Selling More Merchandise on Game Night Without Adding Staff
The Charlotte Hornets used Safari AI in their team store to measure door counts, capture rate, shopper mix and checkout lines from existing cameras.
Measured from existing store cameras
The team store's busiest minutes were also its least visible.
Merchandise sales spiked before tip-off, at halftime and after the final buzzer. Without live data, staffing was guessed in advance, promotions could not be measured, and fans who saw a long line decided the jersey could wait.
- There was no count of fans walking past versus walking in
- Checkout lines were invisible until fans gave up and left
- Displays and promotions changed without a way to test them
Traffic, shoppers and checkout lines in one view.
Connected to team store cameras via an on-premise server
Existing entrance, floor and checkout cameras fed a lightweight on-premise server Safari AI deployed in the arena, so video was processed on site.
Counted shoppers and timed checkout lines
Computer vision counted fans passing and entering the store, told adults from children, and measured time spent in the checkout line.
Reported traffic by game moment
Dashboards showed traffic, capture rate and checkout wait before the game, at halftime and after the buzzer, so staff and promotions could follow the peaks.
Note: Illustrative data
Shorter lines and more sales, with the same team.
Line wait at every register was measured as it built, so staff open lanes before fans give up and head back to their seats.
Passersby and entries were counted by game moment, showing exactly when the store fills and how many fans a display pulls in.
Adult and child counts through the game showed who was shopping when, so merchandise and promotions reach the right fans.
Action Center: From Insight to Action.
Measurements like these feed Safari AI's Action Center, which moves staff to the registers the moment a line starts costing sales.
- 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 in your own team store.
The Hornets measured store traffic, shopper mix and checkout lines from cameras already in the arena. We'll walk through which entrances and registers are the best fit for a pilot on your cameras.
