Background and challenge 

L.E.K. was asked to design, build and deploy a pricing engine that could iteratively reach optimized price points and therefore maximize the lifetime value of our client’s product portfolio. 

The client had a portfolio of 250 product categories across 200 channels, with the ability to price each combination independently. As a result, there were approximately 50,000 possible product-channel combinations to optimize. 


L.E.K. performed a range of analytical assessments to support the client’s goals: 

  • Built a robust pricing optimization model that would maximize lifetime value (LTV) of each of the approximately 50,000 product-channel pairs

  • Segmented product-channel pairs into archetypes that informed the optimized price points (e.g., high levels of customer demand, low price sensitivity, etc.) 

  • Built a live model engine that queries millions of datapoints from the client’s data warehouse, and runs through a demand forecast model, a customer propensity (renewal) model, and lastly an optimization model 

    • The demand forecasting model was based on a Bayesian time series that deployed across all approximately 50,000 product-channel combinations 

    • Using data from the above models, L.E.K. created a pricing optimization engine that output the optimal price and promotion for each of the nearly 50,000 product-channel combinations 

  • Built-in advanced machine-learning capabilities, so that the model becomes increasingly smart over time, and can recommend increasingly significant price increases as it gains in confidence 

  • Designed and built a front-end dashboard to intuitively display pricing information and outputs for the client’s staff 


  • Within 6 months of go-live, the model has informed an average price increase of about 9% across product-channels 

  • Client uses the pricing optimization engine model on a weekly basis to re-assess optimal pricing and promotion across its approximately 50,000 possible product-channel combinations

Complex Pricing Analysis Uncovers Potential 25%-45% Revenue Uplift for Email Marketing Company
person using calculator
Our pricing and packaging strategy for an email and digital marketing solutions client is estimated to drive a 25%-45% annual revenue uplift, which represents over 100x return on project fees.

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