Customer Equity Maximization: An e-Commerce Approach.

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Presentation transcript:

Customer Equity Maximization: An e-Commerce Approach

What are the questions? Cingular Wireless loses about 15% postpaid customers each month, accounting for billions of revenue. Why would the customers leave? How to identify and prioritize the sources of customer dissatisfaction? How to exercise effective managerial interventions to prevent customers from churning?

How to answers these questions… 1.Analyze customer churning: is a kind of trapped customer equity (TCE) 2.Use confirmatory CRM strategy to treat it, as a result, maximize customer equity 3.Distinguish exploratory CRM – data mining, vs. confirmatory (primary data) 4.Demonstration: CEMS (customer equity maximization system)

What is trapped customer equity Customer equity is business driver of CRM: to retain customers Customer satisfaction is the main force of customer equity Customer equity is financial representation of customer satisfaction TCE: customer dissatisfaction

How to liberate TCE Enlarge CE: advertising to acquire more customers Liberate TCE: customer retention program to retain customers Both intend to maximize customer equity “Liberate TCE” is under-studied

TCE vs. MCE (materialized)

Liberate TCE with CRM strategy New CRM distinction: sources of data Exploratory (data mining) vs. confirmatory (collect direct customer response) Exploratory: data mining, secondary data Confirmatory: customer survey, primary data

What are the sources of TCE? Treat the sources to minimize customer dissatisfaction Categorize the sources Customers vs. providers Internal vs. external Example: strength of attitude to product is the source of internal and customer

How to demonstrate the strategy? CEMS (customer equity maximization system) Online questionnaire Online data collection Algorithm of automated prioritization: SQL Identify sources and their impact Guide managerial decision making

What is in the online questionnaire? Online questions are designed to address the four categories of constructs “I do not like the product very much” addresses the “strength of attitude” factor Customers are presented with the questions and respond thru Web Data are collected in a centralized database

How to analyze the primary data? Automated prioritization Algorithm select b.code, b.reason, count(*) from buyerresp a, codeandreason b where a.code=b.code group by b.code SQL: structural query language Count(*) are prioritized with a Java Pie Chart

How to prioritize? Graphically with Java Applet Count(*) for each sources are represented as slices of the pie The pie chart is presented to manager users on the Web Sources are prioritized with the size of the slices of the pie.

CEMS example

Summary 1.Analyze customer churning: is a kind of trapped customer equity (TCE) 2.Use confirmatory CRM strategy to treat it, as a result, maximize customer equity 3.Distinguish exploratory CRM – data mining, vs. primary data 4.Demonstrate the strategy: CEMS (customer equity maximization system)