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Built product assortment framework to optimize product mix and maximize sales for a Fortune 500 CPG company

Summary

The client was witnessing steep loss in sales and out-of-stock situations. This was attributed to the lack of a system that could provide an optimal product mix. They wanted an analytical product mix for their stores to increase sales and maximize pro?tability.

Approach

We took a four-phased approach to this challenge:

  • Data from disparate sources were consolidated into a single data warehouse, improving the usability of data
  • The analytical data layer was then prepared after carrying out data treatment procedures and applying business rules that were appropriate for the client’s business
  • Elementary data analysis helped classify stores based on potential products they could house
  • A regression model was then applied to identify the impact of changing assortment quantities on the top-line sales and the correlation model helped identify the af?nity between different products
  • The combined insights from the models helped us arrive at the optimal assortment strategy for the client.

Key Benefits

  • Our easy-to-use solution enabled the client to identify closely related products and plan assortments accordingly
  • It included recommendations on the mix of products that a store should carry and store-level revenue prediction based on the assortment mix

Results

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Our collective efforts paid off when the client’s Stock Keeping Unit (SKU) level prediction enhanced the weekly sales by 6%.

Results

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