SUPPORTING YOUR RETAIL AMBITIONS. People Counter

Transcription

1 SUPPORTING YOUR RETAIL AMBITIONS People Counter

2 People Counter for Retail Chains 5X Metrics in One Device Combining 2 Technologies Video Counting + Wi-Fi Tracking 2015 New Release Model M5

3 5X Metrics in One Device Combining 2 Technologies Video Counting + Wi-Fi Tracking We are the first in the world to combine video analytics counting and Wi-Fi deacon tracking in one device, giving you 6 business metrics: Video Counting Wi-Fi Tracking 1) Footfall Counting 2) Outside Traffic 3) Dwell Time 4) Returning Customers 5) Cross Shopping

4 1) Footfall Counting High Counting Accuracy of 95% or above Employs the most advanced algorithm, Multilayer Background Subtraction based on color and texture, solving the issues with shadows and light level changes. Bi-Directional Counting Counts IN and OUT traffic simultaneously Widest Door Coverage Incorporating a 180º fisheye lens, covering entrance width of up to 12 meters at mounting height of 3.5m Real-time Data Accessible from anywhere with Internet connection Internal Data Storage up to 5 years Counting is not affected, even if network is down. And data will be kept for retrieval when network is restored Additional Features Wide Angle Lens Independent Unit with Powerful Chipset 8GB Internal Storage Connect via Ethernet Discreet and Stylish

5 2) Outside Traffic Footfall counter is a Wi-Fi hotspot itself It detects the Wi-Fi signal emitted by mobile phones It distinguishes the counting data by their unique ID Detects passer by outside the store and giving you an outside traffic count Comparing this outside traffic with the footfall data and giving you the store front conversion rate Wi-Fi data is normalize with video counting data Distinguishes distance from the door detected by the signal strength

6 2) Outside Traffic This data gives you the following insights: A. Although the footfall is one of the peak of the day, but the turn-in rate is similar to the morning time which is low. Perhaps management need to find ways to maximize the turn-in rate during this time, e.g.: Hand out free samples at the store front Distribute flyers B. Footfall is similar to lunch time, however with the turn-in rate we can see it is much higher, probably due to the marketing promotion at that time many yummy mummies shopping after school hours C. High outside traffic after store closing. Management may need to consider in extending store operating hours to catch the traffics

7 3) Dwell Time Measure how long customers stay inside store by tracking unique identifier emitted by each smartphone s Wi-Fi signals as they enter and exit the store. By looking at the dwell time and sales transaction, management will be able to find the pattern matching This data gives you the following insights: A. Customer dwell time decrease and sales drop on this day, perhaps there is not enough staff to serve customers B. Customer dwell time is high, operating team can find ways to increase customer engagement to boost sales

8 4) Returning Customers Distinguishes if the customers have visited the store before by matching the unique identifier with previous records. Measure customer loyalty via the frequency and shopping habits of returning customers This data gives you the following insights: A. Returning customers are relatively higher during weekdays. Introduce loyalty discount or promotion during weekdays to increase customer loyalty B. By comparing with other stores, management will be able to evaluate which stores able to retain loyal customers better Bad performing stores need to find ways to serve customers better. For example, promote loyalty program

9 5) Cross Shopping Compare the unique identifier records from different stores to identify if the shoppers have visited other stores before This data gives you the following insights: A. Visited outlet and main store is high on this week because it is the bank holiday week so customers are more likely to travel far to visit different stores B. 2 or more store is high on this week probably due to the stocks in store A is not enough and thus customers will go to another stores to buy

10 Additional Features Cloud-based Control Panel Allows retailers to remotely manage multiple counters from a central location Easy Installation Counter will be delivered fully configured, so that it s ready to plug and play Accuracy Audit Up to 5 hours verification study by FootfallCam specialist Reporting Dashboard, data analytics and scheduled reports Flexibility of Data Hosting Data can be hosted in either own server FootfallCam s server or your Integration with Other Business System E.g. EPOS system, Cognos, Business Object, etc.

11 Technologies First Generation: Beam Counters Counts when a person or object passes and breaks its beam. Not networked, involves each night manually record counts from the device. Second Generation: Networked Footfall Counter Thermal Counting: Uses array sensors to detect heat sources 2D and 3D Video Counting: Computer vision carries out its image processing to recognize, track and count people. Third Generation: 5 Metrics Counter (Video + Wi-Fi Counting) Video Counting: Uses the most robust image processing algorithm - Multilayer Background Subtraction, based on color and texture to provide excellent counting accuracy (90 95%) Wi-Fi Counting: o Uses Wi-Fi receiver to pick up Wi-Fi signals emitted from smartphones, counting people nearby (outside traffic). o Detect unique Wi-Fi beacon signals, giving additional business metrics (dwell time, returning customers and cross shopping).

12 CONTATTO Corso Venezia, 5 Tel.: contact@tekio.it