PMF: A Framework

I use a pretty simple 4-part framework for finding Product Market Fit. Nothing can make finding PMF easy, but this structure helps break it down.

Achieving PMF¹ means solving 4 questions:

1. What problem are we solving? (For the customer, for our business)

2. How are we solving it?

3. What is our market? (who is the customer, and is it big enough)

4. What is our GTM strategy? (Repeatable, scalable growth engine)

Using that, we can build a table with four rows, one for each of these questions. We can then add a column for our hypotheses. This is what we think the answer is, based on what we know now (which might be nothing more than a guess).

Now, for each of these hypotheses, there’s an underpinning set of assumptions that need to be true in order for the hypothesis to be true² . These assumptions might be about user behavior (“people are willing to buy [x] online”), internal execution (“we’re actually able to do [x]”), performance (“users convert at [x%]”), or spend (“customers pay at least $x”)³ .

We can then sort these assumptions into two sets: “Probably true” and “Not validated”. Our task is to open up our toolkit — e.g. user interviews, surveys, card sorting, data analysis, modeling, user testing with design prototypes, painted door tests, A/B tests, Pilots, etc. — and find the cheapest & fastest way we can move one of these assumptions into the “Probably true” column.

At some point, we’re going to run into assumptions that prove to be probably NOT true. That’s when we need to go back and iterate on the hypotheses, and restart this entire exercise, with new assumptions born out of the new hypotheses that need to be moved from “Not yet validated” —> “Probably true”.

As you get more experienced, you’ll get faster at 1) spotting the assumptions that are most likely to be wrong, 2) identifying the right tool for the job of testing that assumption, and 3) coming up with hypotheses that are more likely to be right.

None of this is easy⁴ and it’s not quick. But I’ve found this way of structuring things to help me not get overwhelmed by the complexity of going 0 → 1, and more quickly get focus on what to do next. I hope it helps you, too.

The Workshop

This is a newsletter-only section where I share a half-baked idea in hopes that y’all who are smarter than me can work it out with me.

I recently subscribed to the r/ProductManagement subreddit, and it’s such a daily reminder that most people who work in Product are at companies who are terrible at Product.

Check out this thread from last night, about being a Product Owner in a SAFe organization.

It would be fun to do some kind of corporate archeology to identify all the root causes that lead to a company deciding SAFe is the way to go. Like, all the way down to how the company culture reacts to risk, why command & control seems to have won out over autonomy & accountability, what advantages in their market does this company have that would allow for such a slow and bloated process, etc.

It’s a reminder for where on the adoption curve a lot of the “mainstream” topics we’ve assimilated actually are: customer discovery, outcomes over outputs, OKRs, PMF, etc. A lot of people are still living the consequences of the mid/late 2000s, when practitioners of Scrum split into two groups: pragmatists who saw it as a flexible starting place “but do whatever works”, and zealots who saw it as a religious text that must be followed to the letter or else “you’re doing it wrong” (plus the grifters who sprang up certification programs).

1  And here is your regularly scheduled reminder that PMF isn’t a thing you get, it’s a thing you have right now for a certain definition of the market. And if the market changes or you expand your definition of the market, your PMF might not come with you. Also, happy early adopters sometimes means PMF but sometimes is a false positive.

2  Obviously, don’t go crazy with the assumptions. Just put down the ones that seem 1) the most important to be true, but also 2) are the least obvious are true.

3  My favorite place to start is by building a simplistic model of what a successful funnel could look like. Traffic → conversion → $ per user → Revenue. And then asking myself, “What’s my level of confidence that each of these can be true?” And each one might also spawn additional questions, because for that to be true, other things would also need to be true.

4  It’s totally OK if, at the beginning, some of these are blank because you don’t know yet. Start by filling in the Market hypothesis and then immerse yourself in it, get to know the people in that market and what problems they have, the dynamics of the market (competitors, what’s solved well and what’s not, what people value / how money is made). Over time, the other hypotheses should become more clear. Or, you’ll decide there isn’t anything here for you and come up with a new Market hypothesis.