15 Technologies of People Tracking
If you think you need in-store customer tracking, you do.
Anonymous customer tracking solutions are often used by retailers, brands, and malls, to measure shopping behaviors.
Regardless of the tracking system, the positioning and time data quantify the opportunity, and the performance, of a physical location.
If you are a decision maker,
You should know –
(PRO Tip) In 2019, the PIVOTAL People Tracking Systems include Location Analytics, Facial Recognition, and Vision.
Here is what it means –
Location Analytics refers to comprehensive tracking solutions. The applications forecast the demand for the physical location, provide competitive benchmarks, and count people entering and exiting.
Facial Recognition refers to B
Vision is Image-based Deep Learning AI. The technology is most known in driverless cars.
You should also know –
People Tracking technologies can be Anonymous or Interactive (require the customer’s consent with Opt-In).
And the in-store customer solutions can also be Sensor-Based, Device-Based, and embedded with Advanced Analytics.
And you should pay attention to –
(PRO Tip) The people tracking solutions are defined by HOW they capture location (position) and time (how long) of the object (person). Details matter.
15 People Tracking Solutions are:
- (AI Deep Learning) Vision
- Biometrics (Facial Recognition & Demographics)
- 3D Spatial Learning (Augmented Reality)
- 3D Stereo Video Analytics.
- 2D Monocular & Fisheye Video Analytics
- Thermal Imaging
- Infrared Beams
- Time of Flight
- Structured Light
- Open Source Raspberry Pi
- WiFi (Wide Area Network) Tracking
- UWB (Ultra Wide Band) | Radar Imaging
- BLE (Bluetooth Low Energy) Beacons
- GPS (Global Positioning System) Personal Trackers
- RFID (Radio Frequency Identification) Tags & Tracking
The complexity of the system depends on the position of objects (i.e. in-store or street), the state of objects (i.e. a person in motion or product image), and the attributes of the object (such as device-based tracking or facial recognition software).
This is important because –
(PRO Tip) The #1 challenge is HOW to translate the tracking data into actionable information. In 2019, focus on Customer Success.
Why Track People?
The best way to think about tracking people is in terms of business benefits.
Location-based data serves a wide variety of sectors, including Buildings, Hotels, Hospitals, Transportation, Smart Cities, and Retail.
Regardless of the market, Location & Time data provide information on the foot traffic, occupancy, and demand trends for a physical area.
Depending on the technology, solution, and vendor, the people trackers provide a wide range of performance metrics.
Here’s the problem –
Many retailers, brands, agencies, investors, and solution providers, are confused over the plethora of technologies, terminologies, and hype.
“Even at the highest levels, retailers don’t really understand either the rewards or the risks associated with anonymous vs. non-anonymous customer geo-location data.” – RSR Research
The following are topics you should think about & why –
Interactive Vs. Anonymous Tracking
If there is one thing you should remember is –
There is a difference between the solutions that identify shoppers by name (Identity) and those that track people anonymously (random ID).
Tracking people really means “quantify behaviors”.
This is important –
Interactive technologies require the customer’s consent.
The customer’s opt-in is done online, in a digital form. It can happen in the operating system (Google or Apple), application (Facebook or Shopify), or the telecom companies.
Since the customer’s consent often belongs to a third party, retailers and brands are now stepping up on the business model of Direct-to-Consumer.
Interactive tracking is also an integral feature of digital devices for employees. Most store systems – from scheduling to task management – also generate location and time data.
Anonymous tracking refers to systems where captured objects are recognized by attributes (i.e. head of a person) and identified by a random ID.
The fact is –
(PRO Tip) The technologies track objects based on Random ID. The solutions can be adapted to Location Marketing (Opt-In) or Location Analytics (Anonymous)
Here’s what everyone wants –
Customer Tracking (Location Marketing with Device-Based Real Time Tracking)
Location-Based Marketing deploys ads and promotions based on the location of the consumer’s mobile device.
Google “Near Me…” is an example of real-time customer tracking.
Location-Based Marketing (customer tracking) solutions track a specific individual once the person had opt-in to the client-side of the application.
Even if your primary objective is Real-Time Location Marketing…
These are challenges to retailers and brands:
- The consumer’s consent is often to a 3rd such as Facebook and Google.
- Young adults tend to have more than 1 device (which creates havoc in the data)
- Older adults may not have smartphones (with no WiFi Tracking)
- Some people deride real-time location tracking due to privacy concerns (me!)
- Store performance requires data on all behaviors (where anonymous tracking excels)
Here’s the thing –
(PRO Tip) Store Performance metrics don’t require the shoppers’ identity. On the contrary, retail store analytics are better with anonymous customer tracking.
And so…you should inquire about –
Location Analytics (Spatial Intelligence)
Location intelligence , or spatialWikipedia
intelligence ,is the process of deriving meaningful insight from geospatial data relationships to solve a particular problem. It involves layering multiple data sets spatially and/or chronologically, for easy reference on a map, and its applications span industries, categories, and organizations
Location Analytics refers to insights gained from capturing the person’s location.
In retail, Location Analytics measures the VALUE of the bricks-and-mortar store.
If you managing stores…
You should have Demand Analytics and People Counting.
And you should continuously monitor the Key Performance Indicators (KPIs) of Foot Traffic and Proximity T
Location Analytics is also used inside the bricks-and-mortar store.
You should work with location data in layout design (path analysis), checkout areas (queue management), and product positioning (customer engagement).
Here are common business benefits from Location Analytics:
- Shopper Traffic to store (#Visitors)
- Proximity Traffic (% Capture Rate)
PhysicalStore Site (Trade Area Analytics)
- InStore Product Positioning (Path to Purchase)
- InStore Employee Locations (Service Productivity KPIs)
- InStore Live Map & Product Information (Path Analysis)
While In-Store Optimization is what retailers want, the first step is to measure the beginning and end of the sales cycle.
In physical retail, we start with the point of entry to the store.
(PRO Tip) @Door counts is the entry point to the Physical Store’s Path to Purchase.
To recap –
Location Analysis at the door can be done with a people counter, device-based personal tracker, or with the more advanced tracking technologies.
Here’s another common question –
What’s the difference between “People Counting” and “People Tracking”?
The short answer is – People Counting is a subset of Geo-Location Tracking.
Here’s the longer version:
People Counting (Object Detection for Foot Traffic Analytics)
People Counting is estimated at $15.5 Billion market by 2022 – Fior Markets Reserach
People Counting refers to technologies solutions that “count” the number of people that either pass a virtual line or stay inside a specified zone.
People Counting Solutions generate linear data if the object is detected, or not.
Some solutions also recognize the direction of the object (path), provide In/Out counts, and Dwell Time.
Common technologies include Video Analytics, Time of Flight, Infrared Beams, and Thermal Imagining.
People Tracking refers to objects (humans) in motion.
The common tracking technologies are used in Location Intelligence –
Geo-Location Analytics (Object Tracking)
50-60% of perceived value is captured from location-based data.McKinsey Global Institute
In addition to detecting the object, the people tracking solution needs to recognize the object. There are different levels of object recognition.
- People Counting identifies “heads”
- WiFi tracks the location of Smartphones
- BLE Beacons uses opt-in customer data
- RFID tags and tracks product SKUs
- Facial Demographics identifies gender
- Biometrics captures individual faces
- Vision Analytics can “recognize” images
Since the technology needs to “predict” the future track of the object, the more advanced solutions use machine learning and advanced analytics techniques.
Shopper Tracking (or Customer Tracking) refers to solutions that connect between the tracked object (often a smartphone) and the owner’s identity (shopper).
Anonymous People Tracking is currently used in InStore Customer Analytics, Labor Analytics, Queue Management, Product Positioning, and Path Analysis.
“Location Based Services are expected to reach almost $62 Billion by 2022” – Allied Market Research
And one more topic of confusion to clarify 🙂
Sensors vs. Device-Based People Trackers
Sensors and Device-Based are often complementary solutions. Each technology has its own challenges and benefits.
In sensors, we care about the accuracy of tracking ALL objects within the Field of View.
The wireless technologies are distinct by their range and the accuracy between “captured” and “actual” position. In that sense, the technology tracks the behavior of an individual device.
Regardless of the technology, solution, and provider, the data quality depends on the principles of Good Enough Accuracy.
Let’s take a closer look at the technologies* –
(PRO Tip) Since the market changes as fast as these words are written… focus on your positioning and the business problem you are trying to solve.
*We are technology and solution provider agnostic, and this list should not be considered as recommendations.
(2019 Embedded) Advanced Technologies
Tracking customer behaviors is a side benefit from the Advanced Technologies such as Deep Learning Vision, Facial Recognition and Augmented Reality.
These advanced solutions are part of massive Big Data and Cloud ecosystems. In physical stores, they are integrated with the Internet of Things (IoT).
In physical retail, there are two core trends that will impact our objective of building the early adopters framework for In-Store Optimization:
- Today, Behavior Analytics is defined by Location and Time data. It will be expanded to include facial sentiments, body motions, and engagement with products.
- In-Store Loyalty Opt-In applications will allow retailers to develop Growth Loops for VIP customers. This trend has a profound impact on the future of retail.
(AI Deep Learning) Vision
30% of retailers will have up-to-date computer vision technology in place over the next 12 monthsRIS 29th Annual Retail Technology Study: Retail Accelerates (March 2019)
Vision Analytics works by recognizing patterns in images. The Deep Learning AI software translates the images to data, context, and action.
The output is a quantified description of the image, such as Stanford University’s cat or a person. Vision technology has many applications, from driverless cars to medical imagining.
In retail, Vision technology works hand-in-hand with facial recognition and product imaging in these three applications:
- Automated Stores: Vision technology is used to identify the people who walk into the store (facial recognition), grab a product (product imagining), and walk out (connect identity to checkout process). The most known example is Amazon Go.
- Inventory Visibility: Vision technology is embedded in robotics. The Robots stroll the shelve and search for out-of-stock and assortment compliance events.
- In-Store Customer Loyalty: Vision technology is found in beauty applications, personalized promotions, and recognizing VIP customers as they enter the store.
(PRO Tip) Vision is a set of deep learning algorithms, which are molded to solve a specific problem. The expertise comes from the details of training the software.
This is the trick –
Vision technology can also power up Anonymous In-Store Customer Tracking.
Biometrics (Facial Recognition)
Facebook biometric software works as well as the human brain.
Retailers, brands, and shopping centers need to consider two factors when dealing with facial recognition: government regulation and consumer sensitivity.
There are significant differences between continents, countries, and communities in attitudes to privacy and regulation. The European Union created GDPR. In China, the government actively supports the development of facial recognition technology.
In the United States, the retailers and brands are conflicted between the obvious benefits from facial recognition and concerns about a backlash due to inaccuracy and privacy.
To deal with consumer sensitivity to privacy, you have 3 options:
- Facial Identification: the technology compares an image to a given image within a database. Facial Identification is often used for security and surveillance.
- Facial Selfies: the same tech as facial identification with one caveat – the person uploads self-image, tags it, and consent to sharing the data. Used in loyalty programs.
- Facial Demographics: the software process facial features and the output is data on gender and age. The identity of the face remains anonymous.
(PRO Tip) The nuances of privacy and consent are muddled by HOW the data is stored and processed. Pay attention to facial attributes.
3D Spatial Learning (Augmented Reality)
Augmented Reality “adds” images, sounds, and text, to what we see in the real world. The personalization is driven by powerful analytics engines.
The craze over Augmented Reality started with Pokemon Go.
You see the future of retail in the AR Dressing Rooms of GAP and Sephora Beauty Studio.
(Pro Tip) A fascinating new trend is merging of Deep Learning AI, Facial Recognition, and Augmented reality in a digital application that will be embedded in-store. Watch out for Microsoft.
Here’s the thing –
Any advanced in-store technology that tracks what people do should also be used as a platform for anonymous analysis of people behaviors.
The trick is which parts of the data you use for which business benefit 🙂
(PRO Tip) Voice is also a technology that generates location data. Watch this space for an update as voice speakers start to show up in stores and malls…
Anonymous in-store customer tracking, however, starts at the store –
Sensors @Edge Technologies
Traffic sensors are varied in their ability to process Edge Computing. This means the tracker captures the raw data and process the metrics.
The core objective is of a sensors-based solution is to provide analytics at the edge (in the store). The output to the corporate server is a metrics file.
3D Stereo Video Analytics
Stereo video sensors are designed for tracking objects across the camera’s Field of View.
The 3D sensors include a high-resolution camera and processor for the three-dimensional capture of the object.
The 3D Stereo architecture allows for accuracy of high-volume traffic, queue management, and other complex behaviors.
(Pro Tip) In 2019, premium 3D Video Sensors should include a method to exclude the counts of employees with WiFi connectivity, image tags, or facial recognition.
2D Monocular & Fisheye Video Analytics
Monocular sensors capture images through a single lens camera. It also includes the
Regardless of the lens, the sensor process the image, and the output is data counts.
For in-door people counts, monocular devices can achieve 90% accuracy in 90% of stores. This is a cost-effective tracking solution for mall stores and in-store events. The fisheye cameras (used primarily for security surveillance) and monocular sensors are widespread.
(Pro Tip) While two eyes are better than one… which is the reason 3D sensors are more accurate than 2D… the monocular sensors @edge are getting smarter with the embedded software of Deep Learning Vision.
Thermal Imaging detects emissions from moving objects. Since thermal technology is not sensitive to light, it can function in any physical space. The challenge is the “blending” of a person’s heat signature with the surrounding environment.
Time of Flight
Time of Flight detects the time of light between the camera and the object. By sending the laser beams to many directions, the sensor knows the exact positioning of objects. The laser sensors are accurate and cost-effective.
The expertise in laser will allow companies such as BEA Helma to embed people counting software directly into door sensors.
Moreover, the system over-counts and under-counts with no data consistency. Therefore the data quality is not recommended by professional data analysts of @Door Traffic.
Microsoft’s Kinect is also designed with Time of Flight. It detects motion, body-type, and facial features, within 1 cm depth and 3 mm in width.
Structured Light projects a known pattern on a scene. An array of lights strikes the surface and calculates the depth and surface of objects. People Tracking requires Structured Light 3D Scanning.
(Pro Tip) Regardless of the benefits in premium technologies, low-cost trackers offer an attractive proposition in certain store environments and business objectives.
Infrared Beams count when a person crosses the doorway and “cuts” the streaming beam. The advantage is low cost and simplicity. The challenge is accuracy.
The infrared sensors cannot recognize the direction of motion. They also have trouble differentiating between one or more people.
Open Source Raspberry Pi
The hardware of the (Open Sourced) Raspberry Pi can be adapted as a people tracker. This is a low-cost solution but is challenged by accuracy and support.
(PRO Tip) Sensors @Edge are still the best bet for anonymous in-store analytics because they cover ALL behaviors and they can solve the privacy conundrum.
Device-Based (Personal) Trackers
Device-Based Solutions are defined by their core assumption that the device represents the behavior of a specific individual.
This is the distinct difference between sensors and devices. The sensors generate information on a Field of View. The capture of
As a result, these solutions have both marketing and analytics benefits. And in that sense, assessing the value of the tracking solution starts with the question – is the business benefit depends if the customer opt-in the application.
GPS Personal Tracker
Global Positioning System (GPS) is a network of orbiting satellites. GPS tracking is build-in the Apple and Android operating platforms.
In 2015-17, Google’s location-based queries based on Near Me grew 900% (see above). And retailers can subscribe to Google Store Visits.
WiFi Location Analytics
WiFi is a standard for Wireless Local Area Network (WLAN). Antennas capture the radio waves from mobile phones and cover a range of up to 100,000 square feet.
The MAC Address is unique per device and therefore we can assume it represents an individual customer. The data output depends on the customer’s phone and
WiFi suffers from the challenges of location accuracy. But WiFi customer tracking is ideal for large venues such as airports, stadiums, and Shopping Malls.
Bluetooth Low Energy (BLE) Beacons function in the wireless range between NFC (payments) and WiFi. Beacons are ideal for secure communication with customers. Beacons are the preferred tech for in-store customer tracking.
Beacons face two core challenges. First, customers need to opt-in to the retailer’s application or QR (square barcode). And second, GPS/WiFi technologies are improving fast to work indoors.
UWB (Radar) Location Tracking
Ultra Wide Band (UWB) functions in low-energy, short-range, and high-bandwidth environments. UWB comes from Radar Imaging and is entering the retail space.
RFID Location Tracking
Radio Frequency Identification (RFID) uses electromagnetic fields to identify and track tags attached to objects. In retail, RFID is primarily used for supply chain and loss prevention applications.
As RFID adoption rate gains momentum, retailers are looking for more benefits. As such we see shopping carts and employee access cards outfitted with RFID.
(PRO Tip) The differences between @Edge sensors and (personal) device trackers solutions are compounded by analytics. Data expertise is a competitive advantage.
What’s the BEST Customer Tracking Solution (Tool) in 2019?
Is there a BEST People Tracking Technology?
Each shoppers tracking technology has its challenges and business benefits.
Is there a BEST Customer Tracking Solution?
Each people tracking solution has its own nicks and knacks.
Most important –
The VALUE of a tracking solution depends, first and foremost, on the business objectives of the retailer, brand, or shopping center.
Are the same people tracking technologies be used in concept stores, traditional retail, and shopping malls?
Yes. But, again, the decision which customer tracking is best for you and your company depend on YOUR business priorities and objectives.
(Pro Tip) The #1 question you should ask is “What are my objectives today?” and #2 question is “Why?” Hint- this is where many decision makers and teams fail…
Do you recommend a people tracking solution or a provider?
How should you choose a customer tracking solution?
You should follow a consistent & clear framework to manage your tracking project.
You can differentiate between three categories of players:
Vibrant regional companies include Headcount, Lighthouse, and Axper in North America, Xpandretail in Dubai, Pygmalios in Bratislava, TechBrain in Barcelona, Intelligenxia in Chile, and Unicross in China.
Retail security and technology deployment companies are providing installment, calibration, and professional services for tracking solutions. For example, Hollander Techniek in the Netherlands, Halo Metrics in Canada, and ASH Projects in Europe and the United States.
You can also identify the fusing of marketing expertise with anonymous in-store tracking.
And the third trend is…
Big software and consulting companies are entering the market with end-to-end retail analytics platforms.
IBM and Intel, for example, are creating ecosystems of connected solutions and advanced analytics as part of their Internet of Things (IoT) offerings.
Capgemini, for example, is including in-store customer tracking in its retail practice.
(PRO Tip) In addition to technology, the solution providers are differentiated by their geographical locations, professional services, and business models.
2019 Trends of Retail In-Store Analytics
With over 87% of retail sales by 2020, the physical store is still the best bet for retailers and brands to connect directly with their customers.
The people tracking systems provide the tools to manage stores.
You should improve the customer’s experience…
And increase conversions and profits.
Amazon and Alibaba have led the way to a seamless online and offline retailing. Moreover, customer expectations are accelerating. In 2019, retailers are starting to seriously explore how to empower the store with In-Store Technologies.
As a result, new data-based specializations are emerging. And a class of data-savvy executives is rising to the top jobs in brands and retailers.
2019 is a pivotal year for brick-and-mortar stores because the technologies are becoming more cost-effective, and more real-time accurate.
At the same time, our ability to generate actionable insights from tracking customer behaviors is increasing.
If you are working in a retailer, brand, or shopping center company, and you are still wondering if you should have people tracking technologies…