How to Run Profitable Pricing Experiments?
15 days ago
- #A/B-testing
- #ecommerce
- #pricing-strategy
- Pricing experiments differ from standard A/B testing by focusing on value perception and unit economics rather than friction reduction.
- Key metrics for pricing experiments include Gross Profit Per Visitor (GPPV) and Net Profit Contribution, not just conversion rates.
- Understanding Price Elasticity is crucial; products can be highly elastic (commodities), unitary elastic (mid-range items), or inelastic (branded goods).
- Experiments should test higher prices for lifestyle or luxury goods (Veblen Effect) and lower prices for consumables or high-competition goods (Market Penetration).
- Three strategic frameworks for pricing experiments: Margin Hunter (elasticity testing), Context Game (anchoring & decoys), and Volume Play (cash flow & acquisition efficiency).
- Execution requires server-side tools (e.g., Shopify Functions), isolating variables, and ensuring price consistency across user sessions.
- Ad campaigns should be 'Price Agnostic' during tests to avoid misleading customers and skewing data.
- Van Westendorp Price Sensitivity Meter helps estimate price ranges pre-launch, but A/B testing reveals actual customer behavior.
- Pricing experiments should run for at least two weeks to capture buying cycles and ensure statistical significance.
- Optimal pricing can significantly impact profitability, making it essential to test based on data, not intuition.