Customer Lifetime Value AnalysisThe customer lifetime value (CLTV) enables you to determine for a given customer segment how the customer base and profitability have developed over time. You can use this information to draw conclusions and thereby predict the future development of this customer segment and then base your investment decisions on such predictions.
The entire life cycle (divided into lifetime periods) for a typical customer is considered in the analysis of the customer base belonging to a segment. The analysis calculates in particular the profit that a company makes with a typical customer in a given lifetime period and the proportion of customers in one lifetime period to be retained by the company by the next lifetime period. The lifetime period typically taken for a customer is a year, but it can be set according to industry-specific requirements.
The information about past profitability and about customer retention allows you to estimate how the profit made with a customer segment and the number of customers in that segment are likely to develop.
· You need to have access to the following data about your customers:
¡ Costs pertaining to a customer
¡ Revenues made with a customer
¡ The date when the business relationship began
CLTV analysis produces most informative results if the segments under analysis each describe homogeneous customer behavior.
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1. You gather data on customers and customer profitability and determine when the company began a business relationship with the customer.
2. If possible, you create homogeneous customer segments on the basis of customer behavior.
3. You determine for a segment the customer retention rate, profit per customer, and the CLTV.
4. You use CLTV prediction to predict the future CLTV.
5. You deploy the results in the operational processes.
The section Customer Lifetime Value Analysis: 1 BW, 1 CRM, 1 R/3 describes just one of several options for using the CLTV analysis to achieve a closed loop scenario, whereby all data relevant for the CLTV analysis is transferred from OLTP systems into SAP BW for processing, and then applied in the OLTP system for operational processes.