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