What problem does it solve? It helps teams improve the proportion and quality of users completing a defined business action by diagnosing funnel friction, separating evidence from hypotheses, and designing valid experiments instead of guessing at design changes. ## Core Features & Use Cases - Funnel and Landing-Page Diagnosis: Maps the full journey from traffic source to follow-up, reviewing message match, offer clarity, CTA visibility, trust signals, forms, and checkout friction with explicit evidence-state labels. - Hypothesis and Experiment Design: Builds structured CRO hypotheses, prioritization backlogs, and test specifications with primary metrics, guardrail metrics, decision rules, and technical QA requirements. - Test-Result Interpretation: Reviews supplied experiment results for data quality, segment differences, and guardrail conflicts, classifying outcomes as adopt, iterate, retest, reject, or inconclusive. - Use Case: A marketing team suspects their consultation-request landing page underperforms. The skill defines the conversion event, reviews the supplied page and analytics export, produces prioritized friction hypotheses, and drafts an A/B test plan with guardrails for lead quality. ## Quick Start Ask the AI to review your landing page or funnel and produce a prioritized CRO improvement plan with hypotheses, metrics, and an experiment backlog.
