Churn Intelligence

Knowing who will leave is the start. Knowing why is the difference.

Churn prediction on its own produces a list. Churn intelligence makes the patterns, reasons and segments behind that list visible, and feeds your retention strategy.

  • Risk identification

    Rank the customers most likely to leave in the coming period.

  • Root-cause analysis

    Separate price, service, contract and usage-driven risk.

  • Behavioural patterns

    Find combinations that multiply risk when they appear together, not just single signals.

  • Segmentation

    Show where risk concentrates by segment, region, product and customer age.

  • Early warning

    Alert when a customer breaks their own rhythm, before the loss is recorded.

  • Actionable insight

    Deliver every finding to teams with an owner, an action and a timing.

One threshold for everyone is right for no one.

A customer who engages several times a week and one who engages once a month can't be watched with the same rule. Churnico learns each customer's normal rhythm and measures deviation from it.

Personal baselineExample view
Customer A · frequent userDeviation alert
Today
Customer B · occasional userNormal
Today
Normal rangeCurrent silence

The same silence is an alert for A and ordinary behaviour for B.

Signal combinations

Weak alone. Strong together.

A single support request usually says little. Seen together with an approaching contract end and falling usage in the same customer, the picture changes. Churnico searches for these combinations systematically.

Signal combinationsExample view

Relative risk

One signalSupport request
Two signalsSupport requestContract ending
Three signalsSupport requestContract endingUsage decline

See where risk concentrates.

Portfolio averages often hide the problem. A risk heatmap by segment and customer age shows where intervention should focus.

Segment visibilityExample view
0-6 mo6-12 mo1-2 yrs2-4 yrs4+ yrs
Consumer0.420.330.240.160.12
SME0.710.580.390.270.18
Enterprise0.280.220.170.120.08
Public sector0.190.150.110.090.06
Low riskHigh risk

Every assumption is tested against data.

Field knowledge is valuable, but it doesn't enter the model unverified. Each churn hypothesis is tested in the data and its outcome is clearly marked.

  1. Confirmed

    A meaningful, consistent relationship was found; it feeds the model and actions.

  2. Revised

    A relationship exists, but not as expected; the definition is updated.

  3. Rejected

    No support in the data; deliberately left out.

See your churn risk in your own data.

Let's talk through your data in a short call and assess together which signals Churnico can read in your customer base.