Case Study: Leading Auto Service Chain achieves $2.5MM incremental annual profit improvement with Applied Predictive Technologies

Leading Auto Service Chain Company - Customer Case Study

A leading auto service chain wanted to find the most profitable operating schedule — management planned to open two hours earlier on Saturdays to capture heavy weekend traffic but needed to know whether the extra sales would outweigh additional labor and operating costs and how hours changes would affect customer behavior across stores.

Using APT’s Test & Learn® for Sites, the client ran in-market test vs. control experiments to isolate incremental impacts: Saturday gross profit rose 8.4% ($210 per location) driven by the new early hours, with minor mid-morning cannibalization and a 1.1% ($28) drop in Sunday profit; after $170 of additional costs the average net was a $43 loss per store. Critically, analytics identified specific stores (lower income areas, larger households, more nearby competitors) where the change was profitable, and a targeted rollout of those locations produced a $2.5M annual profit improvement — a model the retailer continues to apply.