Customer lifetime value modeling for retail brand

Client

Leading Europe-based retail brand, operating several multi-department stores and supermarkets

OPPORTUNITY

The client wanted to understand the potential contribution that could be made by each customer to its revenue and profit. However, the client did not have any methodology inplace to calculate the customer lifetime value.

SOLUTION

SG Analytics applied the following approach keeping in mind the client’s requirements:

• SG Analytics team aggregated the customer and transaction data for the last 7-10 years and cleansed it for anomalies
• SG Analytics then ranked all the current customers based upon a weighted score calculated using 10 different metrics. Based upon the ranking, the SGA team segregated customers into deciles.
• For each transaction, the team identified the timeframe of the transaction and categorized them across 8different time periods. The team developed statistical models which would help calculate the number of transactions in a definite time period.
• SG Analytics then designed a tool to calculate the corresponding Net Profit Value using client-approved assumptions and subtracted the average cost of marketing/retention to calculate the customer lifetime value for each customer.
• The SG Analytics team added a customization feature, whereby users could put in dynamic values for a customer and assess the potential value for a particular time period.