There are eyes on you, behind the bright lights and mirrored panels. Pick up a boot and a camera will make sure you don’t slip it into your bag. Cross the threshold into a department store and there is a tacit understanding that you will be watched, but new technology is leading retailers to grow a different set of peepers – eyes less focused on shoplifting and more interested in your age, sex, size, head, shoulders, knees and toes. Knees and toes.

A few months ago, IT firm Computer Sciences Corporation (CSC) put out a report that claimed around 30% of retailers use facial recognition technology to track customers in-store. What is facial recognition? It is technology that can identify people by analysing and comparing facial features from a database. You may be familiar with it from Facebook’s photo tagging, but similar techniques are now making their way into the physical world with devices such as Intel’s RealSense cameras, which are able to analyse everything from particular expressions to the clothing brands someone is wearing.

When I spoke to Joe Jensen, general manager for Intel’s Retail Solutions Division, in September 2015, he told me that the aim of bringing RealSense technology into shops is not to create Minority Report-style databases of specific people’s lives, but rather to build generalised models of people’s lifestyles and shopping habits.

“It’s not so much that you need to know, say, ‘Elaine’,” he told me at the time. “It’s that you need to know that this shopper has these characteristics and, in the past, that when those characteristics happen, this is what a person tends to do.”

Combine recognition technology with databases of previous customer patterns and you can start to predict a lot about what a person may or may not do in a shop. If, say, there’s a size-10 woman wearing a gold necklace walking quickly towards the sock aisle, you can collate that data against a sizeable reservoir of previous patterns and predict she wants to, well, buy socks.

That might not need an expensive camera, but for a retailer it could allow them to automatically throw up targeted ads on screens aimed specifically at that person, based on that person’s expressions and movements. If she looks like the type of person who wants to buy socks, they will show her adverts for socks.

Shoppers are more suspicious of cameras in real world stores than they are cookies when shopping online. Photograph: Andrew Winning/Reuters

If it sounds familiar, it’s because the online world has been using techniques like these for years. Search for something on Amazon and you’ll be hounded by targeted banners for similar products on other sites. Express a vague interest in canoeing and you’ll be plagued with canoes wherever you go. Yet dragging these systems into the physical world isn’t a simple case of copy and paste. It turns out that people do not react to cameras in the same way as they do to browser cookies.

Predicting gender based on shoes

If the prospect of having intelligent cameras pointed at your face makes you want to grab a crowbar and start smashing all the mirrors in the department store, there’s an alternative for you: intelligent cameras pointed at your feet.

Hoxton Analytics is a London-based team of data scientists that have developed a technology that makes use of machine learning and artificial intelligence to categorise people based on the shoes they are wearing. By analysing the style and size of people’s footwear as they walk past the sensor, the system can make real-time judgments on demographic and footfall. The company claims it can identify a customer’s gender with between 75-80% accuracy.

Owen McCormack, Hoxton Analytics CEO, tells me that the focus of the system came about in part as a reaction to facial recognition.

For me it's fine - it gives retailers accurate information but without saying who this person is or where they live Owen McCormack of Hoxton Analytics

“My idea was, why don’t we simply consider the clothes someone’s wearing to understand demographics,” he said. “If I just showed you a shot of someone’s body you could probably tell me what gender they are without having to take personal information. However, it turns out pointing a camera at someone’s chest or hips is just as privacy invasive and feels just as creepy as facial recognition. The idea was – what about people’s shoes?”

The word “creepy” comes up a lot during discussions of in-store tracking. For retailers and data scientists, the aim is to find a way of obtaining information without coming across as unnerving or intrusive.

For Hoxton Analytics and the retailers using the technology, including the O2 centre on Finchley Road and men’s lifestyle shop The Dandy Lab, both in London, the answer is to look downwards. This tactic of averting the eyes – avoiding the face and staring at shoes – says a lot about how we, as physical beings, react to being watched. It suggests there are boundaries that do not exist when flipping between websites. Set sights on our torsos and we feel invaded in a way we don’t with click-throughs. But while making calculated judgments about a person based on their footwear instead of their face may toe certain psychological lines, is it actually any less invasive?

‘If you knew everyone in Argos right now was male, you’d be advertising PlayStation, not hairdryers,” said Owen McCormack of Hoxton Analytics. Photograph: Graham Turner/The Guardian

For McCormack, the argument hinges on the fact that personally identifiable information isn’t being harvested. “Right now, shops are doing lots of incredibly invasive things, but we just don’t know about it. The angle Hoxton Analytics is taking on that whole thing is, well, if you know someone’s a male or a female then your advertising will be much more efficient. If you know that everyone in Argos right now is a male, you’d be advertising PlayStations not hairdryers. For me that’s fine – you’re giving the retailers accurate information but you’re not saying this person is so and so who lives down the road and has an expensive house.”

Julija Bainiaksina, co-founder of The Dandy Lab, similarly emphasises the anonymity of the process, telling me that the shop doesn’t “obtain or keep any private information unless customers express an interest in receiving a personal shopping service and provide personal details themselves”.

Anonymity goes a long way to mollifying a sense of invasiveness, but being able to target increasingly narrow segments of individuals based on a number of physical factors still raises questions about what can be inferred, and who ultimately has control of the data.

While The Dandy Lab is pretty upfront with its backend technologies, you can see why other retailers keep the majority of their tracking methods tightly under wraps, including the controversial MAC address tracking trialed by US retailer Nordstrom in 2014.

Keep it hidden and invisible monitoring lets shops optimise their output while keeping the customer blissfully unaware. Put adaptable monitors and targeted ads into a mix, however, and it becomes harder to hide the fact that a machine is stalking you behind the scenes. The argument from the retailers is that they do this to provide a bespoke shopping experience, but it remains a grey area. It still feels creepy.

Offline cookies

From the perspective of retailers, it’s understandable that physical shops want a slice of the information afforded to online outlets in the shape of click-throughs, conversions and demographics. We allow this to happen online, so why not offline? The thresholds of a shopping centre are different from those between websites, and when you can wander freely from one place to another without a pop-up asking you to accept cookies, the rules of consent change.

Then again, for a generation growing up with Amazon first, physical shop second, the modes of online play may not be quite so invasive. In the CSC report, a survey indicated that while 72% of 55+ respondents said they were decidedly uncomfortable with these types of technologies being used in physical shops, only 51% of 16-24 year olds said the same.

Does this relative openness stem from a greater familiarity with digital technology, or a blind belief in the goodwill of omnipresent organisations offering free services?

Is the creepiness of a technology an unvarying, instinctive certainty, or does it ebb and flow with degrees of social acceptance? Whatever the case, between the shelves there are a growing number of eyes, and they care a lot about what you’re wearing.