Hypothesis Backlog Template for User Research

10-20 active hypotheses is a healthy range for most teams. Fewer than 10 suggests you are not capturing enough unknowns from your research. More than 30 means you are not testing or retiring them fast enough. The backlog should feel manageable, not overwhelming. If it grows too large, archive low-priority hypotheses (Impact score 1-2) and revisit them quarterly.

A product backlog contains solutions (features, user stories, tasks). A hypothesis backlog contains beliefs that need evidence. The hypothesis backlog feeds the product backlog: once a hypothesis is validated, the solution that addresses it becomes a product backlog item. Think of the hypothesis backlog as the "why should we build this?" layer that sits above the "what should we build?" layer.

Any tool that supports a table or board view works. Notion databases, Airtable, Linear (with custom fields), or even a Google Sheet are all fine. The tool matters less than the habit. The key requirement is that each hypothesis has fields for evidence level, risk score, and status. Some teams use a Kanban board with columns for Active, In Experiment, Validated, and Invalidated. Others prefer a sortable table ranked by risk score.

Start small. In your next sprint planning, pick one planned feature and ask: "What assumptions does this feature rest on?" Write them as hypotheses. Design one quick experiment (a 5-person interview round, a data pull, a fake door test). Share the result at the next standup. When the team sees a hypothesis get invalidated (saving them from building something users do not want), the value becomes obvious. The [Product Discovery Handbook](/discovery-guide) has more guidance on building a discovery culture.

Absolutely. Engineers often have hypotheses about technical feasibility and performance. Designers have hypotheses about usability and information architecture. The hypothesis backlog should be a shared artifact, not a PM-only document. In weekly reviews, invite the full product trio (PM, designer, engineer) to add and discuss hypotheses. The broader the input, the fewer blind spots. ---