Call Center Relapses

Predictive Customer Retention

Telco

1 min read

In an effort to reduce customer churn and enhance satisfaction, we implemented a predictive system for call center relapses for a major telecommunication company in Iberia. The system aimed to address customer issues before they escalated, targeting those at high risk of churning due to dissatisfaction.

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The problem overview

The company faced a significant challenge with 30% of customer calls leading to relapses. This high rate indicated ongoing dissatisfaction and increased the risk of customer churn. The existing call center operations had a low hit rate for effectively managing these relapses, necessitating a more proactive approach to improve customer satisfaction and retention.

Our solution

We developed a gradient boosting model to predict call center relapses by leveraging detailed data from past customer interactions, service levels, and product information. This model was designed to identify customers at high risk of churning due to their dissatisfaction. By prioritizing these customers, the company could proactively reach out to them, aiming to resolve issues before they escalated further.

The results

Exceptional results were achieved through innovative solutions, turning the challenge at hand into measurable success.

Effective Resource Allocation

Our model achieved a high precision 80% metric, enabling the company to focus on the most likely candidates for relapse.

Significant Reduction in Churn

This approach led to a notable decrease in overall customer churn rates and an improvement in customer satisfaction.

Strategic Metric Selection

The model highlighted the importance of choosing the right performance metric. While the model itself was technically straightforward, the real challenge lay in selecting precision 80%.

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