The use of artificial intelligence in bricks and mortar stores.
1. Artificial intelligence (AI and consumers)
AI-powered systems are now becoming a primary asset of consumer-facing businesses.
From chatbots for online interactions, to analysis of spending patterns, businesses are using AI to assist in processes from fraud detection to profiling.
These techniques are now being complemented with individuals’ unique physical characteristics to enhance their retail experience.
For example, the use of personal voice recognition as part of bank security protocols, or the tagging of customers’ characteristics as part of creating an alternative reality.
2. AI in bricks and mortar stores
This innovation has extended to the bricks and mortar retail experience, with in-store biometrics being used to power payment and security techniques.
Outside the payment and security domains; can retailers exploit algorithm-driven biometrics in the real world, to compete with the online retail ad space, and to enhance the customer experience?
Already under consideration are techniques that identify and track shoppers in store in order to obtain insight into their preferences. For example, Amazon Go’s “just walk out” stores do not require the user to actively make an instore payment at a cashier. Instead, the customer’s shopping is tracked as they move through the store and select items, with the final bill being charged against their Amazon account.
Microsoft’s Dynamics 365 Connected Store program, also shows the potential of these systems. At present, in-store cameras assess how people browse, to drive decisions on where to put particular stock, and what lines are likely to run out and when.
Nestle and its partners’ (including Visa and Samsung) have created a Payment Innovation Hub which aims to improve the customer experience, whilst increasing security, with the use of cutting edge technology.
This includes an ATM facial recognition application that has been implemented by Caixa Bank (one of Nestle’s partners) which allows withdrawals at an ATM without entering a pin. This proved so popular due to increased customer experience and security it received international recognition and awards.
Nestle has also deployed a facial recognition payment system in a grocery store in Spain, which interplays with a app that a customer downloads in advance including a selfie of themselves. This selfie is then matched with the customer’s face instore, providing a secure and seamless payment method. Nestle perceives this as enhancing customer experience by streamlining checkout payments in periods of high demand, such as Christmas.
Additional potential of AI in bricks and mortar stores includes using systems for gaze and sentiment tracking, either through existing in-store cameras or through the use of customer smart phones. For example, tracking customer reactions to in store-advertisements through facial recognition which tracks micro-expressions (facial expressions that last for a short moment). AI-powered systems are likely to be able to complete this more accurately than an experienced store assistant.
The creation of a smart changing room, whereby a customer’s reactions, as well as tag
information, can be analysed in real time to suggest more appropriate sizing, or particular colours that suit the customer, using information sensed through mirrors could pose another opportunity.
3. The drawbacks of AI in bricks and mortar stores
Despite significant potential benefits for retailers and customers, these capabilities are being held back by several factors, including consumer pushback and privacy concerns related to biometric systems. For example in the context of the smart changing room, how comfortable would customers feel facing a mirror which was monitoring them: even if no human being was primarily involved?
We know that in-store security cameras which use facial recognition systems are often subject to legal challenge around the world and have even prompted countries to implement privacy legislation to prevent misuse. For example, in the USA, Illinois now has strict biometric processing laws. In other parts of the USA stores that use facial recognition have been the subject of class action.
4. The balance of AI with real data
Consequently, developers are creating systems which bypass personal data by claiming it is not possible to identify individuals. However, this does not go far enough to conclude that no personal data is being collected and processed if an individual simply cannot be named.
These systems also carry the risk of reputational pushback from privacy campaigners.
From the retail sector’s perspective, not being able to identify customers after their in-store experience results in little or no promotional follow-up nor longer-term behaviour analysis or customisation.
5. The regulation of AI
Despite AI technology continuing to develop at a rapid pace. the regulation of AI also continues to develop.
Several drafts of Europe’s future AI Act considers that where systems are “at a distance”, and happen without the “active involvement” of participants, it will still be perceived to be a “high risk” system. Consequently such systems will still necessitate public authority notification and public consent in order to be compliant.
Lessons can also be learnt from the lack of information provided to customers relating to existing biometric tracking experiments. Several of these have fallen foul of the law in the US, on the grounds that clear prior information was not given to customers entering stores.
As with the presentation of cookie banners, a delicate balance will exist between providing sufficient and excess information. Both approaches risk alienating customers at an opportune moment of engagement.
In order to overcome the increased regulation of AI, whilst deploying innovative and insightful technologies, retailers will instead have to focus on their brand winning the hearts and minds of consumers for successful deployment.
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This article was also published in The Retailer, our quarterly online magazine providing thought-leading insights from BRC experts and Associate Members.