evidence-review

Evaluating customer discovery interview evidence involves analyzing an evidence log across five dimensions to identify confirmation bias, leading questions, and signal quality. This process assigns an Evidence Quality Score to determine readiness for advancing to Lean Canvas routing.

An Evidence Quality Score is a composite metric generated by adversarially auditing interview evidence. It assesses confirmation bias, leading questions, signal versus noise, willingness-to-pay signals, and pattern recognition to produce actionable feedback for Stage 3 readiness.

Checking willingness-to-pay signals requires auditing your interview evidence log for concrete monetary intent. The evaluation extracts specific quotes and assesses their strength to produce a structured breakdown of viable monetization data.

You need an evidence review before creating a Lean Canvas when determining if customer discovery data is robust enough. The review audits for bias and gaps, assigning a readiness verdict to decide whether to proceed with Lean Canvas routing.

The best way to identify leading questions is through an adversarial audit of your interview evidence. This review flags leading questions and confirmation bias, producing a structured artifact with specific quotes and recommendations to update your evidence log.