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.