Product Recommendations | Audit and Experimentation Prompt

What this prompt helps you do

Audit an existing page, process, dataset, or asset, separate facts from assumptions, and turn the highest-priority issues into tests with baselines, metrics, and stop conditions.

Prompt text

Act as a ecommerce personalization and recommendation strategist and audit the current [Page/Process/Data/Asset] related to the objective: design recommendation strategies that balance user intent, inventory, and margin constraints. Materials: [Browsing and purchase history], [Product attributes], [Inventory and margin], [Customer segments], [Placement on page]. Classify findings as Blocking, Major, Moderate, or Optimization, and quote the evidence that triggers each finding. Provide: (1) an issue list; (2) Recommendation use cases, Candidate rules, Exclusion rules, Explanation copy, Experiment metrics; (3) at least four improvements or experiments prioritized by impact versus effort; (4) for each experiment, the hypothesis, change, primary metric, guardrail metrics, observation period, and stopping rule; and (5) required human approvals before publishing or execution. Special requirement: Do not infer sensitive attributes. Balance relevance, diversity, inventory, and user control.