Customer churn prevention

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Business Solution Apr 20, 2020

Analytics Intell

Team

Customer churn prevention using predictive modeling

Customer churn prevention is a common business analytics use case for both B2B and B2C organizations.

If dependable customers suddenly stop purchasing a business’s product, the company must work extra hard to replace that revenue by finding new customers or selling more to other existing customers.  New customers are harder to find than previous or current customers, making customer acquisition costs relatively high, and customer churn a priority.

Luckily for businesses, predictive modeling can be used to prevent customer churn. With enough data, businesses can produce models to identify the best predictors of customer attrition, such as behaviors like customer service communications, demographics, or segment predictors. Armed with this information, businesses can then act to prevent customer churn by ensuring quality experience within certain customer groups, fixing any problematic product features, or giving special treatment to customers who exemplify signs of dissatisfaction.

We help you unlock your predictive power with advanced analytics. Our experts have extensive knowledge in the realm of big data and data science to implement smart methodologies including machine learning and forecasting to help you predict future business outcomes.

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