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Champion™ Champion™  << Products << Home  
 
Customer churn is one of the major threats to profitability in telecom operations. Studies have shown it is upto 7 times more expensive to acquire new customers than to retain existing customers. In a scenario of rapid growth in emerging markets, managing churn takes on a new dimension as the emphasis is on acquiring customers.  Understanding the factors affecting the churn will help the operator to initiate proactive measures to retain customers.

There are several churn prediction tools available in the market. We have developed Champion™ as a churn management product by building telecom churn models and modeling process flow into the tool. Champion™ is an integrated application which has all the components needed for end-end modeling -

Data pre-processing tool
Predictive Modeling tool
Customer scoring tool
Pre-built dashboard for retention/churn monitoring with industry
   standard KPIs pre-configured
On demand reports like: at-risk customers, worst 5 regions for churn    etc.,
 


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Why Champion™?
 
The main plank for Champion™ is -
 
Transparency of modeling – Operators can take effective retention action if the reasons for the churn are known. Champion™ provides transparency in model results and in the reasons for churn for scored customers.
Configurability – In a dynamic and competitive market, business users – i.e retention managers should be able to configure additional dimensions and customer variables easily and build new models without the need for analytics experts OR development effort. Champion™ has a configurable front-end modeling interface which can be used by business users to build new models.
Effectiveness (ROI) – The effectiveness of any churn management tool is in the improvement in prediction accuracy and timeliness of the prediction. Champion™ provides interactive model evaluation tools which can quantify the improvement in prediction. This can build the ROI for the analytics investment.
 
Business Benefits of Champion™
 
To identify postpaid customers most likely to churn in the next 3-6 months based on their behaviour and past churn trend of customers
To identify prepaid customers who are likely to stop recharging in the next 3-6 months
To do the survival analysis for active customers – i.e predict when is the customer likely to churn
 
Modern day process plants are almost automated with telemetry systems to collect...
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