Finding Product Market Fit at Segment

Reinhardt’s team applied to YC with a tool for students to signal when they were confused during lectures. After building it and raising about $600,000, they saw students turn to Facebook instead of using it. Investors encouraged the team to try another idea, so they built an analytics product, but struggled to win customers already using established tools.

While building the classroom tool, the team wrote a small library to send customer data to several analytics services. They later open-sourced it as a way to address objections to their analytics product, and developers began using and contributing to it. After a debate among the founders, they tested interest with a landing page on Hacker News, where the library took off.

Reinhardt describes product-market fit as a point where customers use a product and pull it in directions the team did not expect. Requests from people who are already using a product are a stronger signal than feedback from people who never adopt it. Later, interviews with five customers revealed that they all moved Segment data from S3 into Redshift, prompting the team to build a direct connector.

When founders disagreed about the library’s potential, they chose a cheap landing-page test to get evidence quickly. Reinhardt says interviews taught the team more than the page did. He recommends asking detailed questions about a customer’s problem, costs, decision process, and current workarounds, rather than relying on a polished demo or vague expressions of interest.

Reinhardt says teams benefit from skeptics who work with optimists to design fast, reasonable tests. Segment later formalized four values: karma, tribe, drive, and focus, and used them in hiring, feedback, promotions, and performance reviews. He also recalls hiring experienced leaders in engineering and people operations around $10 million in revenue, which he felt should have happened earlier.