customer story

How churn interventions reached at-risk customers two weeks earlier

at a glance

Client & sector
Pergel Sigorta (demo) — insurance
Arborn products
Arborn Insight + Arborn Logic
Users
Retention team of 25, leadership dashboards
Systems connected
Policy admin, billing, call centre logs
Deployment model
Private cloud
Time to first live use
8 weeks to first scored portfolio
Verified result
Pilot: at-risk customers contacted 14 days earlier on average; renewal +2.3pp in test group

The operation before Arborn

Churn showed up in quarterly reports — after the customer had already left. Risk signals existed in billing delays and support sentiment, but nobody saw them in one place or in time.

What we built

Arborn Insight scores the portfolio weekly from policy, billing and call-centre data. Arborn Logic routes high-risk customers to the retention team with the reason attached and records what was done.

What it connected

Policy administration, billing events and call-centre logs; the retention workflow with human approval on every outreach.

The result

In the pilot cohort, at-risk customers were contacted on average 14 days earlier than the previous process, and renewal in the test group ran 2.3 points above control. Pilot figures over one renewal cycle.

What came next

The same decision flow is being extended to payment-plan offers.

start with the problem that costs your team the most time

Bring us one workflow, not an AI brief. We will help define what should change, what the system needs to connect and how the result will be measured.