1.1 How Does Wi-Fi Counting Work?
1.2 5x Metrics in One Device
Combining 2 Technologies - Video Counting + Wi-Fi Counting
We are the first in the world to combine video analytics counting and Wi-Fi beacon tracking in one device, giving you 5 business metrics:
1.2.1 Video Counting
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Footfall Counting
1.2.2 Wi-Fi Tracking
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Outside Traffic
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Dwell Time
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Returning Customers
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Cross Shopping
1.3 Video Counting Combine with Wi-Fi Counting
Video counting technology is used to count the total number of people that enter and exit the site. Meanwhile, Wi-Fi technology enables the counter to capture the unique MAC address from smart devices people carry and provide further analysis, such as zone analytics, dwell time, passer-by count, turn-in rate, traffic flow, returning customer rate and cross shopping.
- Visitor Count
- Visit Duration
- Cross Shopping
- Outside Traffic
- Returning Customer
1.3.1 Visitor Count
FootfallCam's people counter can help to find out the number of people that enter to your store. It conducts bidirectional counting, which allows it to count in and out simultaneously. FootfallCam achieves a high counting accuracy of 95% and above by employing the most advanced algorithm, based on both color and texture mapping, identifying and solving any issues with shadows and light level changes.
1.3.2 Street Counting
Using video tracking technology to identify the number of shopper passed by the store. Able to identify the absolute number of the people passed by the store front. It gives retailers to understand the window display effectiveness and overview on the miss-opportunity of the branch.
1.3.3 Visit Duration
Visit duration is measured based on unique identifier (MAC ID probes) from user's smartphone. It could approximate the time of a visitor entered and left the store. You can know how long your customer stay in your store. And also, by looking at the dwell time and sales transaction, management will be able to find the pattern matching.
1.3.4 Outside Traffic
FootfallCam can detect user's position within 100m radius. Based on the signal strength, it detects passer by outside the store and gives you the storefront conversion rate by comparing with the store footfall. We will have answer for queries such as how many missed opportunity outside the operating hours and how many people passing through has actually visited the store.
1.3.5 Returning Customer
Distinguishes if the customer has visited the store before by comparing the unique identifies with previous records. You are able to find out how many customers have returned in last 3 months. This can be used to measure customer loyalty via the frequency and shopping habits of returning customers.
1.3.6 Zone Analytics
Location analytics uses advanced data mining techniques tuned to the type of data Wi-Fi location provides. Location analytics provides two methods for defining the different zone or area of a venue. Explicit zones can be defined by the user as named polygons that represent known defined spaces. It could be identifiable by its Zone ID.
