This January, leading IT providers and senior executives from retailers around the world descended on New York City for Retail’s Big Show, organised by the National Retail Federation (NRF) to help them plot their future strategies.

It certainly isn’t simple though as articulated by Sir Richard Branson, founder of Virgin Group, who gave one of the keynote presentations this year. He sympathised with retailers for operating within a particularly tough market and recalled how he “saw the writing on the wall” for his Virgin Megastore record shops before cleverly pivoting the business to focus on its two best-selling products: mobile phones and video games.

“They became bigger than the record stores ever were. It’s not easy but people who own retail stores should not think of themselves as just retailers. They should spin off businesses in order to survive,” he suggests.

Data is the secret weapon

As well as adopting such an agile mindset, retailers also have a secret weapon in their armoury that is becoming increasingly powerful – data. Although they have been accumulating increasing amounts of it in recent years they have not been benefiting particularly well from any insights it can provide.

Edmond Mesrobian, CTO at Tesco, recognises this and is re-assessing how his business uses data: “The next set of [technology] innovations will require an understanding of what happens across the whole business. Pure-plays have understood this but physical retailers have not done so yet. They need to take data, gain insights, and make decisions across the whole business.”

At NRF this year there were myriad solutions to help merchants leverage their data. It was certainly at the heart of the key buzzwords of the 2017 event – artificial intelligence (AI), machine learning, augmented reality (AR) and voice recognition.

Seamlessly sharing information

Intel was being pro-active towards data-driven solutions and has developed the Responsive Retail Platform on which can sit various solutions from different technology providers. It enables them to seamlessly share information that ultimately helps retailers deliver better service to their customers.

It was showcasing solutions from the likes of Theatro, which has developed voice-controlled wearables that are worn by retail employees and which can be linked into inventory management solutions from firms like JDA to issue messages to employees about stock levels. This could indicate that a shelf needs re-stocking before it becomes an out-of-stock situation.

Theatro also enables employees to verbally access experts and specialists, across any part of a retailer’s organisation, thereby helping them address specific customer queries in real time in-store. Intel was also highlighting the True Fit solution that helps customers find clothes suited to them through the mass of data it holds on branded fashion goods and customers’ preferences as well as their previous purchases, which are mapped onto what it calls its Genome. The insight can be delivered through ‘clientelling’.

Shailesh Chaudhry, global director of strategy for retail at Intel says: “Personal shoppers are great but they’re not for everybody. True Fit helps associates to make recommendations in-store, based on the data that’s held. It might also be linked to loyalty programmes.”

Improving the customer journey

Using data to help customers on their shopping journeys – as well as answering their queries – was exactly the objective of many of the AI and machine learning solutions showcased at NRF. They use technology to intelligently automate the interactions shoppers have with retailers.

It does not rely on rigid rules-based programming techniques but constantly learns from the data being processed in order that decision making becomes more intelligent over time. One of the leading solutions is IBM’s Watson, that is being used by various retailers including Staples.

Fasul Masud, CTO of Staples, says the company has recently launched a test version of the ‘Easy Button’ service across its business, including on its website and app, which interacts with customers via voice to automate order taking and answer shoppers’ queries. “We can teach Watson how to take unstructured speech and work out the ‘intent’ of customers and how to then service them,” he says.

At this early stage of implementation he says the solution is simply taking “low class” tasks away from its employees, but he can foresee when it will do a lot more for the Staples business – both internally and for customers – including possibly answering the phones in the call centre.

Next generation interfaces

Another solution that uses AI technology is Mode.ai that works with various fashion and accessory brands to deliver a chatbot, which relies heavily on visuals. Karen Ouk, SVP of business development at Mode.ai, says: “We are integrating visual search into our chatbot with AI. We’re giving suggestions to customers that help the retailers sell them more goods. There is learning from the link between the customer and the brand. They will get to know their sizes and colour preferences. There’s an improved [level of] personalisation possible through chatbots.”

What this solution also highlights is the changing nature of the interface between customers and retailers. The growing use of visuals and voice is pushing text aside. This is also manifesting itself in some of the robotic solutions being developed, of which some examples were present at NRF.

Automating through robots

Autonomous Robots has developed a prototype of its Clone robot that moves around the physical store – relying on a camera as a sensor – and interacts with customers through voice. It can direct them to products they are looking for and provide extra information on items as requested.

The use of visual technology is also at the heart of solutions from Focal Systems and Simbe Robotics that undertake stock checks and identify misplaced products on the shelves in stores. The former uses devices with cameras enclosed that are attached to customers trolleys and collates their imagery into a single view of the store, while Simbe has developed the Tally robot that moves from aisle to aisle undertaking an automated check of each shelf through its cameras.

Brad Bogolea, CEO of Simbe Robotics, says the use of Intel’s Real Sense sensor technology as well as high quality cameras enables the solution to overcome the challenge of automated stock-checking using RFID technology. This is especially relevant in grocery retail where many products are of insufficient value to have been tagged.

It takes detailed images of the products and compares this data with that found on the retailers’ ‘planograms’ and the visual library it holds on each product stocked within the store. Bogolea says the speed and accuracy of the solution makes it attractive to major grocery chains and some general merchandise retailers, and it is being trialled with a number of retailers including Target in the US.

“We’ve also received immense interest from Tesco, Auchan and Carrefour but North America has been the main focus to date. But this year we will be going into Europe,” he reveals.

Rise of ‘emotional intelligence’

Tesco has also been linked with another technology solution involving sensors that has been developed by Cloverleaf and is expected to be piloted by retailers in the first half of this year. Gordon Davidson, CEO of Cloverleaf, says it involves digital shelf-edge signage whose content can be changed according to not only the products on the shelves but also the demographics of the person passing the shelf.

It also has what he calls ‘emotional intelligence’ capabilities, whereby it can identify the expressions on customers’ faces as they look at the content and serve up different images accordingly. “If people frown at a particular piece of content then we can design the database to be predictive to this,” says Davidson.

Being able to predict the future is a bit of a tall order, but the retailers among the 35,000 attendees at NRF will undoubtedly have been given a little helping hand by the 500-plus IT providers showcasing their products this year.

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