Initial, mid-season and calendarized temporary price reductions (TPRs), and season-ending markdown prices commonly set by business rules. Limited use of science-based optimized pricing. All pricing methods handicapped by limited visibility of competitors’ prices. Optimized pricing often breaks price images and creates race-to-bottom competition.
Goals and Objectives
Develop, monitor, and correct pricing strategies and tactics to optimize trade-offs across financial, inventory, price image, and customer behavior goals to achieve item-, category-, store-, and omni-channel objectives. Apply science-based forecasting, optimization, and rules-setting to decisions. Acquire and ingest data competitors’ store and market-area pricing, assortment, and product attribute data. Model customer behaviors as function of their shoppable universe.
AI-enabled assortment planning, ML-enabled forecasting, optimization sciences, AI NLP for classification.
Use Case Summary
Take a holistic approach to setting prices throughout merchandise and assortment lifecycles and across markets and channels to realize constrained business objectives.