Race to Saturn

Finding Product Market Fit Examples


This page lays out examples of companies finding product market fit—that key milestone at which companies know they are building something that people truly want.



Podium is a messaging tool for local businesses, based in Utah, reaching $100 million in annual recurring revenue and valued at $1.5 billion as of April 2020.

CEO Eric Rea gives a terrific talk about it here, and specifically discusses going after product market fit at about 6:30.

As he describes in that talk: In the beginning, their sole focus was finding product market fit. Specifically: building something people wanted, getting it into as many hands as possible, and having them pay for it.

“At 8am, we would get in the car and we would literally drive around Utah, walking into local businesses and selling them our product. And then in the afternoon what we would do is we would come back to the spare bedroom of my apartment and we would take all that feedback that we got in the morning and actually build it into our product.

So we built this amazing feedback loop. So every day we were getting feedback and actually building that into our product.”

Eric provides some good insight into product market fit: not only does a company need it to survive, but it provides validation that you have something real. And you can rely on that validation when you are faced with internal and external doubts.

Lesson : Podium’s example provides a concrete roadmap that any company selling to local businesses: find local businesses, talk to them, show them your product, encourage them to use your product, get feedback, and iterate. It’s so straightforward, that even startups that aren’t serving local businesses can consider it for their own process of finding product market fit.

Here’s Eric Rea’s full talk (he discusses finding product market fit at 6:30):


Segment provides tools to collect and analyze customer data. Twilio bought it for $3.2 billion in October 2020.

They found product market fit by building an application that they used internally to collect user analytics from different sources. They had open-sourced their tool (they called it Analytics.js), but never figured it would be a real product.

Meanwhile, as CEO Peter Reinhardt discussed here, the founders spent months of coding and raising money for a totally different product (a way for lecturers to get real-time feedback from students during class). When they tested it in classrooms, they immediately saw that it was not a good fit–students didn’t want to use use their tool to talk to professors, they just wanted to use social media.

Then, they pivoted to and spent a year building a super fancy analytics tool. They then realized THAT wasn’t going to work (customers had no interest).

Then, not knowing what to do, one of the founders said: “hey, what about those 500 lines of code we wrote a while back to help us understand data from different existing analytics tools. That we had open sourced already. We use that ourselves. Could that be a product?”

The other founders were (very) skeptical that could be a product. It was open sourced already, it was a very simple idea, and it was not much code.

But they built a landing page, put it on hacker news, and, to the serious surprise of some of the founders, it took off from there.

Lesson : If you make something for your own use, and iterate it for your own use, that can be the basis for a product that the wider market wants.

Here’s Peter’s full discussion (he discusses launching Analytics.js at 10:30):

And he gives a good talk about product market fit here (focusing on his own journey of finding product market fit starting at 16:00).


Superhuman is an email service that claims to be the fastest email experience ever made.

In the early days, Superhuman was able to get about 100 to 200 users from connections: founder Rahul Vohra had previously started and sold a Chrome extension for Gmail to LinkedIn. Rahul also generated attention through creating content: here’s a popular post Rahul wrote about getting acquired, which got attention on the heels of news that a well known acquisition of another email service had failed (Dropbox had previously acquired Mailbox, and was now shutting it down).

But Superhuman had been holding back trying to scale their user-base, because they didn’t have product market fit. Enthusiasm among their users was unclear, and it was unclear what Superhuman’s clear value add would be.

So Rahul developed an “engine” for generating product market fit. The engine started with a survey they sent to their users, with these key questions:

1. Key Question: how disappointed would you be if you could no longer use the product?

Superhuman looked at the responses from this group to get a better sense of who were the people most passionate about their product: those that said they would be “very disappointed” if they could no longer use the product. Rahul describes that product market fit is there when the number of users who say they’d be “very disappointed” is about 40%. Superhumans first response rate on this was about 22%.

Give each of those users a persona, to understand the personas of the people in the group (for Superhuman, the personas in that group were founders, managers, executives and people who work in business development ).

2. Key Question: What type of person do you think would most benefit from the product?

Superhuman looked at the responses to this question from the group that said it would be “very disappointed” if they could no longer use Superhuman. Superhuman understood that many people would use use this “What type of person” question to describe the key traits of themselves that they link to the product.

With the info from (1) and (2), Superhuman crafted a vision of their ideal customer. They personified this customer as “Nicole”, an executive/founder/manager, and gave her an in-depth story.

Here's the story Superhuman formed for Nicole, to give a concrete vision of its ideal user

Nicole is a hard-working professional who deals with many people. For example, she may be an executive, founder, manager, or in business development. Nicole works long hours, and often into the weekend. She considers herself very busy, and wishes she had more time. Nicole feels as though she’s productive, but she’s self-aware enough to realize she could be better and will occasionally investigate ways to improve. She spends much of her work day in her inbox, reading 100–200 emails and sending 15–40 on a typically day (and as many as 80 on a very busy one).

Nicole considers it part of her job to be responsive, and she prides herself on being so. She knows that being unresponsive could block her team, damage her reputation, or cause missed opportunities. She aims to get to Inbox Zero, but gets there at most two or three times a week. Very occasionally — perhaps once a year — she’ll declare email bankruptcy. She generally has a growth mindset. While she’s open-minded about new products and keeps up to date with technology, she may have a fixed mindset about email. Whilst open to new clients, she’s skeptical that one could make her faster.

They then sought to serve the segment, personified by “Nicole”.

3. Key Question: What is the main benefit you receive from the product?

Superhuman then once again went to the survey they had sent to their users, and looked at the responses of the “very disappointed” group to this “main benefit” question.

They looked for common themes in the replies, and found those themes to be: speed, focus, and keyboard shortcuts.

They focused especially on speed, and looked at the group of users who said they liked the speed of Superhuman and had said they would somewhat disappointed if they didn’t get to use the product anymore. Why? These were the “on the fence” users–those who showed they could love the product, but weren’t quite there.

4. Key Question: How can we improve the product for you?

For those on the fence users who cared about speed, Superhuman looked closely at the answers to this “how can we improve” question. They found that these users wanted a mobile app, cared about calendar functionality, and a few other items. Superhuman used these responses to determine the key features they should focus on next.

So they then iterated the product, and then re-sent the same survey back to their users, assessing the results in the same way, and then iterating from there.

This accelerated the process of raising the responses to the first question that said they would be “very disappointed”, and accelerated their achievement of product market fit.


So Superhuman’s engine was a survey that enabled them to see:

  • who would be most disappointed if they couldn’t use the product; this helped the company identify the key groups to focus on.
  • how this group described those who would benefit from the product; this helped the company further refine their focus on a target user group.
  • how this group described their main benefit from the product; this helped the company understand the key value of their product;
  • look at the users “on the fence” (the “somewhat” disappointed group) who also saw that value, and identify what the product could do to better serve those users; this helped the company identify what to build next.
  • iterate from there.

Here’s the full article from Rahul: