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data technology

Your future in-store loyalty program will be fed by facial recognition

Lolli & Pops is using facial recognition
Lolli & Pops is using facial recognition

Imagine this: You walk into your favorite store and the sales associate welcomes you by name. She or he lets you go about your business, but on-demand shares with you which of their latest products you would most likely be interested in.

Such recommendations, powered by artificial intelligence, are a very familiar experience online these days, but they’re also increasingly being worked towards in the brick and mortar retail world.

A multitude of different technologies lie at the heart of achieving this, but namely it’s a connection between CRM and machine learning, all with that layer of identification placed on top to deliver results for the specific customer in question.

Your mobile device usually plays a key role in making the ID part possible, but facial recognition is another such way.

Lolli & Pops, a candy store based in the US with roughly 50 doors, is one such retailer experimenting with this. A proof of concept called Mobica, which is powered by Intel, was on show at NRF’s Big Show in New York this week. Using computer vision, it’s a facial recognition loyalty scheme designed to drive VIP consumer engagement.

The opt-in experience (shoppers literally have to enrol their face to be a part of it), means anyone entering the store is recognized in real-time by an app the sales associates are using on their tablet devices. From there, they are able to tell the individual’s taste profile, know for instance if they’re allergic to peanuts, and be able to personally recommend great products to them via AI-enhanced analytics accordingly.

“It’s designed for their loyalty shopper, so about wanting to make them feel really special,” Stacey Shulman, Intel’s chief innovation officer for its Retail Solutions Division, told me. “Privacy isn’t an issue because they have such a strong relationship with their customers and are trusted by them already. It all starts with service and a connection to the customer.”

You can easily imagine the same VIP concept being applied at the likes of Sephora for beauty, or even in an apparel merchant.

Other facial recognition technology on show at NRF enabled special, personalized deals to surface on screens in real-time, demonstrated a restaurant that allows customers to pay by face, and also touted broader data collection opportunities around demographics and store-traffic patterns.

It was the customer service piece that felt particularly pertinent however. As Shulman explained: “Technology today needs to not be at the forefront. It needs to be the helper at the back. When done right, it enables people to get back to the customer and back to what’s important. That’s what we see here; it’s not about the facial recognition or the AI, it’s about the experience the customer then has. The differentiator between a brick and mortar store and Amazon today is customer service. We can’t compete on price and selection anymore, so we have to go back to service. If we don’t we will have a problem.”

The Lolli & Pops facial recognition initiative will roll out to stores in the coming weeks, according to Shulman.

 

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business Comment e-commerce technology

Comment counts: How AI is key to the future of retail

Advances in artificial intelligence are destined to make our lives and shopping experiences stronger than ever – good news for the consumer, and even better news for retailers, writes Uwe Hennig of Detego.

The AI-powered Macy’s On Call mobile tool from IBM Watson and Satisfi
The AI-powered Macy’s On Call mobile tool from IBM Watson and Satisfi

There have been a number of buzzwords and defining technology trends in retail over the last decade, from big data, to omnichannel, and the ubiquitous, omnipresent cloud. Now the internet of things (IoT) and artificial intelligence (AI) have become the latest talk of the town.

Forrester expects investment in AI to triple this year. By 2020, 85% of customer interactions will be managed by AI, according to research by Gartner. It’s becoming big business across industries, and not just in retail: the value of AI is estimated to be worth $36.8bn globally by 2025, predicts US market intelligence firm Tractica.

With the proliferation and accumulation of so much data as people shop anytime, anywhere – whether online, in physical stores or increasingly via their mobile phones – the conundrum for many remains: there’s just too much information to be able to make any meaningful sense out of it.

And that’s where artificial intelligence comes in. AI relies on a continual process of technological learning from experience and getting better and better at answering complex questions. Algorithms powered by AI can rapidly come up with alternative options which are otherwise much more time-consuming and laborious using conventional computer-powered A/B testing. Like the human brain, AI adapts to the environment and gets better the more you use it. But unlike humans, the capacity for improvement is unlimited. What’s more, boring, repetitive tasks are never a problem.

Plenty of examples in retail already fall under the hat of AI: chatbots are being used to help with customer service; personal shopping assistants like Amazon’s Alexa respond to voice prompts; and robots are replacing information kiosks in stores like Lowe’s in the US. Live chat functions on retailers’ websites are also proving popular for replacing staff with always-on robots and providing a continuous machine-learning customer service experience. But the future of this space looks even more AI-enabled.


Personalised service and the human side of AI

Retailers have long since struggled with maintaining ever-increasing standards of customer service as consumer expectations continue to rise. As people continue to shop more via the internet, retailers have to provide a faster, more effective, personalised service specifically aimed at the needs and wants of individual customers.

AI is set to help. eBay’s ShopBot for instance, is an AI-powered personal shopping assistant on Facebook Messenger that helps users find the best deals and sift through over a billion listings.

Chatbots have question and answer recommendation capabilities that are much more personalised than previous systems. They’re examples of retailers trying to create a near human interaction. Yet an IBM study in retail deduced that traditional retailing is too constrained to cope with recent technological advances and that the technology to date is just not human enough.


Humans vs machines

In spite of that, a new report by PwC says that around 44% of jobs in the retail sector are at risk of automation by 2030. AI is extremely good at repeated tasks and number crunching, so machines will do lots of manual processes in the future. We’re already seeing some retailers wanting to close off stock rooms and using robots to make automatic decisions about what needs replacing on the shelves, or managing the flow of goods for deliveries and onto the shop floor, for instance.

In the not too distant future, it will be common practice for consumers to pull out their phones and ask it a question as they enter a store, rather than seeking out a sales assistant or searching through the rails themselves. The smartphone can immediately respond that a desired article is available in a specific size and that sales staff can bring it.

Voice recognition systems and speaking to a computer or smartphone (like Apple’s Siri) for answers is already taking shape. Macy’s used a version from IBM Watson to do exactly this (as pictured above), and talking interactive screens and self-checkouts in fitting rooms is something we’re also already engaged with.


Real-time recommendations

AI, or machine learning, learns from past behaviour, as well as trial and error, to come up with more intelligent solutions. It’s not just science, there’s an art to selling too. Old fashioned rules-based analytics will soon become a thing of the past.

At Detego, this means making more informed recommendations to retailers using predictive analytics. So, much like the practice of online retailers flagging up similar items you might like as you browse the web, some retailers are now taking this to the next level using AI – and not just online, but in their physical stores as well (where still over 80% of sales are driven).

For example, whereas a sales assistant might, if you’re lucky, recommend something that’s evidently there on the shelves, an AI system would be better at identifying what would be the best items to offer based on many more criteria. These would include fundamental credentials like real-time product availability and the resulting profitability for the retailer, as well as other considerations like the consumer’s browsing history, or even what they’ve tried on before in the fitting room (thanks to “smart” RFID tags embedded into garments).

Informed recommendations can also be made by tapping into social media and other factors that might influence product choices, like current fashion trends or weather forecasts in different regions.


Predictive AI

Effective AI systems are also looking for re-occurring patterns to help avoid out-of-stocks and unnecessary markdowns, such as by promoting underselling lines held in reserve that otherwise would later have to be discounted. Not only will such advanced technology know when shelves are empty, but more importantly, it will predict what will happen next.

One of the biggest growth areas where AI can make a significant difference to a retailer’s bottom line – for mobile, online and bricks-and-mortar retailing – is in this field of intelligent forecasting systems. Previously, retailers were only able to predict roughly the quantities of products to order to keep shelves fully stocked using (often out-of-date) inventory levels and historical sales data (usually going back a few years, at best). These days, AI can develop a much more accurate picture of exactly what types of products, sizes and colours are likely to sell, by looking at multiple scenarios in real time (fashion trends, consumer behaviour, the weather etc) and drawing on data from the internet. This means forecasting is no longer so much “stab in the dark” guess work.

Using AI, German online retailer, Otto, predicts with 90% accuracy what will be sold within the next 30 days and has reduced the amount of surplus stock it holds by a fifth. It has also reduced the number of returns by over two million products a year. It claims to be so reliable, in fact, that it now uses an automated AI system to purchase 200,000 items a month from third party suppliers with no human intervention. Humans simply wouldn’t be able to keep up with the volume of colour and style choices to be made.

While some fashion retailers are working with Detego to exploit many of the latest technologies to help encourage more people into their stores and improve levels of customer service, forecasting in fashion is generally quite poor. Despite more than 1,500 stores already equipped with Detego’s software and over a billion garments digitally connected, the wider industry average for forecasting accuracy in fashion still lags at a paltry 60-70%. Although RFID tagging and real-time stock monitoring offers near 100% inventory accuracy, relatively few fashion retailers have rolled-out digitally connected technology on a wider scale.

It’s still only the early stages of AI, but with the promise of it making forecasting and product selections even more accurate, it’s set to become a rapid reality. Now’s the time to jump on board.

Uwe Hennig is chief executive of retail tech specialist, Detego. Comment Counts is a series of opinion pieces from experts within the industry. Do you have something to say? Get in touch via info@fashionandmash.com.

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e-commerce mobile social media

Yoox x WeChat collaboration blends commerce and gamification

yoox_wechat2

Yoox teamed mobile commerce with gaming in a new app launched via messaging service WeChat earlier this summer.

The internet retail company rolled out official WeChat accounts in the US and Italy, and updated its China one, back in July, offering users the ability to shop via an interactive look book, and to instant message customer service teams and personal stylists. Content also invites users to exclusive events and provides early access to specific products.

Accompanying that came a gamification layer with its Shake Your Style app.

This enables users to literally shake their smartphones to see different product options in order to help revamp a friend’s style. Speaking at the Details magazine Tech & Tastemakers Summit in New York earlier this month, Clement Kwan, president of YOOX Corp, the group’s US branch, said: “You shake it and like a slot machine three different looks come up… You can slowly nudge your friends to change their style.”

The resulting looks can accordingly then be shared with contacts across other social platforms, in what’s no doubt intended to drive further customers into WeChat and onward to purchase.

Kwan added: “WeChat has 400m people on it globally, 100m of them outside of China. It’s a great platform for blending social, mobile and commerce together.” Yoox reportedly sees 42% of its global traffic coming from mobile devices already.