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Predicting and Preventing Churn with AI

With the multitude of products and services available and growing, it has become imperative for businesses to have a strong customer retention program and establish a platform that aids in predicting churn.

 

The benefits of retaining customers have been proven. Customer acquisition costs five times more than customer retention. By increasing customer retention rates by 5%, boost profit by 25% to 90% as the probability of selling to loyal customers is 70% and only 5%-20% to new ones.

 

Through Artificial Intelligence, machine learning, and customer interaction analytics develop an accurate perspective on customer behavior and churn tendencies. Effectively predicting churn and providing opportunities to act on it and prevent churn.

Goals

Proactively identifying and predicting churn

Analyse why and how churn occurs

Develop a strategy to combat churn

Example Data Requirements

Key Strategies and Technology

Train Artificial Intelligence to identify at-risk customers.

Utilise Analytics to identify underlying causes of customer churn.

Use Artificial Intelligence to identify customer pain points for effective intervention.

Employ Machine Learning and Predictive Analytics to develop strategy to prevent churn and increase customer retention.

Results

Churn risk identification and prevention

Change from a reactive retention strategy to a proactive strategy, providing a significant competitive edge

Retain more customers with improved service and product

Use Cases

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