Trade Promotion for a Global Beverage Leader

Problem Statement

The world's second-largest wine & spirits company, faced the challenge of maximizing return on investment (ROI) from their promotion spend. With a vast array of promotional strategies, it was difficult to determine the optimal allocation of resources and identify the most effective combinations for different SKUs and target audiences.

They wanted a granular TPO optimizer that could recommend promotions on a store and a SKU level, with over 10,264 stores and more that 175 SKUs.

The previous system lacked the flexibility required for optimal TPO, as it failed to consider factors such as seasonality, store inventory levels, company margins, and secondary sales figures.

Solution Implemented

• Data Collection and Preparation
• Feature Engineering
• Model Development and Training
• Model Evaluation and Refinement
• Model Deployment and Integration