Ultimate Blog: Product-Market Fit

Ultimate Blog: Product-Market Fit

Why venture capital funds care about product-market fit

Series A venture capital investors are obsessed with product-market fit. Product-market fit is arguably the most critical milestone for a startup. Very little else (if anything) will convince a Series A venture capital fund to invest if you haven’t found product-market fit.

This is mainly due to the risk you represent as a startup that has yet to find product-market fit.

If your start-up has product-market fit, every additional £1 in capital invested should generate more than £1 in value. This helps ensure a venture capital fund generates a positive return for their investors, rather than making more speculative bets on startups who are still pre-product-market fit. These companies might never actually launch a good product and represent a much riskier investment.

Often the first solution that you offer to the market is not the perfect product. If you are a good founder, you should be ready to innovate in your space consistently until you find the right solution. Until you have found product-market fit you should have no need to raise the large quantities of capital offered by venture capital firms.


Marc Andreessen of Andreessen Horowitz (one of the world’s best venture capital funds) defines product market fit as:

The customers are buying the product just as fast as you can make it -- or usage is growing just as fast as you can add more servers. Money from customers is piling up in your company checking account. You're hiring sales and customer support staff as fast as you can.

To me, this definition focuses on the outcomes that a start-up enjoys once it has already hit product market fit. Your product-market fit has become visible at this point.

In contrast, Dan Olsen (author of The Lean Product Playbook) has a definition that could help investors and founders to identify product-market fit a bit sooner:

You have built a product that creates significant customer value and the product meets real customer needs.

Whilst these definitions aren’t mutually exclusive, I like the second definition more, as you don’t need to already be experiencing the growing pains that come with exponential growth. This is something you as a founder need to try hard to show potential venture capital investors that you have achieved to maximise your chances of raising a Series A round.


Allowing a few early customers to determine the long-term trajectory of your startup is dangerous. Whilst you might be able to monetise these early adopters, they might not accurately represent the greater market demand. You don’t know at the beginning who your best-fit customers will be. It is likely that a large percentage of initial 1,000 users will not be your future target market.

Founders who can hold their nerve and wait until they fundamentally understand what core functionality causes customers to buy their product/service will enjoy far greater long-term success.

Unfortunately for founders, it is easy for a venture capitalist to see when product-market fit has not been achieved:

  • Organic growth of the product is low, as word-of-mouth referrals are limited
  • Customers aren’t delighted with your product
  • Core usage of your product is low and your customer retention problem is growing
  • Media articles on your business aren’t a glowing report on this revolutionary new product/device that is a must-have

Given that there is no set time a founder can set to find product-market fit, I did some research into how long it took high growth very successful startups to find product-market fit:

How long it took successful comapnies today to find their product market fit and what changed.

Twitch Product-Market Fit Story

Y Combinator Twitch co founder Michael Seibel on product market fit

Michael Seibel (Twitch Co-Founder) recalls just how difficult it was to raise additional capital for Justin.tv, which later became Twitch. Even when the company had 30 million monthly active users and $4-6m revenue run rate, they hadn’t truly found product-market fit.

After the founder had spent four unsuccessful months trying to fundraise, Michael and his other co-founders were forced to become profitable. This forced them to reduce their bloated fixed costs and within two months they went from burning $250k a month to making $100k a month.

This fundamentally changed the trajectory of the business, as the start-up went from imminent bankruptcy to being profitable. Their survival was no longer reliant on outside capital and their runway was extended infinitely to maximise their chances of finding product market fit.

However, this wasn’t the genius that enabled Justin.tv to find product market fit. That came when the team analysed their user data. They discovered a small niche group of gamers that had outlier-type watch times when compared to their average users. Luckily for the team, this customer segment was utilising the product in a legal way. At the time there were plenty of illegal use cases including movie streaming to name just one.

The team discovered within their user data analysis that this population of gamers really loved the ability to watch each other play games in a live forum. Just for context, YouTube/Instagram live had not yet launched. Twitch really was the one place where gamers could do this well.

The Twitch team chose to build on this momentum and built a really great product centred on these specific customers. This eventually led to Twitch finding product-market fit and achieving an exit of $1bn when they eventually sold to Amazon.

How Superhuman found product-market fit

Superhuman GIF showing product market fit progress over time

Superhuman rebuilt the email inbox to help their users get to inbox zero every day. They offer a far superior product to Gmail, which enables them to charge $30 per month!

Rahul Vohra is the founder of Superhuman and like the team at Twitch, he also decided to take a data-led approach when trying to find product-market fit. However, rather uniquely, Rahul managed to reverse engineer his product-market fit.

Given the core functionality of Superhuman is quite basic (an email server), Rahul had to add features to this core service that would help the overall product experience achieve product-market fit with his users. He discovered that one of the most effective ways to measure product-market fit with a leading indicator was to simply ask his users:

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

You can measure the results of this question in a quantitative manner by measuring the percentage of users that answer with “very disappointed”.

Armed with this new leading KPI for product-market fit, which was an insight from Sean Ellis who ran growth teams at Dropbox and Eventbrite, Rahul asked what is the benchmark for companies that have achieved product-market fit?

Sean and Rahul did some research and found 40% to be the magic number. Startups that went on to become outperformers had 40% of their userbase respond that they would be “very disappointed” if they could no longer use the product in question.

Rahul then embedded this KPI into the company culture. Every two weeks the team would poll new users who had used the product twice in the last two weeks this very question.

“how would you feel if you could no longer use the product?”

The first-ever customer survey Superhuman ran to identify their progress towards product-market fit showed that 22% of their total users responded to their survey by saying that they would be very disappointed. This was the actual list of questions they used:

The actual survey used at Superhuman to hack product-market fit and turn it into a leading measurable indicator.

However, simply measuring yourself against this average score is not necessarily indicative of your progress. Rahul knew that some customer segments would respond differently, so he asked the team to give all their customers a persona. This would allow them to identify the customer segment that found Superhuman the most valuable.

This changed the results quite a lot:

Superhuman customer survey to reverse engineer product-market fit survey results with customer profiles.

At the start, you may not know who your best-fit customers will be. As such a lot of your initial users could actually be bad fit customers for your product. Segmenting your customer base like Superhuman did should help you to avoid trying to build a product for these customers. As you can see, it’s not as easy to simply respond as the founder to what the majority of your users say.

Be bold here, identify the people who love your product and double down on meeting their needs.

When analysing the customer survey results, the Superhuman team ignored users who responded in any other way than “very disappointed”. They analysed the responses of the users in this group to the question: “What is the main benefit you receive from Superhuman?” and got the following:

A word cloud of survey results Superhuman used to analyse what their customers loved about their product to reverse engineer product-market fit.

This is a great idea, as it allows your marketing efforts to focus in on these attributes and attract better-fit users to the product. Whilst this is useful to identify new customers who will be good fit users for Superhuman, it does little to help the team identify new product features that would enhance the stickiness of Superhuman to these users.

If this marketing tactic resonated with you, I highly recommend reading Finding language-market fit to make your customers think that you have read their minds” by First Round Capital.

When identifying the product features that your users are asking you to build, be careful who you ask. The team at Superhuman decided to focus on users who responded to their survey; “somewhat disappointed”. This population reflects the users who could potentially be converted into core users with some additional product enhancements. The team analysed the answers of this group to the question: how can we help improve Superhuman for you? They got the following results:

This is word cloud of Superhumans' customer survey for users that revealed the best new product features to develop to further improve product-market fit.

From this survey it became clear what the team should do. Their main priority needed to be developing a mobile app. Additional features, such as calendaring stood out to the team. This was low down on the initial build list, which the team had based on their own thoughts and opinions. However, here was definitive user data showing just how important users felt this feature was. So, the team responded and made it a priority.

To prioritise what features to build first, the team ranked each by cost to develop and impact to their product-market fit score. It’s also important to still develop your core features that is so loved. Rahul’s advice is to:

To increase your product/market fit score, spend half your time doubling down on what users already love and the other half on addressing what’s holding others back.

If you ignore the core competencies that got your initial users so excited by your product and solely focus on additional product features, you can lose your product-market fit. Customers’ needs and wants are constantly evolving, as are your competitors. Expect your product-market fit demands by customers to evolve over time.

For Superhuman, this approach of spending half their time on new features and the other on doubling down on their core competencies really worked. After completing 75% of the book of work that was derived from these customer surveys, the team had grown their average product-market fit score from 22% up to 58%!

Rahul identified that for a new feature to achieve product-market fit, it needs to achieve the following:

  1. Retention for that specific feature
  2. Scalable adoption for that feature
  3. It improves retention, engagement, and/or monetization for the core product

The last point is key. Not only do the products they’re building need to be used regularly and attract their own usage to be successful, but they also need to make the whole of the product experience better.”

Additional Reading:

For more reading on how other famous start-ups achieved product-market fit, I have taken some of the best examples from a blog in Lenny’s Newsletter. You can find his original article here.

Gusto startup how it achieved product-market fit case study.

“As a founding team, we are pretty self-critical and tend to focus on how we can improve things for customers, or what’s broken and how to fix it. So I think I only realized it 2-3 years after it happened. In retrospect though, 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.”

— Tomer London, co-founder

PagerDuty startup case study on how they achieved product-market fit

“I can’t recall a specific moment in time when it clicked and we said we had product-market fit. Instead, it was more of a transition where our confidence that we had reached PMF grew over time.

We launched the beta version of PagerDuty in the summer of 2009 and the paid version in Dec 2009. That early version was very much an MVP oriented around alerting; it didn’t even have the concept of incidents and incident tracking where you could track multiple incidents (issues) broken at the same time. We quickly realized that and added the concept of incident tracking in early 2010.

Throughout 2010 and 2011, we saw exponential month over month growth… if I remember correctly >10% month over month growth in 2011. (Keep in mind, that growth was on a small base… I believe we hit $1m in ARR sometime in 2011). By the middle of 2011, we felt pretty confident we had product-market fit, as we were solving a real hair on fire problem with the platform (namely, ensure critical issues were handled quickly and no critical issue would fall through the cracks and impact customers and the business for an extended period of time) and seeing that consistent exponential month-over-month growth.”

— Alex Solomon, CTO and co-founder

Instacart high growth venture capital backed startup. Case study on how they found product-market fit.

For Instacart, product-market fit happened across a series of moments. we found product-market fit very early on with people who wanted groceries delivered as soon as possible and didn’t care which store they came from. This made us feel like we had achieved product-market fit but it was only with a small sub-segment of customers.

The average customer wanted to shop from their favorite grocery store. So, we formed partnerships with top retailers. As a result, customers started to seek us out and word of mouth grew. We then signed more partnerships, reached a larger scale with customers, and in turn attracted more partners.

Ultimately we created a marketplace where most customers can shop from their favorite stores, and as a result, customers have a great experience using Instacart and want to share it with their family and friends.

Initial signs of product-market fit feel a bit like a calm breeze, while true product-market fit feels like a powerful wind at your back, accelerating you forward and compounding over time.

ー Max Mullen, co-founder

Robinhood (high growth venture capital-backed startup) on how it found product-market fit.

“I remember distinctly it was a Friday night. We had been working on the wait list in preparation for our press launch, which would have been, I think, the following Wednesday or Thursday. Everyone goes home, and I wake up Saturday morning, and I open up Google Analytics, and I see something like 600 concurrents on our site, which nobody knew about at that point. I was just like, ‘What’s going on? This is not normal. Something must be wrong. Right?’

I’m just screenshotting the page; I’m calling my parents saying, “Oh, this is crazy. It might actually be working.” And up until that point, we never really had an idea of what success, at least in the consumer space, was like. That was sort of the first moment where we built something that actually worked.

We ended up getting 10,000 sign-ups that first day, over 50,000 the first week, and almost 1 million in the first year.”

ー Vlad Tenev, CEO and co-founder (source)

Uber logo on how they found product-market fit as a high growth start-up.

“Uber never really had a product market fit problem — zero marketing budget and we were growing like a weed. Word of mouth was uncontrollable, and especially as regulatory heat started it’s all anyone could talk about (is how it felt). Marketing was free because media loved the story.”

— Ryan Graves, first CEO, founding team

Good video resources:

  1. If this all comes a bit too early in your entrepreneurial journey, then Mauria Finley (Founder of Allume) did a great video lecture recorded by True Ventures about how to find product-market fit at the minimum viable product stage. Find the video here.
  2. Y-Combinator videos on product-market fit by Michael Seibel here (8.5 minutes), here (13 minutes).


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