CRM Analytics

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  Case Study

The client wanted to leverage CRM data for a chain of coffee shops they invested in to identify opportunities for higher customer engagement and increase in revenue.


  Solution

  • Calculated breakeven growth required to nullify the impact of cannibalization
  • Estimated price elasticity for each beverage category using Monte Carlo Simulation by incorporating drivers that impact revenue
  • Segmented customers based on purchase patterns via k-means clustering to explore effects of price change on individual groups
  • Created efficient product combinations (through Affinity Modelling) from items likely to be purchased together to increase the probability of cross-sell
  • Graphically represented customer migration in response to price change to determine elasticity


  Value Addition

Optimized magnitude of future price changes based on historical cannibalization and price sensitivity of beverage categories

Interactive tool to enable cross-sell recommendations at POS in line with pre-existing products and customer segmentation

Set targets for new customer growth rate as per breakeven analysis

Visualized results of Monte Carlo Simulation on R-Shiny (application) and calculated likelihood of each event occurring

 

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