How Superhuman Built an Engine to Find Product/Market Fit
by Rahul Vohra
I highly suggest consuming the full piece here (21 min. read time)
“We’ve all heard that product/market fit drives startup success — and that the lack thereof is what’s lurking behind almost every failure.” — Rahul Vohra (Founder & CEO of Superhuman)
“If, after launch, revenue isn’t growing, raising money is tough, the press doesn’t want to talk to you and user growth is anemic, then you can safely conclude you don’t have product/market fit.” — Rahul Vohra
Sean Ellis, who ran early growth in the early days of Dropbox, LogMeIn, and Eventbrite and later coined the term “growth hacker.” Ellis had also found a leading indicator to know whether you have PMF or not: “just ask users ‘how would you feel if you could no longer use the product?’ and measure the percent who answer ‘very disappointed.’”
To achieve this, Rahul says to ask these 4 questions:
- How would you feel if you could no longer use Superhuman?
- Very disappointed
- Somewhat disappointed
- Not disappointed
- What type of people do you think would most benefit from Superhuman?
- What is the main benefit you receive from Superhuman?
- How can we improve Superhuman for you?
All you need is 40 users to answer those questions truthfully (more is better, though). And the goal is to get 40% of users to feel “very disappointed” if they were unable to use your product again. This is the key to know whether you’ve reached PMF or not.
If you fall underneath that 40% threshold, then you’ll need to optimize your product/market fit engine. Rahul goes into great detail in his piece, but here were his main points:
- “Segment to find your supporters and paint a picture of your high-expectation customers.
- Analyze feedback to convert on-the-fence users into fanatics.
- Build your [product] roadmap by doubling down on what users love and addressing what holds others back.
- Repeat the process and make the product/market fit score the most important metric.” — Rahul Vohra
“Investors advising early-stage teams should avoid pushing for growth ahead of product/market fit. As an industry, we all know that this ends in disaster, yet the pressure for premature growth is still all too common. Startups need time and space to find their fit and launch the right way.” — Rahul Vohra
“…it’s better to make something that a small number of people want a large amount, rather than a product that a large number of people want a small amount.” — Rahul Vohra
My two cents: I’ve never seen/heard of a product/market fit optimization engine before, but it’s most likely because I’ve never worked for a real tech company before. The way Rahul explains it makes it seem like optimizing for product/market fit is so easy, although I personally know it’s a lot harder to execute (especially if your product is still subpar). Nonetheless, this framework is too fascinating to not give it a try.
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