pmf-research-synthesis

To prioritize product-market fit risks, you can synthesize market research and expert input to calculate quantitative risk scores across six PMF dimensions, identifying the single riskiest assumption that requires immediate validation.

The best way to refine a product hypothesis is by synthesizing evidence from analogs and antilogs, which updates your V1 narrative to V2 and guides your next validation steps based on potential failure impact.

Identifying the riskiest assumption requires calculating a quantitative risk score for each PMF dimension based on evidence quality, pinpointing the specific dimension most likely to fail and prevent wasted development effort.

Yes, you need an existing V1 narrative and market research synthesis to assess PMF risk dimensions, while optional expert notes can further refine the risk prioritization report and narrative update.

You should update your product narrative from V1 to V2 after synthesizing market research data, using the calculated risk scores and dimension prioritization to pivot or refine your core product hypothesis.

Risk score calculation for hypothesis validation depends on the quality of existing market research and expert notes, meaning incomplete evidence or missing V1 narrative data will limit the accuracy of dimension prioritization.