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CVM Service

Churn Prediction & Retention

Score who is leaving and why, then intervene where it actually changes the outcome — the approach behind up to 40% churn reduction.

SF
The challenge

Most retention spend is wasted on customers who were never going to leave, while the genuinely at-risk slip away unnoticed until the disconnection request lands.

How I approach it

A clear path to a usable result

01
Predict with precision

Churn and value models that identify who is at risk, how valuable they are, and what is driving the risk.

02
Intervene intelligently

Design retention actions matched to cause and value, so effort goes where it changes the result.

03
Measure and learn

A test-and-learn loop that proves what works and compounds the gains over time.

What's included

Deliverables

Churn & value prediction modelsAt-risk and high-value targetingRetention play design by driverTest-and-learn frameworkRetention performance dashboard
Typical timeline
6–10 weeks
Engagement
Analytics + design
Proven outcomes

What this has delivered

Signed-off results from comparable engagements — not projections.

−40%
Churn reduction
Value
Weighted targeting
ROI
Per retention play
Frequently asked
How do you reduce churn without giving away margin?+
By targeting value-weighted risk and matching the intervention to the driver. You stop discounting customers who would have stayed and focus spend where it changes the outcome — I’ve delivered up to 40% churn reduction this way.
How quickly do results appear?+
Once models and plays are live, early signal typically appears within a couple of campaign cycles, with the test-and-learn loop compounding gains from there.
Related CVM services
Customer 360 & Segmentation →Next-Best-Offer Engines →ARPU & CLV Optimisation →

Keep the customers worth keeping

Send me your churn and value picture and I’ll show you where retention spend is being wasted — and where it isn’t.

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