Curated Resource ( ? )
Rahul Vohra Shares Superhuman's Product Market Fit Framework & Tool
Curated:
17/01/2021 from
firstround.com/review/how-superhuman-built-an-engine-to-find-product-market-fit/
my notes ( ? )
How to measure & optimise for product/market fit? Use this leading indicator: "just ask users “how would you feel if you could no longer use the product?” and measure the percent who answer “very disappointed.” " You need at least 40%.
Article goes through the process step by step, and comes with an interactive tool:
A) Ask people who've used the product 2x in past week. 4 questions
- how would you feel if you could no longer use
- what sort of people would benefit most
- what's the main benefit
- how can we improve it for you?
Assign personas. Focus only on responses from personas who dominate the 'very disappointed' answer to (1). Look at their answers to (2) and describe your high-expectation customer (HXC). Focus on them, because:
"you can either build something a large number of people want a small amount, or something a small number of people want a large amount. Choose the latter. "
Use (3) to identify why the first group love the product - eg "speed".
Filter the somewhat disappointed respondents ("maybe with some tweaks you can convince them to fall in love") for respondents who mentioned that characteristic (eg "speed"). What's holding them back? Look to their answers to (4).
Focus roadmap: "If you only double down on what users love, your product/market fit score won’t increase. If you only address what holds users back, your competition will likely overtake you... [so] spend half your time doubling down on what users already love and the other half on addressing what’s holding others back."
Read the Full Post
The above notes were curated from the full post firstround.com/review/how-superhuman-built-an-engine-to-find-product-market-fit/.Related reading
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