Build–Measure–Learn
Create
Experiment with your ideas.
A health tech startup wanted to reduce no-shows for virtual therapy sessions. Their hypothesis: sending personalized reminders would improve attendance. They built a quick MVP—just a basic text tool that pulled names and appointment times from a spreadsheet. For two weeks, half of the users got standard reminders, and half received the personalized ones. The team measured attendance rates and follow-up responses.
Steps
Define what you want to learn. Create a hypothesis based on assumptions or past learnings. Plan a small, focused experiment to test it.
Use this structure: We think that doing [action] for [people we want to help] will lead to [what we want to happen]. We’ll know it’s working when we notice [signs or proof it’s working].
Build a simple Minimum Viable Product or feature variation that can test your hypothesis with minimal effort and time.
Measure relevant data through analytics, user testing, or interviews. Be clear on what success or failure looks like before measuring.
Sort and review the data to find trends, insights, or surprises. Compare it to previous cycles when possible.
Learn and decide next steps:
Pivot (change direction)
Persevere (move forward)
Repeat the cycle. Start again with a new idea, or a refined version of the last.
Based on the ideas of Eric Ries (2011).
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