An established automotive software and marketing platform was building AI-powered audience features but faced a critical gap — their product knew everything about what happened inside dealerships, and almost nothing about the real consumers interested in buying cars.
A leading auto dealer marketing platform embedded Faraday's consumer intelligence into its AI product — provisioning individualized prediction environments across every dealer account it serves, without building a data science team.
Rather than rebuilding from scratch or sourcing raw data from brokers, they embedded Faraday's API directly into their product architecture, using the Faraday Identity Graph (FIG) — 1,400+ data points on 240M+ U.S. adults — as the consumer context layer underneath every audience they generate.
Using Faraday's multi-account API architecture, the platform provisions a dedicated prediction environment for each dealer, with custom propensity models trained on that dealer's own transaction history and audiences geofenced to their serviceable area.
Audience generation, which previously required manual rules-based configuration, now runs programmatically across every connected account, with automated monthly retraining triggered whenever a dealer's data updates — no human intervention required.
The result is audience generation automated across 1,000+ dealer accounts, with every audience reflecting real consumer behavior rather than just CRM activity — and no data science team required to maintain it.
