DATA & ANALYTICS | Automotive | North Carolina

Inventory Turn Rate Improved With Demand Forecasting Model

A multi-location dealership group was holding aging inventory too long on some lots while running short on high-demand models at others. We built a demand forecasting model using historical sales data, regional search trends, and seasonal patterns to optimize allocation across locations and reduce days-on-lot for slow movers.

Measured outcomes

19% Faster inventory turns
23% Reduction in aged inventory

Implementation summary

Render Analytics connected the relevant systems, data signals, workflows and reporting logic so the team could make decisions from cleaner evidence and focus on measurable outcomes.