Case Study
Improving Customer Retention with Machine Learning
Automated data-driven pricing strategies to optimize revenue and enhance customer retention
Client wanted insights into customer retention and pricing
- The client faced difficulties in reducing the time needed to uncover business insights due to the structure of their existing data platform.
- Client engaged Valent to provide insights into factors driving customer retention and develop an application that would enable data-driven decisions by business users.
Developed UDM, analyzed, and predicted retention using machine learning
- Developed a Unified Data Model (UDM) that consolidated the data to draw insights from into a single source.
- Generated correlation heatmaps to pinpoint which features had the strongest correlation with customer retention.
- Trained machine learning models to predict customer retention, uncovering hidden correlations not detectable through common statistical methods.
- Used advanced analytics to reveal how specific demographic factors influence retention, providing deeper insights for strategic planning.
Automated data-driven pricing strategies to optimize revenue and enhance customer retention
- Enabled quick provision of insights into pricing strategies and facilitated rapid ad-hoc analyses due to the groundwork laid by the UDM.
- Created an application that allows business users to visualize trends driving customer retention and develop effective playbooks for future customer engagement.
For Businesses
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