Does Seeketing work?
First question of our partners and clients when they discover Seeketing technology is: HOW it works, and once the know its fundamentals, they ask if it really works in real projects, on the ground.
We show below the example of real projects, with results not prepared by Seeketing, the report bellow are generated by end customers and partners in the use of Seeketing technology
A. Comparison with cameras in a median mall of plants, analyzed for several months
Seeketing offers monthly data equivalent to camera systems across the entire shopping mall, analyzing the behavior and movement of more than 350,000 people each month.
So the big difference between data provided by cameras and Seeketing are not the figures or the accuracy , the big different is that cameras only provide overview figures, but Seeketing provides person by person customer journey along each zone of the venue.
B. Comparison with WIFI tracking and cameras over an hour by hour basis, analyzed over several weeks
Yellow - Cámaras
Blue - Wifi tracking
Gray - Seeketing
The Wifi tracking system (blue) generates bad data and much more errors that it does not have relationship with real visitors.
- Depending on the moment and day..., the first day at 12am when more than 20 people enter the shop it seems to work, however at 3pm, when more than 30 people, detects only 4 phones, but Seeketing always has an excellent relationship with the number of people entering the shop.
- Different envelopes to the current footfall hour by hour, when the data of the cameras (yellow) and Seeketing (gray) go up, and the data of Wifi tracking (blue) sometimes goes up or sometimes goes down.
- When there are no people at 8:00AM Wifi systems provides also high peaks of 10 or even 20 detections
And...Wifi tracking systems are be based its identifiers in MAC, which are random, so it can not provide recurring data, time of stay, glues, etc ..
C. Comparison with Tickets in a Supermarket (analyzed for several months)
Seeketing is the only technology that offers unique visitor data, with information on loyalty and recurrence in different days, months of the same visitors, so these data could directly compare with tickets or family units.
D. Comparison Seeketing vs. 3D cameras in a large shopping center of 6 plants, analyzed for several months.
Los datos de Seeketing superan el 85% de precisión todos los meses, respecto a los datos de footfall de cámaras en todos los accesos.
D. Measuring recurrent visitors in the employee access in a office building.
Seeketing is the only technology capable to measure if the people who enter had already done so previously in the day or in previous days, in a completely transparent way to employees and visitors, without users having to take any action
E. Comparison CUSTOMER JOURNEY. Seeketing vs. WIFI tracking and IBeacon bluetooth / Eddystone in a large shopping mall, analyzed for several months
Seeketing provides better location for the most massive visitor group, which never connects to the mall's wifi portal and never installs APPs, even if they always have the open wifi, because they use it at home/job. But it can work even with those who do not have wifi bluetooth open. For this reason massive results are obtained with respect to the total of visitors.
F. Comparison PROXIMITY MARKETING. Seeketing vs. WIFI Social and IBeacon bluetooth / Eddystone in a large shopping mall, analyzed for several months.
Other systems require phones to install an APP, or connect to the Wifi Captive Portal of the mall/shop. Seeketing is the only one that offers high performance to the most part of the public, which does not connect to the mall's wifi portal and does not install APPs, unless they always have open wifi, to use it at home. But it can work even with those who do not have wifi and bluetooth open.
G. Comparison with tickets on transport systems (measurement of origin and destination of passengers on train line for years)
Seeketing's envelop is perfect, always with a accuracy around 70%. Typical deviation from demand are minimal while offering stable data month to month.
