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Trade Promotions Simulation and Optimisation

Using AI to simulate changes to in-store promotions

Challenges

  • Consumer Goods client wanted to use ML/AI to breakdown the factors of demand, and build a tool to simulate changes to temporary price reductions and optimise overall profitability

  • Client need to increase their empirical understanding of the impact of their promotions on their other products and on the overall category

Solutions

  • Integrated and modelled sales, pricing and commercial data for 2 categories and 10 retailers

  • Developed machine learning pipelines to break down the factors of demand for ~3000 products, including price changes, cross-elasticities, etc. and enable future demand prediction

  • Ran iterations of scenarios to optimise profitability and create a promotional plan that would be acceptable for both retailer and manufacturer

Values

  • Estimate 3-5% increase in sales revenue

  • Estimated 25% increase in promo ROI through more effective promotions

Roles

Data Scientist, Machine Learning Engineer

Technologies

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Sectors

Retail & Consumer

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