Leading Europe-based retail brand, operating several multi-department stores and supermarkets.
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 in place to calculate the customer lifetime value.
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.
Our data scientists ranked all the current customers based on a weighted score calculated using 10 different metrics. Based on the ranking, the team segregated customers into deciles.
For each transaction, the team identified the timeframe of the transaction and categorized them across 8 different time periods. We developed statistical models which would help calculate the number of transactions in a definite time period.
We 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 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.
Delivered a sophisticated application with in-built methodology to calculate customer lifetime value.
Helped segment currently valuable customers, and identify customers likely to become more valuable.
Enabled focused distribution of marketing spend across customer segments.