Skip to main content
← Back to Case Studies
AI / ML Telecommunications Featured

Predictive Churn Analysis

Telecom Provider · Telecommunications

Created predictive ML models identifying at-risk customers before churn occurs for proactive retention.

40%
Churn Prevention
฿15M
Annual Savings
87%
Model Accuracy
850%
ROI

! The Challenge

The telecom provider was losing 8–12% of customers per quarter with no early-warning system, making timely retention interventions impossible.

Our Solution

Built a churn prediction model analyzing 200+ features from usage, billing, and support interactions, paired with automated retention workflows.

Results

  • 40% of at-risk customers successfully retained
  • ฿15M annual cost savings
  • 87% model accuracy (AUC-ROC)
  • 850% ROI within 12 months

Tech Stack

Python XGBoost SHAP MLflow Airflow PostgreSQL Tableau

Duration

4 months

Key Outcome

40% churn prevention, saved ฿15M/year

Tags

Predictive AnalyticsChurnMLTelecom
Services ready to support you every day

Experience something new with

iReadCustomer before anyone else!

Over 10 partners and customers are growing with us — take the step forward together today!
Contact Us