Setup of client-based pricing for this B2B service company and implemention of the pricing strategy to decentralised sales teams through dedicated interfaces





Price rationalization for multiple client segments

  • Complexity for computing the reference prices: more than a thousand products in hundreds of agencies for different packages

  • Price negotiation is time consuming: negotiated rates every year for tens of thousands of client accounts, local and national

  • Capacity optimisation: limited stock of products per agency

  • Hundreds of sales reps implies wide price dispersion and price computed on experience with no data based analysis



Connect sales and headquarters through a smart pricing tool

  • Setup of the pricing strategy based on historical data analysis

  • Central interfaces to input and visualize the pricing strategy, and manage, simulate and monitor the pricing policies

  • Sales interface to identify revenue opportunities and provide sales teams with strategic insights to guide their negotiation

  • Building of a dynamic pricing engine based on ML forecasting models and yield management algorithms to optimize capacity allocation and maximize customer lifetime value



Operational impacts and financial results

  • Increase in efficiency and reactivity for sales teams to configure the prices and get the management validation

  • Price dispersion - 47%

  • Occupancy rate + 6%

  • Revenues +2-8% in agencies where Pricemoov was deployed


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