Telecom

Generative AI for Customer Retention and Churn Prediction

Challenge:

The telecommunications company faced significant customer churn due to a lack of personalized support and an inability to predict dissatisfaction.​

Solution:

Implementing Databricks’ unified data analytics platform enabled the company to proactively engage with at-risk customers through advanced churn prediction models.​

  • Data Integration: Utilized Databricks to consolidate historical data and customer sentiment from various sources, creating a comprehensive dataset for analysis.​
  • Machine Learning Models: Developed predictive models using Databricks' MLlib to identify customers at risk of churning.
  • Personalized Engagement: Leveraged these insights to offer targeted retention plans, generating personalized offers and solutions to common grievances.

Advantages/Benefits:

  • Churn Reduction: Customer churn decreased by 18%.
  • Increased Loyalty: Net Promoter Score (NPS) improved by 25%.
  • Revenue Growth: Retained customers contributed to a 12% increase in revenue.