Challenge
A sales leader suspected revenue leakage but couldn't pinpoint the cause across CRM, NPS, and churn data
The sales leader had a feeling something was off. Quarterly churn numbers looked worse than the team deserved, but every rep's individual performance looked acceptable on paper. There was no obvious bad actor.
The problem was that CRM, NPS surveys, and churn data lived in three separate tools. No single report could cross-reference acquisition source with customer lifetime value. Each rep's closed deals looked fine in isolation. The damage only appeared months later, in a different system, when CS reported another account lost.
By then the salesperson had already closed three more deals. The feedback loop was broken. Leadership had a gut feeling but no evidence, and no way to act without it.
Solution
Nerra AI cross-referenced acquisition data, NPS surveys, and churn records to identify the systematic pattern
Nerra AI connected the CRM, the NPS platform, and the churn records. It started building a model of how deals moved from acquisition to retention, not as three separate datasets, but as one end-to-end journey.
Within weeks, a clear pattern emerged. Customers acquired by one specific AE were churning at 62% within 90 days, compared to the 18% team average. Their deal sizes were 40% smaller. Their NPS scores were significantly lower. And the pattern held consistently across 90 days of data.
This wasn't a single bad deal. It was a systematic issue in how this AE qualified prospects and handed them off to Customer Success. Nerra AI surfaced it as an insight signal with all three data sources referenced, the business impact calculated, and specific recommendations for Sales Leadership.
Results
The revenue leak was stopped, the handoff process redesigned, and qualification criteria updated
Leadership had a concrete, data-backed picture of the problem, not a vague suspicion. The AE received targeted coaching based on specific qualification gaps. The Sales-to-CS handoff process was redesigned to catch context that was being lost.
Most importantly, the team now had an early warning system for similar patterns across other reps and other cohorts, so the next leak could be caught in weeks, not quarters.
- Systematic 62% vs 18% churn gap exposed with full data trail
- Revenue leak stopped within the quarter
- Deal qualification criteria updated based on pattern
- Sales-to-CS handoff process redesigned with Nerra AI monitoring