Applying the Superhuman Product:Market Fit Eval Engine to Ramblers Way
Applying the Superhuman Product:Market Fit Eval Engine to Ramblers Way

This document applies the product:market fit engine developed by Rahul Vohra, the CEO of Superhuman, to Ramblers Way

This document applies the product:market fit engine developed by Rahul Vohra, the CEO of Superhuman, to Ramblers Way

Michael J.J. Tiffany

Background on the Superhuman engine for optimizing product:market fit

In 2018, Superhuman's unique journey to product:market was documented by its founder on First Round Capital’s widely-read blog:

How Superhuman Built an Engine to Find Product/Market Fit | First Round Review⁠

Rahul’s core insight came from

Sean Ellis⁠

, who ran early growth at Dropbox, LogMeIn, and Eventbrite, and who coined the term "growth hacker". Sean had

found⁠

a leading indicator of product:market fit:

Just ask a user “how would you feel if you could no longer use the product?” and measure the percent who answer “very disappointed.”

Ellis turned this into a robust

customer development survey⁠

. Ellis established a magic number and a clear benchmark: 40%. Companies that struggled to find growth almost always had less than 40% of users respond "very disappointed" — whereas companies that grew most easily almost always exceeded that threshold. And therein was the hint that would become core to this method:

Ask your users how they’d feel if they could no longer use your product. The group that answers ‘very disappointed’ will unlock product:market fit.

In 2020, Superhuman ported this process into an interactive document hosted on Coda, which I have forked to make the version you are reading now.

The process is broken into 5 key steps:

⁠

Survey⁠

to ask our customers "How would you feel if you no longer had your Ramblers Way clothing to wear?"

⁠

Segment⁠

to find supporters and paint a picture of high-expectation customers

⁠

Analysis⁠

to convert on-the-fence customers into fanatics

⁠

Roadmap⁠

of company improvements that double down on what customers love and address what holds others back

⁠

Track⁠

product:market fit over time as our most important metric

⁠

👉
`Survey`⁠
⁠

⁠

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Applying the Superhuman Product:Market Fit Eval Engine to Ramblers WayApplying the Superhuman Product:Market Fit Eval Engine to Ramblers Way

Background on the Superhuman engine for optimizing product:market fit

👉Survey⁠⁠

Applying the Superhuman Product:Market Fit Eval Engine to Ramblers Way
Applying the Superhuman Product:Market Fit Eval Engine to Ramblers Way

👉
`Survey`⁠
⁠