Departure risk surfaces before churn.

Departure risk becomes visible in shifting transaction and engagement behaviour before conventional metrics confirm it. The question is whether your systems can detect the change while the intervention window is still open.Assess Retention Economics

The cost of late detection

By the time churn surfaces in a report, the low-cost intervention window has closed. Transaction velocity shifts, channel migration, and agent network disengagement are already visible in your data. Together, these changes can indicate growing departure risk before the report confirms it. The difference is structural: act on behavioural signals and you intervene when retention economics justify it. Act on reports and you intervene when they no longer do.

Early Warning System

Your reports arrive monthly. Risk scores update daily. Every customer carries an individual departure probability that reflects their latest transaction patterns, not last quarter's segment average.

Behavioural early-warning signals

Confidence-scored predictions

Daily risk score updates

Predictive Risk Scoring

Individual risk trajectories update with every interaction, not segment averages. Each score explains which behavioural shifts drove the change, with confidence intervals that distinguish strong signals from noise.

Individual risk profiles

Reason code explanations

Confidence intervals

Retention Campaigns

Intervention deploys when retention probability peaks, not when the marketing calendar says. Multi-channel orchestration across SMS, USSD, and agent networks matches the customer's preferred channel at the right moment.

Automated trigger campaigns

Personalised incentives

Multi-channel orchestration

Compounding Intelligence

Churn signals sharpen cross-sell timing. At-risk patterns improve reactivation targeting. Retention responses refine dormancy detection. One behavioural layer. Each application strengthens the others.

Churn signals sharpen cross-sell timing.Early intervention timing favours retention over replacement economics.

Cross-sell patterns reveal dormancy causes.Behavioural targeting reduces campaign waste by intervening only where probability warrants it.

Precision timing compounds across every intervention.Models distinguish strong attrition signals from noise, enabling systematic intervention deployment.

Proposed 90-day retention proof

We integrate with your transaction data, build behavioural attrition models against your portfolio, and run a treatment-versus-control test. A 90-day structure can be used where data readiness, sample size, approvals, and intervention timing support it. The agreed analysis measures risk, intervention timing, and performance against the existing approach.

Detect

Identify at-risk customers through behavioural signals in your transaction data.

Intervene

Deploy precision retention campaigns timed to peak retention probability.

Prove

The treatment-versus-control analysis will measure retention rates, intervention timing, and behavioural versus traditional economics.

Preserve Revenue Through Early Detection

Stop absorbing the structural cost of late intervention. Behavioural intelligence transforms retention from reactive reporting into predictive capability.45-minute executive consultation. We assess strategic fit before asking you to commit.

Predictive models calibrated to your attrition patterns.

Intervention economics validated in your environment.