case study

Churn Prediction Model for CPG Manufacturer and Distributor

Retail & CPG

Business Impacts

Data driven identification of churn factors

Enhanced customer lifetime value

Significant increase in retention rates

Customer Key Facts

  • Country : United States
  • Industry : CPG

Developing a churn prediction model to identify consumers most likely to churn

The customer, an American wholesale manufacturer, and distributor of bakery ingredients and products wanted a system to identify consumers who were more likely to dissociate with the brand so they can take preventive measures.

Challenges

  • Limited data availability
  • Inconsistent variables
  • Weightage of unidentified factors affecting retention
  • The untuned model resulting in reduced accuracy

Technologies Used

Google Cloud Platform

Google Cloud Platform

Google Compute Engine

Google Compute Engine

Google BigQuery

Google BigQuery

Google AI Platform

Google AI Platform

Google Ads

Google Ads

Cloud Storage

Cloud Storage

Cloud IAM

Cloud IAM

Cloud Monitoring

Cloud Monitoring

Cloud Logging

Cloud Logging

Vertex AI

Vertex AI

Churn Analysis Model for an American Wholesale Bakery Goods Manufacturer and Distributor

Solution

Quantiphi segmented customers into various buckets through RFM analysis and developed a churn model which will help them understand the segment of customers most likely to drop off along the way.
This helped the client devise mitigation plans for factors associated with each segment.

Result

  • Data-driven identification of churn factors
  • Enhanced customer lifetime value
  • Increased retention rate

 

Start Your Next Gen AI Journey Today

Discover how Quantiphi’s AI-powered solutions can transform your business. Fill out the form, and we’ll help you explore tailored AI strategies to unlock new opportunities for growth.

Thank you for reaching out to us!

Our experts will be in touch with you shortly.

In the meantime, explore our insightful blogs and case studies.

Something went wrong!

Please try it again.

Share