Retention and churn prevention
Retention and churn prevention on Adobe Experience Cloud: risk signals, retention audiences, save journeys in AJO, and measurement in CJA.
Churn prevention identifies customers showing risk signals — falling usage, service issues, contract milestones or competitor research — and triggers timely, relevant save actions. On Adobe Experience Cloud, AEP unifies the signals, audiences segment risk, Journey Optimizer orchestrates retention journeys and CJA measures retained customers against a control group.
The business problem
Retention offers often go to customers who would have stayed anyway, while genuinely at-risk customers are reached too late. Without a shared view of risk signals, retention budgets are hard to justify.
Reference architecture
Signals
Usage trends, service tickets, billing events, contract dates and digital behaviour.
Risk audiences
Rule-based or model-scored segments refreshed on the right cadence.
Save journeys
Service recovery, proactive outreach and offers with eligibility rules.
Measurement
Control groups and retained-value reporting in CJA.
Delivery approach
- Define churn — agree what churn means per product and segment
- Signals — bring the right events and attributes into AEP
- Segment — build and validate risk audiences
- Journeys — design save paths with suppression and caps
- Control — hold out a group to measure true impact
- Iterate — refine signals and offers using results
How success is measured
- Retention rate versus control
- Cost per retained customer
- Offer take-up among high-risk customers
- Time from risk signal to first contact
- Complaint and opt-out rates
- Retained revenue (where measurable)
This page describes a solution pattern we deliver. It is not a client case study, and results depend on each organisation's data, licensing and execution.
Frequently asked questions
Do we need a machine-learning model?
Not to start. Clear rule-based signals often deliver value first; models can be added once data and measurement are in place.
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