Case study: Assortment planning for a Global CPG Giant
About the Client
The client is a global CPG giant with ~70 brands and with presence in over 80+ countries.
The client was actively looking to grow top-line in their pursuit to win market share. They needed a solution to optimize the SKU assortment in more than 1.5Mn stores in India through 30+ distributors.
BRIDGEi2i addressed the problem using artificial intelligence to provide the sales representatives with store level intelligent recommendations at the point of sale. We partnered with the client to develop an SKU Mix recommender to identify the optimal SKU mix at a store level.
- The Data Engineering team undertook consolidation of sales data across 1.5Mn stores in multiple formats and also considered data from development POS and shipment data mart
- The next step was to mashup data into Hadoop System
- This led to creation of a single view of stores with all existing and derived variables
- The AI Labs team built an algorithm for store segmentation: Dynamic segments based on interpretable factors – Wallet size, Value and Variety of SKUs purchased (WVV). The algorithm identified stores that were similar to look-up stores based on certain predefined attributes.
- Looking at similar stores in similar geographies, the algorithms discovered SKUs that would be an ideal match for stores with high sales lift potential based on sales in lookup stores.
BRIDGEi2i’s AI Labs deployed an SKU Mix Optimizer solution that was able to deliver Personalized SKU assortment recommendations for every store to sales rep’s handheld device; the recommendations were a combination of new SKUs and base SKU retentions