GoKawiilUser research “in the wild” can, like an actual safari, lead to surprises and learnings.
If you’re an early-stage startup founder, learning velocity is critical. Being able to test and reject or double-down on hypotheses to help you establish if you’re building the right business and product for the right customer and market is essential.
When you’re in the wilds of pre-product market fit and navigating the idea maze, you need ways to orient and learn whether you’re going down the right path – or about to hit a dead end.
Why I’m Writing About Gathering Qualitative User Feedback
While The Mom Test book by Rob Fitzpatrick is an oft-referenced and useful resource, I thought I’d share a bit about how I’ve approached getting feedback on early explorations as a founder for CodeYam and over the previous decade while working at technology startups. This is a practice I’ve honed over time and I’m still constantly learning, improving, and experimenting.
This journey began when I discovered the Design Sprint book and process developed by the team at GV while working at a startup called Kamcord roughly circa 2017. On and off (as needed) over the years since then, I have been using variations of that process, along with the accompanying GV Research Sprint created by Michael Margolis, to help get unstuck, speed up learnings, and test out new ideas in low-risk ways.
One of the first sprint timelines at Kamcord, circa May 2017.
If you worked at a larger technology company, “design sprint” often comes with a very different set of connotations; you might imagine designers blocking off a week (or more!) of time on the product and development team calendars and spending it working on ideas that, while fun or interesting, are never going to be priorities to build. This whiteboard whimsy that leads to no real results is the opposite of what I’m talking about, and using facets of the sprint process to accomplish, here.
Instead, we’re trying to get real feedback from potential customers and/or users of a product (or that might be users of a potential future product that hasn’t yet been built). We are trying to get relevant feedback from a small, representative group as fast as we can to test our risks, hypotheses, assumptions, and to inform how we successfully meet our goals (or fail faster and move on with the learnings).
A Note on Using AI Tools for User Research
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