DATA STUDY
Real JamBox data from a high-traffic NYC retail location. See what footfall analytics can tell you about customer patterns, peak hours, and seasonal trends.
One month of footfall data from JamBox revealed powerful insights about customer behaviour.
Hover over the charts to see detailed numbers. Click legend items to show/hide data.
See how traffic varied throughout the month. Notice the holiday surge in the final weeks.
Average footfall by hour of day. Peak is 6pm-10pm.
Weekends see 23% more traffic than weekdays.
Compare rainy days vs dry days. Rain significantly reduces foot traffic.
Most retailers face these challenges without accurate traffic data:
Without footfall data, managers schedule staff based on intuition - often overstaffing quiet periods and understaffing peak times.
You know your sales figures, but without visitor counts you can't calculate your true conversion rate or benchmark improvements.
Holiday staffing is typically based on last year's sales. But sales don't tell you how many people walked past without buying.
Peak footfall consistently occurred between 6pm and 10pm, with 9-10pm being the busiest hour. This was surprising as the store had always focused staffing on lunch hours. The Times Square tourist crowd peaks in the evening.
Weekend traffic averaged 109,614 visitors daily compared to 88,889 on weekdays - a 23% increase. Saturdays and Sundays required fundamentally different staffing models.
The week of December 20-28 saw daily footfall jump to 130,000-153,000 - nearly 60% above the monthly average. Dec 21st hit the peak at 153,406 visitors. Christmas Day itself saw 152,185 visitors.
On December 3rd (13mm rain), footfall dropped 30% compared to similar dry days. This data now triggers automatic staffing adjustments when rain is forecast.
Understanding when customers arrive transformed how the store operates.
With one month of JamBox data, retailers can make informed decisions about:
Most retailers assume they know their busy periods. This data often reveals surprises - like peak traffic occurring in the evening rather than at lunch, or weekends being 23% busier than expected. Without measurement, you're guessing. With JamBox, you know.
Here's what a store manager could do with these insights:
The data shows peak traffic at 6-10pm, not lunchtime. A manager could reallocate staff from morning to evening shifts to better match actual demand.
With weekends 23% busier than weekdays, there's a clear case for adding weekend coverage rather than spreading staff evenly across the week.
The Dec 20-28 surge to 130K-153K daily visitors was predictable from the trend. Next year, this data justifies hiring seasonal staff for those specific dates.
The 30% drop on rainy days (Dec 3rd) suggests staffing could be reduced when heavy rain is forecast, saving labour costs on predictably quiet days.
JamBox installs in minutes and starts delivering insights immediately. No complex setup, no ongoing fees surprises.
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