CASE STUDY — GLOBAL AUTOMOTIVE OEM
Finding the silent detractors.
Predicting customer satisfaction from service-lane operational data, surfacing the dissatisfied customers who never answer a survey.
The Task
Predict customer satisfaction
Data Source
Service-lane operations
The customers who leave without a word
A global automotive OEM tracks customer satisfaction largely through post-service surveys. But the customers most likely to be dissatisfied are often the least likely to respond — they simply disengage. That leaves a blind spot exactly where it matters most: the dissatisfied customers a dealership never hears from until they've already gone to a competitor.
Reading satisfaction from what already happened in the service lane
Instead of relying on customers to self-report, NEXUS was trained to predict customer satisfaction directly from service-lane operational data — the record of what actually happened during the visit. That means dissatisfaction can be flagged even for customers who never fill out a survey, surfacing the silent detractors a survey-only approach would miss entirely.
03 — THE RESULT
Catching dissatisfaction before it goes quiet
MEASURED OUTCOME
more accurate detractor predictions
Proactive outreach before dissatisfaction becomes defection: NEXUS identifies likely detractors 17% more accurately, giving dealerships a chance to reach out while there's still a relationship to save.
04 — THE IMPACT
Retention starts before the churn.
When dissatisfaction can be spotted from operational data instead of waiting on a survey response, dealerships get a real window to intervene — a call, a make-good, a fix — before a quietly unhappy customer becomes a lost one.
