Service and retention
Customer service and retention audit — how much revenue leaves before anyone notices?
We take the tickets, the complaints and the cancellation calls, and measure recovery on your worst day rather than your average one. Then we rank the churn drivers by the revenue actually at risk behind each one.
What you are probably seeing
The symptoms that bring people here.
- Thousands of contacts a month and no agreed list of the ten causes underneath them.
- Cancellation calls are handled by whoever answers, with no measured save rate.
- Response times look fine on average and fail every Monday morning.
- Complaint themes are known anecdotally and never costed.
Method
How the audit actually runs.
Ticket clustering
Every ticket, chat and email in scope is clustered semantically to find the small number of root causes generating the volume, sized by contact count and handling cost.
Cancellation and complaint call scoring
Save attempts are scored against a retention rubric — acknowledgement, cause discovery, offer construction, escalation — with the recording attached to each score.
Channel performance reconciliation
First response and resolution are measured by channel and by hour against the demand curve, so the failure window is named instead of averaged away.
Churn-driver ranking
Drivers are ranked by revenue at risk, with the evidence trail from each driver back to the contacts and accounts behind it.
Deliverables
What lands on the table.
- Root-cause cluster report with contact volume and cost per cluster
- Save-rate analysis with call-level evidence
- Channel-by-hour service performance report
- Churn drivers ranked by revenue at risk
- A 30/60/90 action plan and retention training for the service team