Case Study: AutoFi reduces dealer churn with RapidCanvas AI

How AI Transforms Dealer Engagement Using Data And Analytics

AutoFi, a company in the automotive finance industry, faced challenges in understanding dealer behavior due to data being siloed across different sources like their CRM and support systems. They needed a way to proactively anticipate dealer needs and predict churn but lacked the robust analytical capabilities. To address this, they partnered with the AI platform vendor RapidCanvas for a solution involving data orchestration and predictive modeling.

RapidCanvas implemented a solution that centralized and cleansed AutoFi's data to build a machine learning model for predicting dealer churn. The model analyzed factors like dealer tenure, support ticket sentiment, and platform usage to identify at-risk accounts. This provided AutoFi's teams with actionable insights, leading to a 15% reduction in dealer churn and an estimated 24% increase in dealer satisfaction, helping to protect significant annual revenue.

AutoFi

Scooter Schmidt

Head of Analytics