweated over. That bar has gone up, not down.

Revolut scaled across so many markets so fast. What’s PMM’s role in that?

PMMs are largely global, and at our scale you have to build with a global denominator, a wedge that’s fairly consistent everywhere. The part that gets localised should be the proof of the product, not the story. So it’s one story that’s true in all the different places, addressing a real friction in each market, rather than lots of stories stitched together.

What’s newer is that we’ve hired our first country-specific PMMs. We’ve got one covering the whole of APAC, and we’re recruiting for the Americas. They look across those markets and close the feedback loop. Being global is all very well, but once you’re on the ground you get a different perspective. I want the local teams to tell me if the central thinking is wrong. That’s the whole point of the role. That’s the bit we’re working on now: not just product parity, but what actually matters to this audience, before any positioning or creative work is done.

How systematic is all this? Do you believe in playbooks and templates?

Pretty systematic, though I used to be more anti-process. The second I write something down here it goes out of date, because we move so quickly. But to keep up with the volume, you need it. We have a very well-modelled GTM process - about ten steps. It’s a bit of a GTM Bible that has evolved over years. Any time I have a new learning or spot a gap, it gets updated in there. Alongside it we have GTM tiering for channel decisions, plus value prop and GTM strategy templates that feed a proper value proposition library.

Where we lean into playbooks most is repeatable, sequential launches. New partnerships on plans, for example, are playbooked so local teams and ops can pick them up, adjust, and get PMM review. I wouldn’t do that for the big things. Those are too important to copy-and-paste. The whole point is to free up effort for the new bets and the work built from scratch.

Reflecting on your time running PMM at Revolut, what are you most pleased about, and what excites you next?

The thing I didn’t expect is how much the calibre of the team compounds. When everyone around you is genuinely excellent, the bar for your own work quietly goes up, and that’s been the most rewarding part to protect as we’ve scaled - not letting that slip even as the headcount grows.

Second, the measurability. Attributing GPPU directly from conversions to PMM is a big thing, and a big challenge for our discipline generally. Once we cracked financial attribution, the risk was over-indexing on it. Some of the most important PMM work will never show up in a GPPU number. The story, the craft and the willingness to try something that’s never been done before, none of that attributes cleanly, and we protect time for it deliberately.

Third, the creativity - the never-settle instinct. Whether it’s a tiny GTM or something as simple as a product article, we’re all conscious of whether it’s the best it could be. What excites me next is cracking that local nuance at scale, keeping the global model working while getting genuinely sharp on individual markets. No small challenge, but it’s the one I’m most keen to solve.

If this sounds like your ideal PMM set up, you’ll find a number of roles at Revolut live on PMMJobs.co right now. You can sign up for the PMM Jobs weekly email, which lands in your inbox every Monday, here.

If you’ve worked in product marketing for a while, this might sound like a strange question. Because, for those of us in it, the difference between a product manager and a product marketer is very obvious.

But it’s worth reminding ourselves that it isn’t clear to everyone. For a lot of our colleagues, those new to tech, arriving from a broader marketing background, or simply working with product managers and product marketers for the first time, the two sound pretty similar.

They both sit close to the product. They both talk about customers, launches and roadmaps. I understand the confusion. So this week I want to do my best to pull the two apart and explain the difference as clearly as possible - for you to share as a guide for anyone who needs it.

There are, of course, outlier examples. Some companies, like Airbnb and Apple, combine the two into a single role, with one person owning both the product vision and the story of the product. As far as I can tell that’s still the exception rather than the rule, but it’s worth being aware of, because I suspect it’s where some of the confusion comes from. Everything below describes the more classic distinction, where these are two separate roles working side by side.

What a product manager does

A product manager is the person steering a group of disciplines towards a shared vision and goal for the company’s product(s). They sit where the technical side of the business - engineering, data and design - meets the commercial goals of the company, and their job is to keep all of it pointed towards the same outcome.

The clearest industry definition I’ve come across is Marty Cagan’s. He says the product manager is responsible for making sure that what gets built is both valuable and viable. Valuable to the customer, viable for the business. More than anyone else, they’re the one accountable for whether the product succeeds or fails.

In practice that looks like leading a squad of people. Usually engineers and designers - often a researcher or analyst too - working together to solve a real problem for customers. The PM sets the roadmap with buy-in from leadership, runs the product sprints that get the squad shipping, and is on the hook for hitting launch dates and growing the product to agreed levels of adoption and revenue.

Much of their time goes on collaborating with engineering and design. How best to solve a particular problem. What a great customer experience might look like. What the optimal sign-up flow might be. Where the flaws and the opportunities for optimisation are hiding. They’ll explore new routes for the product too, whether that’s new categories, expansions or capabilities, and they’ll commission and sit in on user research to understand how people actually use the thing they’ve built.

I’ve found that there are different flavours of product manager. Some have a real flair for design and user experience, and they’re brilliant at driving a great product experience for customers. Some come from an engineering background, and excel at getting the most out of engineering teams. And some come from a more business-focused route, often with an MBA, and act more like a general manager, very focused on the numbers and the metrics. Each type brings its own strengths, and there’s no single right way to approach it.

What a product marketer does

I’ve written a full definition of product marketing before, so I won’t relay all of it here. But in the context of this comparison, the simplest way to put it is this:

If the product manager steers the product and technical teams towards the goal, the product marketer is the bridge between the product and the commercial parts of the business. Usually marketing and sales.

Where the product manager owns what gets built, the product marketer owns the story of what gets built. In practice that means setting the positioning for each individual product, and then at the company level, owning the value proposition and the messaging for the full product offering. You drive the go-to-market for every new product and feature, from the launch narrative to how it actually reaches customers. And you tend to own the workstreams that keep the company honest about the market, competitive intelligence, win-loss analysis, and the sales enablement that gives the commercial teams what they need to sell the product well.

A lot of your time goes on getting to the truth of the product’s value and then translating it. That starts with insight, the market, customer and competitor research that tells you what people actually need and how you’re uniquely placed to give it to them. It means defining who you’re for, the ideal customer profile and the buyer personas, so the whole company is focused on the same people. And it ends in clarity, distilling a complex product down to a story a customer can understand in seconds, building the messaging that carries it, and making sure sales, marketing and customer success are all telling the same one. Throughout it all, you’re the voice of the customer inside the building.

The shortest version of the split:

• The product manager owns what gets built and whether it works.

• The product marketer owns how it’s told and how it reaches the market.

Where the lines get blurry

That clean split is useful for explaining the roles. It’s less useful for describing a good working day, because the best PMs and PMMs don’t always respect a hard line between them.

Product managers rightly want a view on the distribution strategy and the story of their product. This should be encouraged. It’s their product, after all. I’ve argued before that product marketing needs a seat at the product table, and the reverse is just as true. A PM who cares about how their product is positioned and reaches customers is likely a great PM.

The healthiest way I’ve found to think about it isn’t a boundary at all. It’s a partnership. The kind where a product manager has such a strong relationship with product marketing that they trust the PMM to own the story and the distribution, with the PM’s input. Because product marketers spend their days obsessing over the most effective way to get a product into people’s hands. When you’ve got someone with that time, expertise, and that focus, you should let them run with it.

So keep the distinction clear in people’s heads, so everyone understands who does what. But the working relationship is a different thing, and there the blurred lines are to be embraced. It’s what good collaboration looks like. What you do need is to know who’s accountable for what, so the team can stop negotiating it and move at speed.

The cleanest version of this is having product management and product marketing on the same team. Where possible, I’d have a product marketer sitting inside the squad the PM is accountable for, alongside engineers, designers, researchers and analysts. The PM still owns the success metrics of the product. Product marketing owns the delivery and accountability for specific initiatives inside that squad. Once that’s clear, everyone can get on with the work.

And then, respect the craft. Product marketing is a craft and a discipline, and the same is true of product management. Product managers are good at things product marketers aren’t, and the other way round. Blur the day-to-day as much as you need to keep the project moving, with people doing whatever needs doing, but let the important calls sit with the person best placed to make them. You want the big decisions made by the right expert, not just whoever has free time.

AI is about to blur it further

The lines are going to blur further still, and AI is the reason.

Product marketers will increasingly mock up the experiences they think should exist, straight from the insights they’re seeing. Product managers will increasingly do their own marketing and content. Both are already starting to happen, and both are acceptable.

Blurring who does the work is fine. Blurring who makes the call is where things begin to fail. Product management should still hold the pen on what gets built and on what a great product experience looks like for customers. Product marketing should still make the final call on positioning and on what good product messaging looks like. AI isn’t yet good enough to make that level of decision, and even when it is, you’ll still want your most important calls made by the person who understands them best.

The short answer

So, if someone new to tech asks you the difference, here’s the version I’d give.

The product manager decides how best to solve a customer’s problem, what to build as part of this solution, and makes sure it works. The product marketer decides how to talk about it and takes it to market. In an optimal setup they work as one team, the PM owns the product’s success, and the PMM owns the story and the distribution that so much of that success depends on.

If you’re setting up these two functions in your own business and want to spar on how they should work together, get in touch. I’m always happy to talk about how best to untangle the two teams.

Don’t miss

This week, members of The Product Marketer Plus got a step-by-step guide to setting up a Morning Briefing skill in Claude Cowork. It plugs into your email, calendar and meeting notes to set your day up well, every working day.

Start a free trial to read it here.

I have a theory about this. The bulk of marketing functions have obvious things to automate, with well-worn tools and processes to hand over. Product marketing is a bit messier. There are very few repeatable processes sitting there waiting to be overhauled, so it’s hard to know where to start.

So this week I want to share something I built that has really changed the way I work. It’s a morning briefing agent that plugs into the tools I use and tells me how to prioritise the day ahead. It’s become the way I start every work day.

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Founders talk about it in podcasts. Sales leaders blame it when deals don’t convert. Marketers riff about it when they want to launch a new brand campaign. It gets used to mean the tagline, the category, the pitch, the brand, or simply “the way we talk about ourselves”.

But if you’re a product marketer who cares about the craft, you know positioning is a real thing. A defined piece of work, with a real definition and processes to follow - and real consequences when it’s done badly.

I wrote last year about how to run a positioning process properly. This week I want to answer the more fundamental question: what even is positioning? We’ll walk through two definitions that helped build the concept, and then the way I’ve come to see it, as a statement of strategy you never fully control, one that keeps shifting as the market moves beneath it.

Where it started

I’m a self-taught marketer. I didn’t study marketing at university (I was a history and politics student - not sure what that was supposed to lead to...) But I do know that the idea of positioning didn’t start with software or SaaS. It comes from the mythical pre-internet world. It started in advertising. So let’s dig into that a bit. (Ok maybe the history degree was useful?)

Jack Trout first wrote about positioning in 1969, in a trade magazine article about winning in a “me-too” marketplace. He and Al Ries developed the idea through the 1970s before publishing Positioning: The Battle for Your Mind in 1981, still one of the most influential marketing books ever written.

Their definition is this:

“Positioning is not what you do to a product. Positioning is what you do to the mind of the prospect.”

This was the era of Avis (”We’re number two. We try harder.”) and 7UP (”The Uncola”). Consumers were drowning in advertising, and Ries and Trout argued the only way to cut through was to occupy a single, clear position in the prospect’s mind, usually defined relative to the leader in your category.

It holds up remarkably well. The core insight, that positioning lives in your buyer’s head rather than in your product, is still a principle that rings true for any product marketer, regardless of industry.

You don’t get to simply declare what you are and have the market accept it. The market already has a landscape of products in its mind, crowded with competitors, and your job is to work out where you fit in it and what you can credibly own.

This was a groundbreaking idea in an era where shouting the loudest and spending the most was the conventional wisdom.

How software changed it

The Ries and Trout worldview assumed a fairly stable set of categories. Soft drinks, cars, painkillers. Software changed that. Now, new categories appear (and vanish) all the time. Products change every quarter. Buyers spend months researching dozens of near-identical alternatives before they speak to a salesperson.

The arrival of SaaS and the explosion of B2B tech changed the game. Suddenly there were thousands of products solving problems customers didn’t yet have language for, in categories that didn’t exist a year earlier. That’s roughly the moment product marketing became a real job, and people like me became employable. When your product is complex and the category is unclear, someone has to make the market understand what you are. That someone is usually a PMM.

The best modern definition of positioning - in my opinion - comes from April Dunford, whose book Obviously Awesome reframed positioning for this new world:

“Positioning is the act of deliberately defining how you are the best at something that a defined market cares a lot about.”

Dunford describes it as context-setting for your product. Her analogy is the opening scene of a film. Before you can follow the plot, you need to know where you are, what year it is, and who these people are. Positioning does the same job for a product. Get the context right and customers understand you instantly. Get it wrong and even a brilliant product looks confusing.

I like that the word “deliberately” is in there. In Dunford’s world, positioning stops being an advertising trick and becomes a strategic exercise: choosing your competitive alternatives, your differentiation, your target market, and accepting the trade-offs that come with those choices.

How I think about it

Both definitions are excellent, and I refer to them regularly. But after years of doing this work in-house and now across consulting clients, I’ve landed on my own way of thinking about it. And it starts one level up from the product.

Most definitions treat positioning as something you do to a product. Find the best way to frame it, set the context, place it in the right category. That’s all true. But, for me, positioning is really the practical expression of your company’s strategy. The decisions underneath it - who you’re for, what you’re best at, what you’re deliberately not going to do - are strategic choices, not marketing ones. Positioning is where that strategy becomes a claim the market can understand.

So here’s the definition I use:

Four ideas are touched on in this sentence.

Strategy. Positioning isn’t a copywriting task. It is based on hard commercial choices: the segment you’re going to win, the alternatives you plan to beat, the one or two things you want to be known for, and the value you create that others don’t. Pinning those down is the hard work. Get them clear and the claim almost writes itself. It’s also why I think a product marketer, rather than a brand team, is usually best placed to drive positioning. It sits at the point between the product, the market and the commercial reality of the business.

True. Whatever you claim has to hold up the moment a buyer uses the product. Positioning that oversells opens a gap between the promise and the experience, and buyers feel that gap straight away. This is the part that keeps you honest. It’s also why you never fully control your positioning. Your market, your competitors and your customers all influence your claim.

Compelling. ‘True but dull’ is just as a bad as claim that’s delusional. The claim also has to matter to the people you’re selling to, and pull them towards where your company is heading. This is the ambition side. Positioning lives in the space between how your product is seen today and how you want it to be seen tomorrow. Pure reality is unambitious. Pure aspiration is fiction. The trick is finding the point that’s both true and compelling at the same time.

Never finished, because positioning moves as the world underneath it moves:

• The facts change. Markets shift, categories mature, the ground you’re standing on isn’t fixed - especially with the change AI is driving.

• Your competition changes. They get better, or they get worse, and either way your relative position moves.

• Your customer changes. The type of company or buyer you’re going after evolves, and so does what they care about.

• Your product changes. New capabilities mean a new value proposition, and the reason people buy you shifts with it.

• You change. Get stronger at brand building or develop a sharper sales motion, and that becomes a factor you can lean on.

Positioning has to reflect both the now and the future. It’s a living, breathing thing, not something you lock in for years.

Why it matters

When positioning is strong, everything downstream gets easier. Messaging sharpens because you know exactly what you’re claiming and for whom. Sales conversations improve because the pitch matches the claim you’re making on your website. Product decisions get clearer because everyone understands what the product is and isn’t. Pricing, packaging, onboarding and GTM all have a reference point.

When it’s weak, you can really feel it. Sales pitch one story, marketing tells another, product builds something different entirely. And customers are left to work out for themselves what you do and why they should care.

Where it goes wrong

The most common failure I see in consulting work is companies that don’t really have positioning at all. They’ve never made the deliberate choices, so there’s a clear absence of it. Teams pursue different strategies, and the messaging is inconsistent.

Beyond that, there are some common mistakes:

Treating it as a tagline exercise. Positioning isn’t copy. Copy comes later, and good copy can’t rescue confused positioning.

Being for everyone. A product for everyone that solves everything usually resonates with no one. Positioning that avoids making trade-offs almost definitely won’t work.

Not being grounded in reality. This often happens when positioning sits with brand teams or founders alone. You end up describing a company that doesn’t exist yet, and buyers notice the gap.

Setting and forgetting. Positioning agreed a few years ago and never revisited, while the product, the market and the competition have all moved on.

Skipping the process. Jumping straight to messaging and GTM tactics, because positioning feels too abstract or too slow, will lead you back to the same old problems.

What to do about it

If the word “positioning” has started to lose its meaning at your company, the fix likely isn’t a better definition (though I hope this one helps). It’s doing the work.

There’s more than one good way to run the process. The traditional approach works methodically through your customers, competitors, market and product. April Dunford’s method starts from how your happiest customers already describe you, then tests and refines until it clicks. I use both, depending on the client. What matters is that it’s deliberate, rigorous, and taken seriously by leadership, and that you make the hard choices and get buy-in on the answer, so the whole company can get behind it.

And if your company’s positioning needs that kind of attention, this is a big part of what The Product Marketer consultancy does. Get in touch.

Rory Woodbridge is a London-based consultant working with European tech companies to unlock their growth potential through world-class product marketing. Get in touch to discuss working together.

And one o…

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Sometimes it’s difficult to explain what product marketing is versus the more general marketing roles, or partner marketing, or field marketing. It’s hardest of all when I’m trying to explain to friends and family what it is I actually do - what I spend all my working hours writing and talking about.

We do have a pretty good definition of product marketing, one that covers what it is and what it isn’t.

The Product Marketer

What is Product Marketing?

The Product Marketer is a London-based consultancy working with ambitious companies to unlock their growth potential through world-class product marketing. Get in touch to discuss working together…

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a year ago · 43 likes · 2 comments · Rory Woodbridge

But one thing I like to talk about when I’m clearing it up and distinguishing it from other disciplines is that there’s a belief good marketing needs to be based on insight and data. And this is a belief that any PMM should hold dearly.

Everything a product marketer produces should be based on insight.

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Of course launches matter. I’m not arguing otherwise. But today I want to make the case that your next laun…

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Not on the hunt right now? You can opt out of the PMM Jobs email here and you’ll still get regular content from The Product Marketer every week.

Here are twelve roles worth a look this week, with a good mix of senior and director openings. There are over 1,000 open roles on the site right now, so if nothing here looks right, there’s plenty more to explor…

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I imagine it’s been a complicated dance ever since the dawn of modern marketing, when consumers began to enjoy so much more choice.

Marketing tech and software comes with its own particular difficulties. Product cycles are short, so the thing you positioned around last quarter can be matched by a competitor in the next. C…

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It sounds a bit worrying when I put it like that. I’m a big believer in “writing is thinking”, so I’m sceptical about fully outsourcing something so important. But I do think we’re at the point where, if you write anything for work, it’s worth exploring how AI can help.

I mean that broadly. Maybe the bigger stuff like essays or social posts, or maybe just your emails and your Slack messages. Even if you’re a strong writer, there’s value in having something to spar with.

A lot of it comes down to how you use AI. Lean on it without intention and you just add to the noise. (I’ve written before about The Nonsense Machine, and how we don’t want to be part of that…) Use it with care and it’ll give you more time to think, and sharpen what you were trying to say in the first place.

So here are the practical things I’ve learned about writing with AI. And “with” is the crucial word. This isn’t a job to fully outsource, especially for a product marketer, whose role is increasingly about setting the bar for quality thinking and content across the business.

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