Telecom — Churn Management

Telecom Save Desk Reduces Voluntary Churn by 35%

Proactive churn management programme for a mid-tier telecom operator — combining predictive analytics with trained retention specialists.

↓35%
Churn Reduction
28%
Save Rate
6mo
Programme Duration
Telecom Churn AI Analytics

The Challenge

A mid-tier telecom operator with 4.2M subscribers was facing voluntary churn of 3.8% per month — nearly double the industry average. Retention efforts were reactive (calling customers who had already requested disconnection) and had a low save rate of 11%.

Our Approach

01

Built a churn propensity model using 14 months of behavioural data: call drops, data consumption trends, payment delays, and competitor activity signals.

02

Identified at-risk customers 30 days before predicted churn — enabling proactive outreach before the decision was made.

03

Created a retention specialist team of 35 agents with personalised offer authority: plan upgrades, bill credits, device upgrades, and loyalty rewards.

04

Designed a save desk decision tree aligned to churn reason — price sensitivity, network quality, competitor offer — with distinct retention playbooks per scenario.

05

Tracked save rate, offer cost per save, and 90-day re-churn rate to optimise offer selection over time.

 Key Results
↓35%
Voluntary churn reduction within 6 months
28%
Save rate on proactive at-risk contacts
3.1x
ROI on programme cost vs revenue retained
↓68%
Reduction in reactive disconnection requests
"The shift from reactive to predictive retention was transformative. Ayuda built both the model and the team that makes it work in practice."
— Director of Customer Retention, Telecom Operator
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