Customer Value and Profitability- Business Intelligence

Customer Value and Profitability KPIs

• Customer Value (current value, long-term value, lifetime value) against expectations.
• Customer Profitability against expectation.
• Customer Value Distribution against expectations.
• Customer Profitability Distribution against expectations.
• Sales value and volume with new vs. existing customers.

Measures-Facts related to Customer Value and Profitability

• Customer Value (Long-term, Current and lifetime)
• Customer Cost
• Customer profitability
• Sales volume to existing customers
• Sales value to existing customers.
• Number of Up-sell and Cross-Sell Transactions

Dimensions for Customer Value and Profitability

Following are the Foundation Dimensions and attributes which you can use to create your analytics and reporting base.

• Product-wise customer value and profitability
• Channel-wise customer value and profitability
• Location
• Customer segment
• Customer Value Band
• Customer Profitability band
• Tenure band of customer since acquired
• Tenure band of customer since last transaction

Analytics for Customer Value and Profitability:

Key analytical insights you can have on customer value and profitability:

• Time Trend Analysis of customer value enhancement: It tells us how well are we moving up the value enhancement. You can do time trending analysis on dimensions of customer-segment, product-segment, location and channel.
• Validating your actions to customer value: Once you have taken your actions to enhance the customer value, you would like to validate the actual impact on the ongoing basis.

Business Modeling/Data mining examples on customer value and profitability:

• Validating the association between a customer parameter and the customer value: This is a subject of data mining OR analytics, whereby you come out with the level of co-relation between a customer characteristic and its impact on the outcome. Before you come out with a business model to project life time OR long-term value, you will need to have this validation done. This can be done by analytics (taking the parameters one by one OR in simple combinations) OR using a data mining tool, to come out with the associations.
• Data mining on identifying actions to impacts on customer value: You need to find association between your actions and predicted impact on customer value. For example- the expected customer behavior of high value customers, if you increase OR decrease price.