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Reducing Customer Churn

Background

A leading Telecom & Media firm required an advanced analytical framework to evaluate the key drivers of customer experience and proactively prevent churn on an ongoing basis.

Approach

Developed simple and easy to understand metrics. Then, identified the drivers of customer experience and the relative impact of each. Lastly, manage churn by engaging with customers through a value-based approach rather than simple competitive pricing alone.

Solution Framework

• Harmonized disparate data sources.
• Adaptive learning of customer behavior based on data (e.g. viewing, usage), and real-time understanding of Customer Experience through AI.
• Rapid integration into existing client environment through a scalable solution capable of answering additional business problems and integrating future training data sources.

Outcome

The AI architecture reduced churn by capturing dynamic and static information (i.e. sequential events in a customer’s journey and demographics), enabling a holistic understanding of behaviour signals at the individual customer level.