This article was first published in 2020.
This podcast uses two successful product launches as case studies to demonstrate the various aspects of discovering product-market fit: 20VC: Superhuman’s Rahul Vohra on How To Measure Product-Market Fit, How To Construct A Process To Increase It & How To Implement A Strong Feedback and Reporting Cycle To Sustain It
Rahul Vohra founded Rapportive (a Gmail extension which was acquired by Linkedin for about $15M) and then Superhuman (an email experience faster and more user-friendly than Gmail).
There is so much good material that we had to listen to this multiple times. We have identified some of the key highlights and resources mentioned in the podcast so you can quickly access them after listening to the episode.
Qualitative definitions are trailing indicators
(audio: 8:45 - 10:35)
There are several good descriptions of product-market fit. However, they describe what happens when you have achieved product-market fit and not how to get there or gauge progress. For example:
Paul Graham, Co-Founder of Y Combinator: You have product-market fit when you have made something that people want.
Sam Altman, President Y Combinator: When users spontaneously tell other people to use your product.
Marc Andreessen, Co-Founder Netscape, and VC firm Andreessen Horowitz: 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 get the idea).
Measuring Product-Market Fit
(audio: 10:35 - 13:40)
It is crucial to measure product-market fit so you can gauge your progress and determine your success/failure. A predictive approach is needed.
In the podcast, they outline an innovative system devised by Sean Ellis, and it can act as a leading indicator. Ask your end-users the following question:
How would you feel if you could no longer use our product?
And provide them with three choices for their answer:
Very Disappointed | Somewhat Disappointed | Not at all Disappointed
After studying hundreds of companies, Ellis discovered that those who had at least 40% of their users respond with Very Disappointed had product-market fit.
Suggested resources for more information:
Using Product/Market Fit to Drive Sustainable Growth by Sean Ellis
Product/Market fit survey tool by Sean Ellis and GoPractice
Segmenting the User Base
(audio: 13:40 - 26:00)
To better understand his user base, Rahul added three additional questions to the survey at Superhuman:
How would you feel if you could no longer use Superhuman?
What type of people will most benefit from Superhuman?
What is the main benefit you receive from Superhuman?
How can we improve Superhuman for you?
Few companies will achieve the 40% threshold in the early iterations. You first have to understand who the people are who really love your product. Superhuman relied on Julie Supan’s High-Expectation Customer Framework (HXC). This framework involves determining your most discerning person within your target demographic who enjoys your product for its greatest benefits. They will spread the word, and others will aspire to emulate them. And the elegant aspect of these questions is your HXCs will provide you with the precise language that will make your marketing material resonate with your audience.
Rahul discusses the process of finding the segment of users who are on the fence but are more apt to be converted into fanatics. This exercise will involve politely disregarding feedback from users who did not resonate with the main benefits from question one above. You then ask this segment how the product can be improved for them, since something small may be holding them back. This, in turn, will improve your product-market fit score.
To improve your score, Rahul recommends the following:
Spending half the time doubling down on what end-users love
Spending the other half systematically addressing what holds end-users back
Ideally, you have at least 40-50 responses to the survey, and naturally, a few hundred is better.
Editorial Note: Another approach is the Net Promoter Score which uses just one question. This may be a better option when the number of users is small and you want to make it very easy for users to answer the survey.
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