Why Your Startup Needs a Product-Market Fit Metric

I Got 99 Problems, but Product-Market Fit Ain’t One

For early-stage businesses, product-market fit is an obsession. Evidence of it has become an investment requirement for many Seed and Series A VC funds. It makes sense from an investor’s perspective; take a look at data from CB Insights as to why startups fail, and you’ll see that “No Market Need” tops the list, accounting for over 40% of startups that close their doors.

It’s clear that finding the proverbial product-market fit is critical; however, it is unclear what exactly finding it means. If you scour the internet, you’ll find countless blog posts providing trite descriptions.

“I’ll know it when I see it.”

“The dogs are eating the dog food.”

“You can’t keep up with demand.”

“It’s obvious when you have product-market fit, and it’s obvious when you don’t have product-market fit.”

In my four years in venture capital, I’ve been just as guilty of using broad and unhelpful descriptions of product-market fit when providing feedback to entrepreneurs. I would regularly pass on an opportunity citing a lack of evidence of it, but when the founder would fairly question what I needed to see, I couldn’t name a specific growth rate, number of customers, or monthly recurring revenue figure that would tip the scale.

Point blank: I couldn’t quantify product-market fit.

For entrepreneurs, the inability to quantify product-market fit is incredibly frustrating. Not only might it be a barrier to raising capital, but as the old adage says, “If you can’t measure it, you can’t improve it.” What’s more — product-market fit is not binary. A startup cannot simply achieve product-market fit and then rest on its laurels while growing its way to unicorn status. New competitors will enter the market, your product team will release new features, and macroeconomics factors will shift your customers’ needs and budget — all of this and more will impact product-market fit. Based on this constant fluctuation, entrepreneurs and investors need a way to not only quantify product-market fit, but to track this metric over time and with different customer segments.

Enter Sean Ellis, an early employee at Dropbox, LogMeIn, and Eventbrite who has spent his career focused on growing early-stage businesses. Sean developed a framework to quantify product-market fit and track it over time. Using the framework, a company poses one key question to its customers:

“How would you feel if you can no longer use the product?”

Ellis argues that a leading indicator of product-market fit is the percentage of customers that respond “very disappointed” when asked this question. If more than 40% of a company’s customers respond this way, Ellis believes the company has found true product-market fit. By regularly asking this question of its customers, a company can track its progress towards product-market fit across different customer segments, geographies, and products.

In a Medium post about his framework, Ellis reflects on the benefits of a leading, rather than lagging, indicator of product-market fit.

Scaling growth before having product-market fit is the fastest way to kill your startup. But it may be an even bigger tragedy to have product-market fit and miss the opportunity to successfully scale growth…Without the survey, I would either have to rely on gut feeling or wait for retention cohorts to mature to see if we had sufficient customer retention to support sustainable growth. This could delay aggressive growth acceleration execution for several months.”

When TechNexus portfolio company CEO Seth Miller came across a case study of Ellis’s product-market fit framework, he knew it could be helpful to understand his company’s product-market fit. Miller is the CEO of Rapchat, a mobile app that allows users to record songs on their phone using the app’s library of free beats. Rapchat hopes to provide wider distribution and listenership for artists while enabling beginners to more easily create their own songs on their phone using vocal effects and other cool tools. Like any B2C company, the Rapchat team is constantly refining its product and working to understand the needs of its core customer.

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The company has had over 4 million users (mostly 13–28 year olds) that have created over 10 million songs and listened to 375 million tracks. These numbers alone could be seen as initial indicators of product-market fit; however, the Rapchat team viewed Ellis’s framework as a solution that they could use to monitor product-market fit across time and customer segments.

Rapchat sent out a quick, seven question survey to its users. Our team at TechNexus helped Rapchat comb through more than 1,000 responses, coding the free responses and cutting data by customer type. High level results are depicted below.

How you would (honestly) feel if you could no longer use Rapchat?

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43% of users surveyed responded that they would be “Very Disappointed” if they could no longer use Rapchat. This was a great sign for the Rapchat team — Remember, Ellis’s threshold for product-market fit was 40%! As we dug further into the data, we learned more — there was a meaningful difference in this sentiment between Android and iOS users. Cutting the data in different segments can help the team to prioritize its product development and marketing strategies in the future.

What would you use if Rapchat was no longer around?

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“Our next step was somewhat counterintuitive: we decided to politely pass over the feedback from users who would not be disappointed if they could no longer use the product.”

— Superhuman CEO Rahul Vohra

We decided to follow Vohra’s logic to interpret our subsequent questions. The data you see above and below is only from customers that responded “Very Disappointed” to the initial question. A quick competitor question (above) provided insight into the closest comparables currently in the market. An open-ended request for app improvements (below) helped the Rapchat team to prioritize (and perhaps more importantly, deprioritize!) its product development plan.

Help us make the app better.

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In reflecting on the exercise, Miller commented,

“The results we received from the PMF engine were super encouraging. Not only did we hit the 40% threshold, but it also confirmed that we’re working on the right features for the right customers. We’ve spent a huge chunk of time this year on a very big update that will be launching soon, and it was reassuring to know that a lot of the requested features from the survey are in this update. Furthermore, this entire process helped clarify our mission and why we do this in the first place — to democratize music creation and to be the easiest way to make music on your phone.

Lastly, it was great to share these results with our team and our investors. It adds context to the startup grind when you’re seeing real feedback from real customers who love your product. We plan to evolve the engine and use it at a minimum every month to help keep us on track.”

Our team at TechNexus was excited by these results and the ease of use of the general framework; we’re planning to work with many of our other portfolio companies to repeat this exercise.

Do you have a preferred framework or technique to measure and improve your product-market fit? If you’re working on quantifying and refining your product-market fit, we’d love to talk through your methodology. Don’t hesitate to reach out!

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