Telecom company improves customer retention through predictive churn model

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Telecom company improves customer retention through predictive churn model

Business Challenge: Improving customer retention.

A leading telecom company in Europe wanted to implement a proactive customer retention analysis and predictive churn modeling program that could help them improve customer retention, and reduce customer churn rate.

Situation: Unable to derive granular insights from vast customer data.

The client had huge amounts of customer data, and wanted a solution which could help them analyze it to identify customers with highest chances of churn, and thereby enable the sales and customer relationship teams to take corrective action before the actual trigger happens.

Solution/Approach: Predictive churn modeling to provide real-time insights.

We cleaned and analyzed the customer data, and integrated traditional and digital data sources to correlate the data. We setup a predictive churn model based approach to identify potential churners. We also provided real-time reports and risk flagging for potential churn.

Impact: Improved customer retention through predictive churn modeling.

Client was able to ensure maximum utilization of CRM data and data collected through digital sources. Our solutions helped them obtain insights for proactive churn planning before any damage to business, and take preventive measures to reduce churn. The client was able to achieve better customer retention with more efficient customer engagement.