Amazon and sophisticated omni-channel retailers dynamically re-optimize their online prices in view of competitors’ tactics, their own inventory and sell-through metrics, and general market conditions. Efficacy depends on high-quality market data and real-time re-optimization. Retailers lacking these capabilities suffer erosion of revenue, margin, sales, and price image.
Goals and Objectives
Enhance omni-commerce revenue and margin by identifying and monitoring dynamic-pricing movements by product, class, competitor that matter (some do not), set re-pricing cadences and other business rules, and apply optimization science as second stage.
Cloud, industry cloud, machine learning, predictive and optimization science, and natural language processing to ingest and filter competitive data.
Use Case Summary
Ensure ecommerce prices continuously meet competitive and market conditions to achieve desired pricing position, e.g., value, parity, or premiumn