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 on-line, 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).
- 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 to identify and expose profitable growth opportunities.
After building the data lake we deploy our solution in 2 phases.
- Launch a learning phase
- We run the algorithm to build the first points of the elasticity curve.
- We set-up the pricing tool & implement the business goals for each product category.
- We train the category managers for the tool.
- Optimisation phase
- The pricing tool pushes price recommendations and optimises for the target.
- 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 tool to steer their P&L.
- Our experience has driven us to an average incremental gross profit around +10,3%, out of error range.
- We aim to achieve the best balance among the multiple KPIs targeted.
- We implement the process & tools looking after more than 90% of price recommendation adoption.