How AI will change the retail experience

The rise of the Artificial Intelligence (AI) is happening right now at a retailer near you

Consumer habits have changed dramatically in the last decade. Bricks-and-mortar and online retailers have undergone profound transformations and will continue to evolve thanks to innovations pulled straight out of sci-fi novels. Machine learning, neural nets and AI are becoming buzzwords in the industry as they help simplify the shopping experience whilst increasing efficiency and reducing costs for retailers.

A window into consumers’ minds

Today’s consumers may not understand how Amazon seems to know exactly what they need and want or how Airbnb knows they’re planning a trip to New Zealand and has found just the right place for them to stay, but they interact with and benefit from the applications of AI every single day.

Research in AI has been on-going for over 60 years but it’s finally trickling down with practical applications in data analysis and prediction models, computer vision, and pattern recognition, which can now be used to increase efficiency, reduce costs, and offer customers more personalised experiences.

These innovations come at a crucial time as consumers, accustomed to technological change in other areas of their lives, want more from retailers, according to a survey by Accenture. They want to receive real-time promotions (38%), the ability to automatically credit coupons and discounts (27%) and want retailers to provide them with shopping list, item locator and navigator options (30%).

Integrating deep learning applications will be a challenge for retailers for many years to come. “Newer and better technological advancements will continue to crop up at faster rates than ever before, and in the process will intrinsically change the way we shop at a mind-boggling pace,” according to Ovum.

What trends in retail do we expect to see in the futureSource: Ovum

Welcome to the future of retail

Convenience and technology go hand in hand

Webloyalty’s The Unfaithful Consumer report found that almost 70% of UK consumers have less time for everyday shopping than before and a majority (55%) cite convenience as their biggest priority.

They particularly hate shopping for groceries, says the report, with more than 55% ready defect from their current retailer. New technologies, which boost convenience, could help retailers recapture their customers’ hearts.


Take Watson for example, an artificial intelligence robot created by IBM. Shoppers could soon walk into a store with their grocery list on a mobile app, which would be captured along with their location by sensors, thanks to Watson’s cognitive technology. Within seconds, they could receive “a map of the store and the order in which” items can be picked up “in as short a time as possible, knowing where the queues are, which aisles are congested and if any products are close to selling out.”

Retailers could save 15% in running costs making “the technology very attractive,” says Tim Dunlop at The Guardian. Considering Amazon’s track record for trialling and then licensing its applications, there’s a good chance retailers in the food and groceries industry as well as other sectors, will jump at the chance to develop such stores.

Amazon Go

Amazon is set to go even further. When it launches Amazon Go in Seattle in early 2017, the retail giant will be testing a completely different type of grocery store (coming to the UK soon) . Consumers will scan the app on their phone upon entering; pick whatever they want and simply walk out; no checkouts or line-ups. Their purchases will be charged to their Amazon account and they’ll receive a receipt. This will be made possible by Amazon’s “just walk out technology,” powered by deep learning and a series of sensors and cameras equipped with object recognition software disseminated throughout the store.

The development and implementation of applications derived from AI happen in part because corporations like Amazon and Google want to create a tech-centric society from which they’ll be able to derive profits, but it’s also the result of Gen X and Millennial consumers pushing for such innovations to streamline their lives.

Considering Millennials, born between 1980 and 2000, will represent the largest group of consumers by 2020, retailers cannot ignore AI-based technologies if they want to keep up with the demands of future customers.

Fashion retail focusing on personalised experience

Fashion retailers will also benefit from AI applications but will focus less on convenience and more on personalisation. This makes sense since consumers actually “enjoy shopping for fun and creative products like homewares, beauty and clothing,” says The Unfaithful Consumer report. So it’s not a case of “getting it over with” as in grocery shopping but more about enjoying the experience and finding retailers who truly seem to understand their needs.

Imagine your favourite retailer uses a mix of deep learning, computer vision, sensors, and pattern recognition software in addition to having a shopping and payment app. You receive a message through the app informing you the bag you placed on your wish list is discounted. Proximity sensors pick up your presence as you enter the shopping centre and you receive a reminder about the bag.

As you near the store, the sales clerk receives an alert that you’re nearby. She brings the bag to the counter and checks your wish list. You’re pleasantly surprised with the personal touch as the item you want is already waiting for you and the clerk reminds you of items on your list.

You spot a dress you like. You decide to “try on” the dress using the store’s virtual mirror, which also suggests suitable accessories, and share the image with your friends to get their feedback. You decide to buy the bag, dress and one other item on your list. Your purchase is processed through a contactless POS terminal and your discounts are applied automatically.

These innovations may seem like they belong in a futuristic tale but in fact, they are already being trialled by many retailers around the world.

Is deep learning killing privacy?

One of the most practical uses of deep learning applications is the collection of data, which is analysed to better understand consumer preferences to tailor cost-effective customer experiences. Netflix, for example, uses deep learning to draw a portrait of its subscribers’ viewing habits, allowing it to make very accurate suggestions.

Claude Nahon, president of Food Media in Europe, argues this may lead to stores eventually foregoing public pricing completely. “Instead, vast instore data mines will know all they can about an individual – where they shop, what they buy, their income and brand loyalty, and then use that profile and purchase history to give the customer a better deal.”

Data comes in many forms including demographic information such as gender and age, purchasing habits, and even visual data. Connected cameras are everywhere nowadays and many are equipped with recognition software. Does that mean the end of privacy? Yes and no.

There’s very little to be done about the collection of data in the public space. A retailer or shopping centre operator can deploy wireless cameras throughout the store or centre and follow you, registering what you look at, and then connecting to the “tills for purchase data,” explains Benedict Evans who works for a venture capitalist firm in Silicon Valley.

While privacy concerns are real, most consumers are willing to share their personal data with retailers in exchange for rewards, discounts or loyalty points, according to a global Microsoft survey.

A delicate balancing act

Innovations stemming from AI research have the potential to transform the lives of consumers positively as well as reduce the cost of doing business for retailers. That said the integration of deep learning applications is bound to have significant consequences on the economy.

Currently, there are 5 million people employed in retail in the US and 2.8 million in Britain. It’s not difficult to foresee that the implementation of “shop and walk out technology” into retail stores will inevitably lead to job losses, but the ramifications could be much more profound.

The rise of tech giants like Amazon, “Uber, Airbnb, Netflix, and even Google and Facebook, are part of a fundamental restructuring of the economy,” says Dunlop who sees this as “a recipe for massive inequality and insecurity” because these companies “need so few workers,” they “tend to funnel the wealth they generate to owners and investors rather than distribute it broadly via wages.”

At a time when many politicians around the globe are making hollow promises of “bringing the jobs back” and even the staunchest socialist regimes are flirting with capitalism, governments may have to intervene to find ways to redistribute wealth in a world where the “value of a good day’s work” doesn’t mean much anymore.

Is AI right for your retailer?

Ultimately, it will be up to individual retailers to decide what is appropriate for their customers. Not everyone is interested in an Amazon Go type of retail experience. Many consumers, such as tech-challenged baby-boomers, still prefer a human touch. This will require a delicate balancing act from retailers. They want to benefit from the increased efficiency and cost reduction new machine learning applications have to offer but they must also remember that unemployed and struggling individuals don’t tend to consume much.

Are AI applications changing the face of modern retail? Absolutely, and they will continue to do so at an increasingly faster pace. This frantic race toward the future is partially fed by consumer demand for a more personalised and less time-consuming shopping experience but it holds many benefits for retailers as well. As they weigh the benefits of new innovations, retailers will need to keep their customer base in mind.