Case Study
To value a coffee chain using the predicted lifetime value of the customers it acquires using its historical acquisition rate and purchase patterns.
Solution
- Binned historical customer shopping pattern using RFM analysis by examining how recently a customer purchased (recency), how often they purchased (frequency) & how much they spent (monetary)
- Performed regression to predict probability of churn in each period based on customer demographics
- Calculated value added by each customer in the forecast period using churn probability and expected monetary value
Value Addition
Evaluate long term ROI of customer acquisition costs
Verify valuation models using data by discounting predicted value of customers in each period
Sensitivity analysis to calculate long term value of customers for money spent on each customer
Use intermediate results from RFM model to identify customers likely to churn and develop measurable & cost-effective win-back campaigns to retain them
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