Client retention model
A machine-learning model that predicts which active clients may leave, with an explanation for each prediction and a documented fairness audit, so staff can reach out in time.
Most businesses already hold the data that shows which clients are about to leave, which accounts will fall into arrears and when the phones will get busy. We build models that surface those signals early — and explain each one.
What we deliver
What’s included
- Customer churn and retention risk scoring, with an explanation for every client
- Payment-default and arrears risk, and collections propensity: who to call, and when
- Best-time-to-contact and success-likelihood analytics
- Demand and volume forecasting for call volumes, cash flow and workload
- Anomaly detection on transactions, usage and operations
- Fairness auditing, with the compliance position documented for each model
Case studies
Systems we have built
Our clients stay anonymous; we describe the work, not who it was for.
ID pool allocation with success analytics
A service that allocates identifiers from a managed pool and tracks success rates to inform how they are used.
Usage and billing reporting
Management reports on Wi-Fi usage, and billing reports produced with JasperReports.
Tell us what you want to improve
Describe the problem in your own words. We’ll come back to you with how we would approach it and a quote.