Use Cases

Pricing strategies approach

We don’t believe in the one-size-fits-all approach to Dynamic Pricing. Our Dynamic Pricing solutions will provide you with a library of algorithms that optimise for different use cases. You can choose from: multi-product pricing, psychological pricing, cross selling, etc…

Multiple Trading Targets

Our client, a major retailer in the French market doing 20% of its revenue online, is looking for a way to help category managers to better optimise profitability in their different product categories. PricingHUB provides price optimization software for different categories pursuing different business goals (Revenue, Volume or Profitability).

Challenges :

  • Build a holistic data model: aggregating different datasets from various functional business areas.
  • Monitor price recommendation acceptance rate: Provide Category managers with enough information so they can understand and validate a specific price recommendation.
  • Explore the data and segment elasticity on different dimensions to identify and expose profitable growth opportunities.

Methodology :

After building the data lake we deploy our solution in 2 phases.

  1. Launch a learning phase
    • Our AI computes 6 different price points to be tested each day of the week so we can build and segment the elasticity curve.
    • We set-up the pricing tool & implement the business goals for each product category.
    • We train the category managers to use the tool and leverage the exhaustive reporting dashboards.
  1. Optimisation phase
    • The Dynamic pricing application computes and pushes price recommendations for the category manager or the pricer to validate
    • Validation can be manual, or automatic based on rules.
    • Once validated prices can be uploaded automatically to our customer ́s back office thanks to a web service connectivity
    • For each price recommendation validated and implemented we measure performance and contribution to the target

Achievements :

  • Category managers are equipped with data-driven decision pricing tools based on elasticity understanding rather than only focusing on benchmark data.
  • Category managers have a clear understanding of the elasticity of their category and have access to a powerful Dynamic Pricing application to steer their P&L.
  • Our price recommendations have an average acceptance rate of 90%.
  • Our experience has driven us to an average incremental gross profit around +10,3%, out of error range.

Use Cases