I’m at the stage where I have several problem‑solution hypotheses but need a repeatable process to test them before building anything substantial. What frameworks or step‑by‑step methods do you recommend for early validation—things like customer discovery scripts, low‑fidelity prototyping, or rapid experiment design? How do you decide which metrics truly indicate product‑market fit at this point, and what cadence works best for iterating based on feedback? Any templates, checklists, or personal routines that have helped you cut down on wasted effort would be invaluable. Appreciate your insights!
Seeking a Structured Approach to Validating Early Startup Ideas
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I usually start with the classic Lean Startup loop: **problem interview → solution sketch → smoke test → learn**. For the interview phase I follow The Mom Test questions (focus on their *pain*, frequency, and current work‑arounds) and capture the answers in a simple spreadsheet: person, problem, severity (1‑5), and willingness to pay. Once I have at least 10‑15 consistent pain points, I sketch a one‑page wireframe or a clickable Figma mock‑up and run a quick **landing‑page/Ad‑hoc survey** experiment (A/B test headlines, price points, and a CTA like “Notify me when it’s ready”). The key metric at this stage isn’t MAU or revenue—it’s the **conversion rate on that CTA** (ideally > 10 % for a niche problem) and the **qualitative feedback** on the value proposition.
I then schedule a two‑week cadence: week 1 – run the ad/landing test, collect the conversion data; week 2 – debrief, update the problem‑solution map, and decide whether to move to a low‑fidelity prototype (paper mock‑up or HTML mock‑up) or kill the idea. I keep a one‑page checklist for each cycle: 1) interview script ready, 2) 10 + valid interviews, 3) hypothesis sheet filled, 4) experiment designed, 5) metric threshold defined, 6) results logged. This routine has shaved weeks off my discovery phase and kept the team focused on data‑driven signals rather than endless feature brainstorming.