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Churn Analytics and Prediction

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Churn Analytics

Customer churn is one of the most pressing issues for telecommunications service providers. The competitive pressures have pushed up the cost of acquiring customers .Analytics helps to understand churn by analyzing churn in different customer segments. Some of the analysis possible includes -

		Analysis of Overall churn - This is done using graphs. This can be done over a period of time OR for a specific time period. The patterns and trends in the graphs reveal unsuspected information and hence analysis can be done.
		Analysis of segment level churns - Some of the analysis possible include -
		How is churn in different segments like regions, products and customer categories? Is there any pattern in the churn of fresh activations across distributors and retailers for prepaid subscribers?
		Best and Worst performing markets analysis - Finding out the segments with highest and lowest churn would help focus customer retention efforts.

Churn Prediction

Using analytical models, we can predict the likelihood of churn of specific customers OR customer groups. This process is called churn scoring and these predictions are based on previous customer behaviour and statistics. The behaviour of past churn customers is understood by performing several processes on historic data. This is applied to active customer database to predict the future churns.

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