Implementation of a dynamic pricing tool, to implement the pricing strategy in multiple points of sales and update the prices in real time





Handle a great number of prices in a dynamic environment

  • No synchronisation between pricing department, category managers and stores directors results in inconsistent pricing strategy

  • Difficulty to adapt to fast moving local specificities of hundreds of points of sales accross national territory

  • Difficulty to use data to improve knowledge of the price image for thousands of products, for many different client typologies

  • Difficulty to follow-up efficiency and performance of pricing actions



A 360° dynamic pricing tool powered by Artificial Intelligence

  • Setup of the pricing strategy based on historical and market data analysis

  • Central interfaces to manage, simulate and monitor the pricing and marketing actions: promotions, rebates, fidelity programs…

  • A calendar interface for operational teams to visualize and validate price recommandations, and access key market insights for all product categories, in order to take immediate actions

  • Development of a dynamic pricing engine based on ML forecasting and elasticity models to update prices in real time



Operational impacts and financial results

  • Increase in efficiency and reactivity for operational teams to configure their prices

    • Better understanding of prices and brand positionment for customers

    • Mean price + 1%

    • Revenues +2-8% ins stores where Pricemoov was deployed


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