SOLUTION/Choose the right intervention before churn, not after the score
A churn score tells you who is at risk. It does not tell you what to do about it.
Retention decisioning starts where prediction stops: matching customer value, churn reason and risk against an inventory of interventions with real costs and channel constraints, then testing which of them actually retains revenue rather than which of them feels responsive.
Churn risk · 30d
0.80
Attribute the churn reason
Live · 1/4What retention decisioning looks like with Markin.
Prediction is an input
Risk scores enter the decision alongside customer value, churn reason and what it would cost to intervene.
Save what is worth saving
Retained revenue net of intervention cost, not raw save rate. Some at-risk customers are not economically retainable.
Reason-matched interventions
Price, product friction, service failure and competitive loss demand different responses. A single save offer answers none of them well.
Opportunity intelligence
The segments your team should be acting on today.
Markin surfaces live opportunities, scored, sized and priced in ARR, so growth work starts on the accounts that actually move the number.
Service-failure churn
Discount offered where the driver was an unresolved service issue, so the save does not hold.
Reach
11.4K accounts
At stake
€1.1M ARR
Low-value at-risk base
Intervention cost exceeds the revenue it would retain across the whole band.
Reach
42.6K accounts
At stake
€680K margin
Late-cycle contacts
Intervention lands after the decision to leave, response drops 4x versus T-30d.
Reach
19.2K accounts
At stake
€950K ARR
Disengaged but active
Usage decay precedes cancellation by ~90 days and is not in the current trigger set.
Reach
26.7K accounts
At stake
€1.3M ARR
How it works
Data. Intelligence. Action.
The same three-layer loop that powers every Markin motion, tuned for retention decisioning.
01
Separate risk from reason
Survival and sequence models estimate when, while diagnosis attributes why: price, friction, service, competition or natural end of need.
02
Match against the intervention inventory
Each available intervention carries a cost, a channel, a policy constraint and evidence of where it has worked. The matrix is explicit.
03
Test, then scale what retains revenue
Interventions are trialled against control by value band and reason, and only the economically positive ones scale.
1:1 execution
One decision per customer. One message. One moment.
Every row is a live decision Markin ships into your CRM, app or contact center, no segment builders, no rule trees.
Marta L.
Telco · High value, price-driven
“Keep your number, lock a 12-month price”
Care
T-30d
Value-matched
Hugo D.
Streaming · Friction-driven
“Playback issue resolved before any retention offer”
Support
On detection
None
Rita N.
Fintech · Low value
“Hold: save cost exceeds the revenue retained”
—
—
None
Andreu C.
Retail · Lapsing loyalty
“Your size is back in the range you actually buy”
Post-decay
No discount
Measured impact
The numbers retention decisioning teams see with Markin.
+13%
incremental retained revenue net of save cost
-29%
save budget spent on non-retainable accounts
100%
of interventions run against control
We were very good at predicting churn and very bad at deciding what to do with the prediction. Those are different problems.
Head of Retention
Subscription operator, EU
Inside the product
Retention Decisioning, running 1:1.
Three concrete decisions Markin ships for retention decisioning, on the surfaces you already run.
Churn risk · 30d
0.80
Diagnosis
Attribute the churn reason
Price, friction, service and competition separated before an intervention is chosen.
Plan match · per user
Basic
Recommended for this user
€9
Premium
€14
Annual
€119
Economics
Size the save
Retained revenue net of intervention cost, per value band.
Match ranking · per user
Inventory
Map the interventions
Every available save action with its cost, channel and evidence base.
FAQ
Is this a churn prediction model?
Prediction is one input. Retention decisioning is the layer that turns a risk score into a specific, costed intervention choice — or into a deliberate decision not to intervene.
Why is save rate the wrong metric?
Save rate can be raised by discounting customers who were never going to leave. The economically meaningful measure is revenue retained net of intervention cost, measured against a control group.
How do you decide the churn reason?
Behavioural, billing, service and product signals are attributed to reason classes. Interventions are then matched to the reason rather than to the score alone.
Do you replace our retention campaigns?
No. Existing campaigns and care flows remain the execution surface. Markin decides which customers enter them, with which intervention, and measures the result.
What if no intervention is worth making?
That is a valid outcome. When expected retained revenue does not cover the cost of intervening, holding is the recorded decision.
How is impact measured?
Against control, as incremental retained revenue over the measurement window rather than immediate cancellation avoidance.
See retention decisioning run on your data.
A 30-minute demo, the same agents, the same decisions, the same 1:1 execution.