How are shoppers being monitored by Wi-Fi?

The gap between these online and offline stores has rekindled the advent and explosion of technological advancements that allow users to analyze behavior when visiting normal stores. Wi-Fi has become the most popular and flexible tool for this job and is also used by many retailers.

The way retailers measure consumer behavior in stores is constantly being interfered with unprecedented speed. The main reason is because of the sublimation of the online stores we have witnessed in the past few years. These stores are extremely successful in creating an "invincible" shopping experience. This is thanks to a secret weapon that online stores have owned for more than a century: collecting detailed and real-time analytical data in real time about each website visitor, from there optimize and personalize their shopping experience based on collected data .

In contrast, normal stores can only be measured by methods based on the store's operations such as counting the number of people who set foot in the store or the transaction data through the POS payment system ( Point of Sale). It is understandable that these methods are not accessible to customers as the behavioral analysis data that online stores currently use. Because these data are selected for each customer, right in real time and from there will bring a better shopping experience.

Wi-Fi is the most versatile technology for analyzing modern stores

The gap between these online and offline stores has rekindled the advent and explosion of technological advancements that allow users to analyze behavior as soon as they visit normal stores.Wi-Fi has become the most popular and flexible tool for this job and is also used by many retailers .

When compared to counting the number of people entering the store or POS data, Wi-Fi is able to analyze all (and repeatedly) the number of visits to the store, providing real-time data about socks. whole space throughout the store, it can also provide path directions, distance-based services and customer marketing . Most importantly, none of the above data requires an application installed on the customer's device, meaning that accessibility to customers will be much better than other application-based technologies.

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Decode Wi-Fi analysis mechanism

Because this technology is relatively new, many people will want to understand how Wi-Fi collects and analyzes user behavior. Here is the working mechanism of this technology.

Step 1. Our devices "talk to themselves"

Even without Wi-Fi connection, devices that can turn on Wi-Fi are still continuously emitting signals to detect and connect to available Wi-Fi networks around. This happens every 15 to 30 seconds depending on the hardware of the device. Call these signals "ping".

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Step 2. Transmitting and Wi-Fi sensors detect signals sent from the device

Wi-Fi hotspots are available and / or Wi-Fi sensors will "listen" to ping signals sent from the phone, and along with that, the weak strength of these pings. By listening to ping from many different locations in the store, we can estimate where the device emits a ping signal.

Step 3. From signals to customer location observation

The Wi-Fi analytics solution has built-in advanced algorithms, uses weak signal strength and other parameters to detect the presence and location of all Wi-Fi enabled devices. Other filtering algorithms are used to exclude static devices and employee equipment, along with fixing errors or other deviations in the observation process.

Step 4. From observing to behavioral trends

With a series of location observation results in customer stores, this tool can analyze an entire customer's "visit", where they go to the store, according to the what order and spend time in each location . Thanks to that, you can experiment and see the results of other changes such as layout of goods, marketing . and then choose ways How to make customers most satisfied.

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Will Wi-Fi analysis change the way retailers manage stores

With these capabilities, normal stores can quickly keep up with the speed of online stores in the field of measuring and optimizing the user experience based on the actual behavior of customers. This means offline stores can now manage their stores like online stores: measure conversion rates, keep monitoring and optimizing, experiment with new things, take a close-up look. into the behavioral trend of shopping, behavior-based segment .

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We can also see the emergence of many other applications such as optimizing staff positions based on customer needs, tracking, managing assets, and delivering location-based marketing messages. of the user.

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