Reducing churn for a subscription service
Customer segmentation and a churn drivers model that told the retention team who to talk to — and what to offer.
The challenge
Churn was rising, and the retention team was offering the same discount to everyone who tried to cancel. This was expensive and did not work for many customers who were leaving for reasons other than price.
The question
Who leaves, why, and what retention offer actually works for each group?
Our approach
- 01
Customer survey — 4,000 current and former customers on satisfaction, usage and reasons for leaving.
- 02
Behavioural data — analysis of usage, billing and service data for the full customer base.
- 03
Segmentation — 6 customer segments combining needs, behaviour and value.
- 04
Churn model — model predicting churn risk 60 days ahead, with the main drivers for each segment.
- 05
Offer testing — retention offers tested with the client's team on selected segments before rollout.
What we delivered
- Customer segmentation with profiles and recommended treatment for each segment
- Churn risk model integrated into the client's CRM
- Retention playbook with segment-specific offers
- Retention dashboard for management
Outcome
−18%
Churn in targeted segments down 18% over 6 months
Lower spend
Retention discount spend reduced by focusing offers on high-value, price-sensitive customers
Daily use
Churn risk scores used daily by the retention team
Key insight
Price was the main reason for leaving in only two of six segments. For the rest, the issue was content and service — and a discount could not fix that.
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