A couple of years into building my first startup, we had paying clients that fit our ideal customer profiles, a great tech team, and had hired our first sales rep. On top of that we had some good vanity metrics - raising a seed round, winning national pitch competitions, getting into a great accelerator, and securing grants from the Gates and the MacArthur foundations. At the time, it sounded a lot like we had the beginnings of product-market fit.
Spoiler alert: we didn’t.
Turns out, we’d gone too long doing things that don’t scale. 1) Even though customers were willing to pay, it took too long to onboard and service them. 2) The amount of product customization we built to fit each client's needs ended up bloating our tech. That added up to a linear model that only scaled with the number of our account managers. Not something you can raise a Series A around.
It also turns out that I wasn’t alone - and ten years later we still hear stories on a weekly basis from founders and investors about startups who have burnt hundreds of thousands of dollars and years of hard work on the wrong customer or product based on the wrong signals.
We get it. For any founder whose paying customers are asking for more features, it’s really hard to question whether or not they’re the right customers. If you’ve got signs from a certain type of customer, spending time on anything except selling to them just feels wrong - but making time to continuously test your product and growth hypotheses is the most effective way to optimize for success. It hones your value prop, focuses your growth efforts, optimizes pricing, and de-risks investment in tech and growth.
In my case, we should have been doing the hard thing and telling those first customers “not yet” until we proved that the feature requests solved big enough pain points for other customers. It shouldn’t take the majority of a founder’s focus, but it should be consistent - we recommend spending 80% of the week closing more leads that match your initial ideal customer profile and 20% (a day per week) conducting customer discovery around new segments and calculating the ROI of your next feature.
After being a part of building other growth stage companies (one of which made it through acquisition), leading corporate innovation/venture programs for Fortune 100s, helping run five accelerator programs, and working closely with 50+ founders over the last few years with Further Faster, one of biggest mentality shifts that we can make as early-stage startup builders and investors is to stop talking about product-market fit like it’s a one-time event (and Ben Horowitz agrees with me 😉).
Product-market fit isn’t something you find or get - it’s something you do.
Product-market fit is a verb. And to achieve scale, it’s something you have to make a habit of doing over and over on a daily basis for the life of your company - making iterations an organizational habit for everyone on your team as you scale. If you don’t iterate, Brad Feld has a friendly reminder about what can happen - “I’ve been involved in companies that thought they owned the market at a $2M MRR only to have a new competitor come out of nowhere and beat the crap out of them.”
$2M a month probably felt a lot like product-market fit…but market conditions and customers change, the person championing you at your anchor client gets a new job, the competition figures out how to make a better version of what you’re doing. Even if you’ve found product-market fit once, it’s probably already changed - which means you have to change too.
It can’t be put more clearly than Sam Altman tweeted - “The number one predictor of success for a very young startup: rate of iteration.”
Founders don’t need more theory around what product-market fit is. Lots of people way smarter and more successful than me have defined it (here, here, and here). Everyone’s read The Lean Startup, and everyone knows that CB Insights report on how most startups fail because they don’t have product-market fit.
We hear that founders do need more tactical support on quickly and cheaply testing their hypotheses to prove out feature roadmaps and pricing models. They need a sounding board of someone who’s been there before to give them confidence in which techniques to use and how to apply them to their specific business with the limited time and resources they have. That’s what we love doing most and why we built Further Faster.
For more “minimum viable test” frameworks around measuring pain points, setting pricing, prototyping positive ROI features, and growing towards your Series A, follow our newsletter.
To chat about what you’re building, feel free to find time to brainstorm with me here.