The clearest sign of finding product-market fit is feeling "pull" from the market.
But what does "pull" look like?
👇 Read on 👇
1/ Sign 1: A sudden inflection in organic growth
Netflix: "Where before we were struggling to get traffic, all of sudden we couldn’t keep up." - @mbrandolph
Tinder: "Downloads started to skyrocket" – @badeen
Uber: "Word of mouth was uncontrollable" – @ryangraves
2/ Sign 2: Customers ask to pay for the product before you ask
Carta: "I've been trying to get to your sales people for weeks!!! Why won't you take my money???" – @henrysward
Github: "To our surprise, users started writing to us asking ‘Can we pay for this??’" – @mojombo
3/ Sign 3: Users flip from excited to upset
Datadog: "When we hit early product-market fit, our users switched from being excited at all the things our product could be to them to being upset about all the things it didn't do yet." – @oliveur
3b/ Segment: "The thing that flipped was, people would previously tell us they wanted a feature, but not use it. Whereas now, people were using it and they would want a second feature." – @reinpk
4/ Sign 4: Customers complain when your site is down
Nextdoor: "10 minutes after taking the servers offline, I started getting emails/calls from users. What happened to Nextdoor? One user called me in a panic because she needed to contact a neighbor immediately." – @sarahleary
5/ Sign 5: People use the product even when it’s broken
Gusto: "A pretty good sign for PMF was when in spite of the obvious gaps in our marketing, product and care, we saw consistently high NPS (80+), low churn, and record high MoM organic growth.” – @tomerlondon
6/ Sign 6: Consistent and accelerating growth
Datadog: "We started seeing a regular influx of sign-ups, and as we added key features (such as alerting), we saw them use our product more and more actively" – @oliveur
6b/ Superhuman: "I asked our Head of Growth to update all our analytics. What we saw was that every single metric was amazing — growth, DAU/MAU, PMF score, NPS, virality, CAC payback, CAC:LTV, activation rates, long-term retention rates, and so on" – @rahulvohra
6b/ Substack: "We've just been growing fairly consistently, and gradually the how-do-we-keep-up anxiety got bigger and bigger until there wasn't time left in the day to worry about whether we had product-market fit." – @cjgbest
1. Remote jobs are shrinking fast (down 35% from peak)
2. There’s been a shift to hiring more senior candidates
The chart below shows the proportion of open PM jobs by level over time.
If you look at the light blue and dark blue segments below (i.e. Senior and Lead/Senior++ roles), you can see they have definitely grown from early 2023 in the percentage of PMs being hired. In particular, Lead/Senior++ roles are growing their percentage of open roles the fastest. And the share of Entry/Mid-level roles (the pink segment) has decreased the most since early 2023.
3. More than one in five open PM roles is based in the San Francisco Bay Area. The share grew from 15.4% to over 20% in the past two years, and it appears to be growing further.
The rise of product management over the past 25 years.
Huge growth for 20+ years, followed by a plateau over the past couple of years.
This tells us the PM role isn’t going through the hypergrowth it saw earlier this decade, but it’s also not shrinking. This seems like a good and healthy thing all around.
Numbers-wise, there are about 450,000 active PMs in the U.S. right now, and 2,500 to 4,500 are being hired each month.
Here are the top hirers of PM roles over the past few years:
As a comparison, here’s the engineering role over that same time frame—similar growth trajectory, also a bit of a slowdown in the past one or two years, though not as much of a slowdown as PMs. Again, this seems right and healthy.
In most hiring processes, you’re lucky to get 45 minutes to chat with a candidate before having to make a thumbs-up or thumbs-down decision.
How do you use that precious time to get the most important information about the candidate?
For over a year now, I’ve been asking my illustrious podcast guests to share their favorite interview questions (nearly 150 guests now!), and the collection of questions that’s emerged is like nothing I’ve seen elsewhere. These are not just great questions—they are exceptionally good at pulling out the essential insights about the candidate in the least amount of time.
Below, I'll share some of my favorite high-signal-to-noise interview questions, including what to look for in a great answer, grouped by theme. To see the full list, don't miss today's newsletter post (link below).
How to learn the most about a candidate from a single interview question—High-signal-to-noise interview questions inspired by my 150+ podcast guests
Question 1: Talk me through your biggest product flop. What happened and what did you do about it?
“I look for people being brutally honest about how bad it was and why it failed. The rest of the interview, they’re trying to tell you all the wonderful things they did and all the accomplishments they had. And so I think the rawer the answer in terms of how bad it was and why, the better.”
—Annie Pearl, corporate vice president at @Microsoft, ex-CPO at @Calendly
Every startup can be distilled into a simple equation.
And until you can express yours as one, you don’t fully understand your business.
Having this equation gives you a map for understanding your biggest growth drivers, your key inputs and output, and once your teams are aligned behind it, and the equations operationalized, you’ll experience a huge force multiplier—because every team will be focusing their energy on the same (high-leverage) levers.
I teamed up with @danhockenmaier to collect the detailed equations for the eight most common tech business models:
Some of my biggest surprises when researching paths to PMF for top B2B companies:
1. If you build it, they *will* come—if you have strong product-market fit.
Though it often takes years to find initial PMF, once you do, a common pattern across top startups is strong (and explosive) organic growth—primarily seen as cold inbound and word-of-mouth growth.
This was true for Segment, Loom, Dropbox, Canva, Sprig, Stytch, and most others.
2. Stop thinking of product-market fit as a single moment.
It can be, but it almost always isn't.
Instead, think of finding PMF as an ongoing process of finding stronger fit with more and more segments of the market.
Though there will never be a foolproof formula for finding product-market fit, here’s my best attempt at creating a guide for B2B startups that'll save you much time and pain.
It's based on interviews and research into the PMF journeys of 25 top B2B startups.
Here's a peek:
Here's the full post: A guide for finding product-market fit in B2B
Inside: 1. A framework for finding PMF 2. Signs that you’re approaching PMF 3. What to do if you aren’t