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4x growth in Revenue of a retail outlet planning using data science for business decisions

Consumer Patterns and Buying Behavior Study through Data Science for a Retail Chain

A leading organized retailer from central India in lifestyle, fashion and hypermarket with 100 stores aimed for 4x growth in revenue. In order to work out strategy for increasing sales of each store, they wanted to closely observe the consumer patterns and buying behaviour. They wanted to have evidence-based answers to below questions.

  • How to maximize sales per square foot for existing stores
  • Decision on the location for opening a new store
  • Visual merchandizing in such a way that it boosts more purchase and impulse buying.

Our approach

  • Segmented the state into more meaningful clusters based on shopping behaviors
  • Analyzed the baskets to understand each store’s performance down to individual shelf level
  • Creation of dashboard for the store team to quickly and easily compare performance on multiple parameters, identify which parts of the store are driving success and matching existing store’s profiles to new locations

Solution outcome

This approach gives a clear picture of each store’s potential, also what works and what not and accordingly take a call on further investment in stocks, liquidation for avoiding overstocking and the need for opening new stores.

Experience analysis prototype

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