A PGSA approach to interactive pricing optimization: converting consumer costs into marketing value

Purpose This study reconceptualizes interactive pricing as a reciprocal and value co-creation process that sets personalized optimal prices to drive purchases and profit margins. We introduce Predictive Global Sensitivity Analysis (PGSA) as a method for real-time interactive price optimization. Design/methodology/approach We simulated over 180,000 shopping scenarios based on 80,763 Amazon SKUs and constructed cart-level optimization models to generate profit-maximizing prices across multiple fulfillment tiers. We then used PGSA to create structural decision rules from these optimizations, enabling near-optimal pricing without requiring algorithmic infrastructure. Findings The PGSA-derived interactive pricing strategies outperformed traditional carrier-rate or free-shipping price policies. Personalized price rules created with PGSA enabled optimal prices that aligned with real-time customer behavior and margin protection, thereby transforming pricing into a dynamic mechanism for behavioral influence and segmentation. Practical implications PGSA generates interactive pricing rules that allow vendors to personalize prices based on live cart data, transforming pricing strategies from cost recovery to interactive value delivery. Originality/value Our study is the first to use the PGSA to operationalize interactive pricing. Our approach treats pricing as personalized interactive marketing mechanism, enabling price interactions without real-time optimization engines or advanced infrastructure.