The client is a leading CPG Company and wanted to set up a robust pricing optimization engine for maximizing revenue uplift of multiple campaigns run continuously in the system. The existing system was unable to utilize multiple data sources and handle big data flowing at a higher frequency and was also ineffective in capturing the long-term impact and ROI of promotions.
Sigmoid built multiple Generalized Linear Models (GLMs) and clustering models for predicting/forecasting demand, revenue, and profit at an SKU-brand-category level of various campaigns (end of season, national events, special events). At the product-campaign level, we built a Test Control System-based evaluation framework for assessing the ROI of campaigns and ensuring an increase in revenue.
Our price optimization engine maximized revenue uplift of various campaigns and events, leading to a 30% increase in QoQ revenue and a 3% increase in margins.