pricing-experiments

What problem does it solve?

This Skill helps ecomm operators design controlled price tests that produce defensible learning while avoiding unethical or legally risky price discrimination.

Core Features & Use Cases

• Hypothesis-driven experiment design: forces explicit expectations for both short-term conversion impact and long-term LTV or margin uplift.
• Data-aware baseline pulls and measurement plan: uses AOV, margin-by-product, ROAS by channel, and cohort LTV to evaluate feasibility and downstream effects.
• Ethical randomization and durability safeguards: enforces non-protected-class randomization units (visitor/session/account), persistence rules, and guardrails like grandfathering and refund-on-discovery.
• Operational decision framework: recommends ship/stop rules using contribution per visitor plus 90- and 180-day LTV signals, with segment-by-segment evaluation.

Quick Start

Use the pricing-experiments skill to design an A/B test for your flagship SKU price change, including a clear hypothesis, randomization unit, required guardrails, and the metrics and stop-rule needed to decide whether to ship.