Smartphones are to be known as one of the most impactful technologies of this century. To have the ability to access the Internet anytime, from anywhere has fundamentally altered the work and personal life across the globe.
But recently, the issue that has been making headlines is that in exchange for this level of access to the Internet, people are giving up a substantial amount of privacy and data. This has even led to the fact that organizations are using the channel for obtaining the MAC address to track people through their mobile phones. A MAC address, or a media access control address, is a unique identifier for a network interface, which in turn provides data such as where you have been, are going, how much time you have spent in that particular location and to an extent how many times you have been to a particular location.
Until now, this unique, static MAC address of each Wi-Fi device has been used to uniquely identify a device; but since Apple’s introduction of iOS 8, the new feature uses a random MAC address for Wi-Fi connections. Apple’s main focus behind introducing this feature is to enable additional safeguard measures for consumer privacy, while increasing barriers for vendors who track and gather analytics.
In previous versions of iOS, apps had access to MAC addresses by way of the address resolution protocol, or ARP, tables stored within the device. Now moving forward, thanks to the many misuses of the data that is collected, the latest release of the iOS 11, apps can no longer use the ARP table to view the MAC addresses.
Now moving forward, the retail landscape Bluetooth Beacon technology was a goldmine before the crash. Today we are witnessing another crash in the making — behavior analysis systems, which are based on Wi-Fi access points, and Wi-Fi router technology, which is used to track devices within a retail business and public common areas. This sophisticated level of tracking has been possible because Wi-Fi-enabled devices routinely probe request to search for nearby networks, and these requests contain the unique MAC address of the device. This replaces the number that uniquely identifies a device’s wireless hardware with randomly generated values.
So this brings me to beg the question — does Wi-Fi tracking really work? Let’s go over some of the problems of reusing Wi-Fi infrastructure and the misconceptions of Wi-Fi Tracking systems.
Reusing Wi-Fi Infrastructure Is Limited
Existing Wi-Fi access points and/or Wi-Fi routers heed to the MAC address of the signals that are sent by the smart devices. As the signals are in communication from multiple locations within the business, the Wi-Fi access points can determine where the device emitting the signal is located. But keep in mind, any existing Wi-Fi access point at any retailer is in a position for a certain optimized coverage, not in analytics usage. So, it is impossible to obtain accurate and useful location insights for the business layout. The viable option would be to increase the number of Wi-Fi access points to increase the accuracy, but in turn becomes a very expensive solution.
Big Errors In Detection
All vendors for Wi-Fi routers or access points provide an API that communicates with the MAC addresses from the signals to identify the smart device. This is the core functionality for solution vendors of Wi-Fi tracking and analytics systems. But today, a majority of new smart devices in the market are emitting multiple MAC addresses when they are not even connected to the Wi-Fi access points.
For example, one iPhone is able to produce 20 or more different and/or false MAC addresses when visiting a store for 30 to 40 minutes. So, imagine a customer comes into the store at which the smart device is in use — the MAC address is captured. Then the customer begins his/her journey through the store but puts the smart device on sleep mode, once the device is turned on — a second MAC address is generated for capture.
Here-in-lies the dilemma where Wi-Fi tracking solution vendors are offering statistical data to the retail sector, which in turn is false information and misleading. At the current state, there is no viable solution to this particular dilemma.
Only if the smart device is connected to the Wi-Fi to access free Internet, only then can you be able to detect the unique MAC address of the device. But this also goes to beg the question, how many visitors actually opt into the free Internet service? In general, no more than 10 to 20 percent.
Many of the solutions that we are witnessing in the market have been developed by engineers without any real experience and without feedback from the retailers.
Followed by visitor counts is the heatmap solution, which is used to detect highly populated shadow zones. Heatmap data is based on triangulation of signal strength by using several access points, but primarily depends on the position of the smart device. As it is in constant motion, the signals would not be received by all Wi-Fi access points, and depending on the obstacles in the path to each access point the signal strength varies.
In a real setting, the location data that is obtained is poor and/or misleading, as the location accuracy cannot exceed more than 20 to 25 square meters. In short, the Wi-Fi heatmap analytics data provided would not have actionable information for a retailer, as its main focus is to understand the traffic by each aisle/zone with each product.
Communication With Apps Is Limited
The main focus for any retailer to collect data is to implement a strategy which drives the consumers into the business and/or to create a window of opportunity to connect the consumer with the brand on site. For a beacon, this would serve as an added purpose as it would be able to interact with an app once the customer is in the vicinity.
When it comes to Wi-Fi detections, the possibilities to detect high volumes of different smart devices are endless, compared to beacon results. But the problem herein lies that you would not be able to send push notifications to the app using or reusing the Wi-Fi infrastructure. The reality of the matter is that there is no such solution in the market based only in Wi-Fi access points capable to do as such.
So, by reusing Wi-Fi infrastructure you would only be able to utilize the analytics features, but with little to none on actionable data to use for interacting with customers within the store. Unless the customer has opted into using the free Internet access service, but this form of Wi-Fi solution retailers have been using for decades.
Retailers are now sourcing out omnichannel solutions, which is becoming a modern approach to commerce that focuses on designing a cohesive user experience for customers at every touchpoint, mixing online and off-line or in-store concepts.
Thus, leading to a solution based in specific radio sensors and SDKs is required to be designed in order to solve the gap to connect both worlds. This would allow connection to even the standard IT infrastructure: CRM, APPs, WEB, Wi-Fi, POS, Digital Signage and Digital Advertising (double-click networks, etc.)
In the long run, the technology must be able to provide a full plug and play feature with a dashboard and web service delivering data about the KPIs, which have been configured. The KPIs would be essential to determine groups of a segment of consumers’ profiles and to impact them using proximity messages to their smart device. It could even be used with APPs or without the APP installed. So, we can say the beacon barriers and the reusing of Wi-Fi access points could become a thing of the past.
There are few solutions out in the market today which are trying to bridge the gap, or claiming to do so, but the fact of the matter is that there still not a viable one-stop solution.
Rajiv Prasad is the chief information officer at Xpandretail, which is powered by Sávant Data System.