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Digital & AI Solutions

Telecom churn model reduces monthly churn by 2.1 points

ClientNational telecom with prepaid and postpaid lines
IndustryTelecommunications
Timeline20 weeks
SERVICES

Services Delivered

Digital & AI SolutionsData analytics & insightsAutomation
CHALLENGE

The Problem

Marketing spent heavily on retention offers without precise targeting.

APPROACH

Our Method

  • [01]Built unified customer features from network, billing, support, and device data
  • [02]Developed uplift models to optimize offer treatment
  • [03]Automated A/B policy rollout with holdouts for causal measurement
SOLUTION

What We Built

End to end ML pipeline with monitoring for data drift, batch and near real time scoring to campaign tools

TECHNOLOGY

Tech Stack

Databricks, Feature Store, MLflow, Airflow, Snowflake, campaign API integration

OUTCOMES

Results

01

2.1 points

Monthly churn reduction

02

12%

Retention spend reduction

03

$18.4M

Annualized benefit at national rollout

Client names withheld by agreement. Results validated by client finance or operations.

NEXT STEPS

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