TL;DR: AI tracks customer behavior and communication and flags those showing signs of leaving. You get a chance to act while the customer is still here, instead of seeing it later in a report.
The exit you only notice once it's over
Almost no one says "I'm leaving." A customer just starts using less, stops opening messages, or sends a complaint that gets no real response. The signals are spread across different systems, and no one looks at them together.
So the loss only shows up in the monthly report, once the customer is already gone.
How AI recognizes the risk
- Changes in usage. A drop in activity or purchases compared to the earlier pattern.
- Signals from communication. Silence, a negative tone, or repeated complaints.
- Risk scoring. It combines the signals into a clear list of customers at risk of leaving.
- Suggested action. It proposes a move — a call, an offer, fixing a problem — for each case.
Measurable results
- At-risk customers spotted while they can still be kept
- Retention effort aimed where it's needed most
- A more stable base and less revenue churn
FAQ
What data does it use?
The data you already have — purchases, usage, communication — combined into a single picture per customer.
What do we do with the at-risk list?
The team works it by priority, and the system can even trigger the first contact step automatically.