After boom and crash of bluetooth ibeacon technology another boom and future crash are behavior analysis systems based on Wifi access points and Wifi routers technology to track devices in retail and other public areas with existing Wifi access points.
Lets talk about the problems of reusing wifi infrastructure and mis-understanding about Wi-tracking systems.
1. Reusing WiFi infrastructure is not enough
Existing Wi-Fi access points and/or Wi-Fi routers listen the MAC Address of the signals sent by smart devices. By listening to those signals from multiple locations in the store, they can start approximating where the emitting device is located, but existing Wi-Fi access points at any retailer have been located originally thinking in optimize coverage not in analytics usage, so it is imposible to obtain accuracy and useful location insights for the venue (categories of products visited, customer journey, ...), excepting the presence or not in the venue (for example for very small shops), but this presence detection has more errors….
So to increase the number of wifi access points trying to increase the accuracy is a very expensive solution.
2. Big errors in detection
All wifi router or access points vendors provides an API which listen the Mac Addresses of the signals to identify smartphones, this is the base of solution vendors of Wifi tracking and analytics systems, but almost new smartphones emit several Mac Address when they are not connected to the WiFi access point (not associated devices).
For example, only one iPhone can produce 20 or more different and/or false mac addresses when visit a venue during 30-40 minutes.
Wifi tracking solution vendors are offering statistics and data to the retail based on these false data, and there is no accuracy way to avoid this issue using existing WiFi access points.
Only if the smartphone connects to the WiFi to have free internet access, you can detected the true MAC address of the iPhone. But how many people of total visitors use the free internet service? In general no more than 10-20%
3. Data not actionable
Most of the solutions based on wifi tracking have beed developed by engineers without any real experience and without feedback of the retailers.
Main data provided is called "heat map" supposedly used to to detect shadow zones for example.
Heat map data is based on triangulation of signal strength using several access points, but depending of the position of the smartphone (because they are constantly moving) their signals could be not received by all Wifi access points, and depending on the obstacles in the path to every access point the signal strength is different. So with real conditions obtained location is poor and even with big mistakes for every smartphone, it is not possible to have more location accuracy than 20-25 square meters even with more than one hundred of access points in a small venue. So the wifi analytics heat map has not actionable information for a retailer which is interested to know traffic by every aisle even by every product.
And if the heat map is the average of thousand of these signal during a day for example then the heat map will show red and blue areas in the same position day by day, which obviously are zones well know by the retailer or by simple observation during 5 minutes in the venue.
3. No interaction with Apps is possible.
What is more important to any retailer is to obtain data to drive customers to store or to increase their average ticket, and this implies to interact with those clients that are in-store. That is the beacon main advantage (interaction with App in-store), but most of the retailers know yet that there are a very few people who can interact with beacons. Read more click here.
With Wifi detections you can reach to detect thousands of different smartphone (10-20% are true smartphones), of course these figures are much higher than beacons results. The problem is that you can not send a push notification to the App using or reusing the wifi infrastructure, there is no solution in the market based only in Wifi access points capable to do this.
Some Wifi solution providers include in the same box an access point and an beacon, and they sell that these is a complete solution. But every system (wifi APs data and ibeacon data) work complete separately, there are no cooperation between them at all. So retailers will get same results that if use beacon from one vender and wifi analytics of other vendor.
So reusing wifi infrastructure can only produce analytics features, but with no actionable information or data to interact with customers in store, unless they use free internet access service, but guest wifi is a solution that retailers are using 15 years ago.
4. Other alternative
Retailers now are looking for omni-channel solution, mixing online and offline or in-store concepts, because they know that people is the same in both environments.
Seeketing is the only technology that provides solution for unique device identifier both online and offline. With 5 years of experience in airports, retailers, transportation system, digital signage and smart cities, is based in specific radio sensors and sdk´s designed to solve the gap to connect both worlds, even can be connected to the standart IT infrastructure: CRM, APPs, WEB, WIFI, POS, Digital Signage and Digital advertising (double-click networks, etc..)
The technology provide full plug and play solution with dashboard and web service providing figures about the KPIs configured, not only heat maps. This KPIs are useful to decide groups of segment of the customers (profiles) and to impact them using proximity messages to the smartphones. It can we used with APPs or without APP installed. So most of the barriers ibeacon and reusing Wifi access points are overcome with Seeketing technology.
In-store detection is based on listening 2,4 Ghz and 5 Ghz frequency bands (even they can work with other cellular bands). Seeketing nodes not only use MAC addresses to detect and identify smarphones, they recognize patterns of signals based in full signal parameters. With Seeketing nodes can provide information about approximately 70% of total visitors to the store.
Seeketing is not based in triangulation so accuracy is related only with KPIs needed to obtain, not with size in square meters to cover. Every Seeketing nodes can cover about 15.000 square meter, and they will be located only depending useful insights for retailer so only one seeketing node could produce useful KPIs based on thousands or millions of devices detected, with so less cost than to enlarge the wifi infrastructure.