Example study, illustrative data Retail research

Foot traffic for a fashion brand

A fashion retailer feels busy but sales do not match the crowd. Two weeks of counted footfall, hour by hour, shows when people come, how many convert, and where the store leaks buyers.

The question

We look busy, why are sales flat, and when do we actually need more staff?

Method

Door counts, in store observation, conversion tracking and mystery purchases

Sample

One flagship store, 14 days, 18,840 counted visitors

Timeline

4 weeks including the reporting session

The rhythm of the store

Footfall by hour, two weeks combined

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Visitors counted, two weeks0
Overall conversion4.6%
Peak hour18:00

Gold bars mark the peak hours. Illustrative values.

Where buyers are lost

From the window to the receipt

Passersby at the window100%
Entered the store18%
Reached a fitting room7%
Purchased4.6%

In this example the store loses most of its buyers between the door and the fitting room in the two peak hours, a staffing problem, not a product problem.

Findings

What a study like this delivers

An hour by hour footfall curve that puts staff where the customers are

A conversion funnel showing exactly where buyers drop out

Peak hour service checks from mystery purchases

A before and after benchmark to prove the fix worked

All figures on this page are illustrative examples, not client data. Your study produces the same charts with your market's real numbers.

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