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A case study on churn analysis1

A case study on churn analysis1






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    A case study on churn analysis1 A case study on churn analysis1 Presentation Transcript

    • Axion Connenct 1A CASE STUDY REPORT ON CHURNANALYSIS Submitted to Mr. Sanjay Rao Founder, Axion connect Presented by Amit Kumar
    • Way Forward….2  A Business Scenario  Business Problem  Available Solution  Stepwise solution  Results & Findings
    • A Business Scenario…3 A leading telecom service provider has a customer base of 1million users. In the cellular base, a customer can choose pre-paid & post-paid services. In this competitive telecom market customers have vast array of choices, the cost of acquisition & rate of customer churn, both are increasing at a rapid pace. In last three quarters operator’s profitability has gone down & faced problem of customer churn in one of the operator’s largest circle. The average attrition rate for each quarters for the operator is 8% , 12% & 15% respectively. Axion Connenct
    • Business Problem..4  Telecom service provider is loosing customer base & their profitability has gone down.  The average churn rate is around 12%(Q1-8%, Q2-12%, Q3-15%)  The acceptable return on their retention program is very less & it has not targeted sharply to the customer churned in second & third quarters Axion Connenct
    • Available solution..5  To address these problems, operator wants a robust retention model/churn model that would help the telecom operator to identify the propensity of churn & high-value customers.  Need to use advance modeling techniques like neural networks, decision trees & logistic regression to construct a model that can score each customer for his probability of churn over next quarter. Axion Connenct
    • Stepwise solution..6  Integration of the data like, billing information, demographic information, service record information, customer participation in retention program etc. in a single file to capture all aspects of customer interaction.  Understanding of data dimension, functions & association of data object with functions  Data object preparation  Constructing the model  Validating the model  Implementing it & track it Axion Connenct
    • Results & Findings..7  Model will help the operator with other CRM metrics to build retention strategy.  Customer with high profitability with high propensity to churn should be in the highest priority of retention and should offer best incentive.  Customer with low profitability with high propensity to churn should encouraged to increase the usage. Axion Connenct
    • Axion Connenct 8THANK YOU!