Choosing Better Sites and Staffing Stores to Real Foot Traffic
7-Eleven used Safari AI to measure pedestrian traffic at properties it was evaluating, and door counts and capture rate at more than 10 stores in New York City.
Measured from storefront and street-facing cameras
Site and staffing decisions relied on short traffic studies and gut feel.
Before a lease was signed, foot traffic was estimated from a few days of manual counts or modelled data that could not show the hour-by-hour pattern. Once a store opened, nobody knew how many passersby actually walked in, so staffing and marketing followed habit.
- Prospective sites were judged on short manual counts or modelled data
- There was no view of how many passersby actually walked in
- Staff schedules followed habit, not the hours traffic peaked
Foot traffic and capture rate, store by store.
Connected to storefront cameras via an on-premise server
Existing storefront and street-facing cameras fed a lightweight on-premise server Safari AI deployed, so video was processed on site.
Counted pedestrians, entries and capture rate
Computer vision counted people passing each storefront and walking through the door, and calculated capture rate by hour, day and month.
Compared sites and stores side by side
Dashboards ranked current stores and prospective sites by traffic volume, peak hours and capture rate, so real estate, marketing and operations worked from the same numbers.
Note: Illustrative data
Better sites, better-timed shifts.
Prospective sites were judged on measured foot traffic by hour, day and month, so leases go where the customers already are.
Each store's entries were compared with the people walking past, showing which windows, offers and locations actually pull customers in.
Schedules were built around the hours traffic actually peaked, so stores are covered at the rush and lean when it is quiet.
Action Center: From Insight to Action.
Measurements like these feed Safari AI's Action Center, which flags a store whose traffic and staffing drift apart while there is still time to adjust.
- Real-time recommendations to improve KPIs via email, SMS, robocall, mobile app, Power BI, or API.
- Recommendations grounded in your own written SOPs, not generic best practices.
See this at your own stores.
7-Eleven measured foot traffic and capture rate from cameras at its New York City stores. We'll walk through which stores and sites are the best fit for a pilot on your cameras.
