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WiFi Smartphone Tracking: How to Maximize Retail Success

Discover the power of WiFi smartphone tracking for retail analytics and people counting. Overcome data limitations and optimize customer experiences.

Retail Business Smarter 

In the fast-paced world of retail, understanding customer behavior is vital for success. But how can retailers gain valuable insights without invading customers’ privacy or causing inconvenience?

Smartphone tracking offers a solution to gain insights. Imagine being a retailer wanting to optimize store layouts, improve product placement, and enhance customer experiences.

Traditional methods fall short, providing limited data. The solution? Tracking smartphones for retail analytics and people counting!

By utilizing smartphones’ WiFi and Bluetooth capabilities, retailers can analyze customer movements and make data-driven decisions.

This guide delves into the benefits, ethics, and innovative technologies turning smartphones into powerful tools for retail analytics. Let’s dive in!

Can You Track a Phone through WiFi?

Yes, you can track a phone through WiFi. When connected to a WiFi network, your phone reveals its unique MAC address. By monitoring WiFi signals, location-based services can triangulate your position.

How to Track a Smartphone

Smartphones can be tracked actively or passively.

Here is a quick rundown of active and passive tracking for Bluetooth, WiFi, GPS, and GSM.

Active smartphone tracking

Active smartphone tracking using GSM, 3G or 4G is illegal in most countries.

It’s also the playground of government security agencies like the FBI, AFP, etc. This method of tracking smartphones is considered a man-in-the-middle attack.

All other methods of active smartphone tracking require a user opt-in as follows:

  • Bluetooth Beacons – the user must have your mobile application installed on their phone and accept the relevant permissions.
  • WiFi – the user must log in to your WiFi network (thereby opting in).
  • GPS – the user must download and install an app with the relevant permissions.

However, actively tracking smartphones is not a viable solution for people counting and retail analytics.

Why? Because tracking a smartphone in this way, the customers must opt-in via an app download or sign into WiFi.

What percentage of your customers would take this action prior to shopping in your stores?

Passive smartphone tracking

Passive smartphone tracking does not require a mobile app or user opt-in.

This method only provides anonymous data, and can be done in the following ways:

GSM, 3G, and 4G Phone Tracking

It’s possible to ‘sniff’ cell phone traffic as it moves between the phone and the cell tower. However, it requires specialized hardware and software and doesn’t provide much value.

It’s also impossible to monitor all 40 channels a smartphone may use to communicate. In addition, the data quality is poor because this data traffic is heavily encrypted.

Moreover, locating a smartphone in a small retail environment when the cell towers are far away is nearly impossible.

Overall, this tracking method is legally questionable, only gathers a small sample size, and is ineffective.

Bluetooth Phone Tracking

Due to the device handshake protocol of Bluetooth, non-standard hardware is required to ‘sniff’ Bluetooth messages. For example, a Ubertooth dongle typically used by app developers for testing purposes.

Sniffing Bluetooth signals is also limited as phones only transmit in response to ‘accepted’ devices (eg. Beacons, smart watches, Fitbit, etc.).

The likelihood of seeing these messages is very low. Also, this tracking method will only provide a small sample size and is ineffective.

WiFi Phone Tracking

Smartphones broadcast WiFi probes in search of WiFi network connections constantly, and intercepting these probes is relatively easy.

As such, this is the most common way of passively (and legally!) tracking smartphones.

Since 2017, smartphones have randomized MAC addresses in these probes. This has made it challenging to provide accurate people count and retail analytics.

However, WiFi phone tracking provides a good sample size. Most people have WiFi turned on, and both iOS and Android use WiFi to locate smartphones. It’s effective in providing useful retail analytics data.

Does It Matter Where the Sensors Are Installed?


WiFi, Bluetooth, 4G, etc., emit a circular signal from the sensor (WiFi router) and the smartphone.

It’s essential to place the sensor in the center of the measurement zone. If the sensor is installed on the sidewall of a retail store, it will also measure the neighboring.

If the sensor is not centrally installed, it will measure neighboring stores. The best place to install a sensor is in the middle of the measurement space, in the ceiling.

It’s possible to use a directional antenna to push a signal in a particular direction. However, this method is costly, ugly (they are large and external to the WiFi router), and ineffective in small spaces.

Their primary purpose is to extend the signal range over a large distance. As such, directional antennas are not typically used by WiFi analytics providers.

How Accurate Is WiFi Heat Mapping?

In short, not very.

The accuracy of heat mapping via WiFi depends on two key factors:

  1. The placement and number of sensors (WiFi routers); and
  2. Whether the smartphone is connected to the WiFi network or not.

How Many Sensors Are Required for Accurate Heat Maps?

The number of sensors required depends on the space you’re measuring.

For example, the minimum number of sensors required for a square or rectangular space is four (4). For optimal placement:

  • Place sensors in the far corners of the space.
  • Ensure the signals overlap to pick up the probes from phones in the space. If less than four sensors detect smartphone probes, the data quality diminishes quickly.

Three sensors can provide triangulation. However, the accuracy is less ideal and not consistent. You can improve the accuracy by placing the sensors within a 5m x 5m box.

It’s also common when using three sensors to place the devices in a straight line between two of the sensors. However, this approach renders this data useless.

Can Two Sensors Provide Heat Maps?

No. Attempting to heat map a space within a small zone of a retail store (e.g. changing rooms) is impossible with two WiFi sensors.

Two sensors are not able to triangulate the smartphone. When using two sensors, the smartphone may appear anywhere in the signal strength intersection of the two sensors.

Using two sensors does not work. A smartphone seen by both sensors may be in the store next door (you have no way of knowing). Additionally, this method will not provide an accurate count of smartphones within a store because neither sensor is centrally placed.

Ok, so let’s assume you’ve got four WiFi routers installed to provide heat maps, what accuracy can you expect?

Heat Maps from Wifi-Connected Smartphones Are the Best

A smartphone connected to the WiFi network provides high data quality. The reason why is that the phone constantly communicates with the WiFi router and updates its location.

However, a smartphone not connected to the WiFi network will only provide location updates each time it sends a probe in search of WiFi. This can be every 6 to 90 seconds.

In an average retail store, with daily visitors of 50 to 1,500 people and location updates every 6-90 seconds, the results are useful. However, not highly accurate.

Customers appear to ‘teleport’ around the store. It’s also impossible to provide path analysis or heat maps with a high level of accuracy.

Use the Right Technology If Heat Maps Accuracy Is Important

If highly accurate (ie. 1-2m2) heat maps are important and you need accurate data to inform store layout, then use a camera or thermal-based people counting technologies.

These technologies provide accurate, reliable, and usable heat mapping data.

Is It Possible to Measure Change Rooms or Other Small Spaces?

Not really. WiFi can measure a range of up to 80m (depending on the antenna).

However, the measurement range cannot be restricted to less than five (5) meters from the access point or sensor. This is due to the dB signal strength readings from smartphones being on a logarithmic measure.

Also, low RSSIs (dB) close to a sensor with high signal strength ‘blend’ together or jump around. Any measures inside 5m become meaningless.

This technical reality of WiFi signal strengths makes it impossible to provide accurate data for very small spaces such as changing rooms.

What Is the Impact of Mac Randomization?

Since 2017, both Apple and Android have progressively increased the randomization of MAC addresses in WiFi probes. This means every time a phone probes for a WiFi connection, it presents a different MAC address.

As a result, it’s increasingly difficult for a WiFi analytics platform to accurately identify the number of smartphones it’s ‘seeing’. For example, if a phone sends 100 probes and only 10 have the real MAC address, do the remaining 90 probes represent 1 phone or 90 phones?

In short, MAC randomization has a large impact on WiFi-based smartphone tracking, particularly when it comes to data accuracy.

What Can Be Done About Mac Randomization?

Skyfii has invested millions in developing proprietary algorithms to uniquely identify smartphones regardless of their MAC address.

Our Blix hardware and firmware collect the full probe packets from smartphones. It also uses machine learning algorithms to ‘fingerprint’ each smartphone.

We train our algorithms on extensive datasets across thousands of Blix sensors. We also use multi-dimensional cluster and probabilistic analysis to fingerprint smartphones regardless of whether their MAC address is randomized or not.

This means Blix is leading the way in WiFi-based smartphone tracking. This innovative solution provides accurate people counting and retail analytics data in spite of MAC randomization.

Discover the Possibilities

Request your demo to discover how WiFi-based people counting, and retail analytics can transform your business

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