Data, data everywhere at NRF 2017
There was no escaping data at Retail’s Big Show (organised by the National Retail Federation) held in New York recently.
It is fuelling the key trends seen at this year’s event – from Artificial Intelligence (AI) and machine learning to driving changes in customer interfaces via voice and visual search technologies.
Speaking at NRF, Brian Krzanich, CEO of Intel, told delegates: “All parts of businesses are undergoing transformation and what’s driving this is a flood of data, which is at the heart of the customer relationship. It has become one of the most important forces in industry. Just like oil, it is transforming things and providing insights and opportunities to retailers and to customers.”
Data driving the interactions
As well as providing many of the chips for today’s retail technology solutions Intel is also bringing together various IT vendors onto its Responsive Retail platform that enables a seamless flow of data between the various solutions that can drive increasingly rich insights and interactions.
One example is JDA working with Theatro to improve replenishment. Theatro has developed a Siri-like app that is being used by retailers including The Container Store to improve customer service and product availability. Retail employees use a voice-controlled wearable that can highlight to them audibly when products are running low and need re-stocking as prompted by the JDA forecasting software.
Voice to the fore
Increasingly rich data is very much at the heart of such voice interfaces and one of the leading proponents of this is IBM with its Watson solution that uses machine learning to analyse massive amounts of structured and unstructured data in order to make intelligent decisions, which can then be delivered to customers.
These take the form of mobile apps, Chatbots and other conversational interfaces such as that being used by Staples. Its ‘Easy Button’ service is being tested by some of its trade customers. Fasul Masud, CTO of Staples, says the system can be used to take orders, as well as receive questions asked in natural language on various areas such order tracking, and product recommendations. “We can teach Watson how to take unstructured speech and work out the ‘intent’ of customers and how to then service them,” he says.
Machines are learning fast
The clever aspect of these machine learning technologies is that they build on their knowledge over time. The capabilities increase as they gain experience of dealing with customers’ interactions.
Mode.ai works with a number of fashion retailers providing Chatbot solutions, which utilise this same machine learning capability to gradually gain knowledge about individuals and their interactions with specific brands.
Karen Ouk, SVP of business development at Mode.ai, says: “There is learning from the link between the person and the brand. We will get to know their sizes and colour preferences. There’s an improved [level of] personalisation through Chatbots.”
Personalisation at scale
Growing numbers of retailers are recognising the ability to use this technological capability to deliver personalisation to a level that was not previously possible. Speaking at NRF Ratnakar Lavu, CTO of Kohl’s, says it is enabling relevant content to be given to each customer as they land on the home page of the Kohl’s website.
“To make the home page unique for millions of customers is impossible when it was previously people doing this task. You need machines. Now with big data and machine learning we can turn personalisation on,” he says.
It is a similar story at US-based Lululemon Athletica that has found machine learning makes it possible for it to deliver personalisation over its fast-growing business. It was previously done by the store managers but this has become unmanageable as the store estate has expanded. An element of digitisation and automation had to be brought in.
Miguel Almeida, EVP of digital at Lululemon Athletica, says: “To continue to grow without losing the connection, the human relationship, we knew we needed to build a digital platform that would amplify the human experience. We wanted to build a digital DNA and mindset that could scale very rapidly. We wanted to evolve from a culture of ‘tribal knowledge’ to one of ‘scientific knowledge’.”
Robots improve inventory accuracy
Data is also increasingly being crunched to boost operational back-end efficiencies and this was evident in the robotic solutions at NRF that work on the shop floor to improve product availability and pricing accuracy. Simbe Robotics has developed the Tally robot that is being piloted by a number of US-based retailers.
It uses both Intel’s Real Sense sensor technology as well as high quality cameras that enable it to take move up and down the aisles taking detailed images of the products and comparing this data with the expected situation based on ‘planograms’ and the visual characteristics of each product that it has stored.
Brad Bogolea, CEO of Simbe Robotics, says these technologies are massively quicker than humans at undertaking such tasks: “They can recognise 15-20,000 products per hour. A small grocery store can be done with a single Tally robot in one hour. It is much cheaper and faster than humans and there is near perfect accuracy.”
Developing variations of reality
The use of visuals is becoming increasingly commonplace as the technological capability and processing power becomes available to retailers. This is helping fuel the growth in Augmented Reality (AR) and Virtual Reality (VR). These were key trends at NRF this year.
One such company with an AR solution is Augment, which is working with online store Cdiscount and DIY retailer Leroy Merlin to display rich visual versions of their products online. The customer can then manipulate them around the screen as well as placing the items within their own home environments.
Visualisation really comes in to its own with VR. Although the technology has been around for some time it continues to evolve and is just beginning to look interesting to retailers – from a back-end rather than customer perspective at this point.
One of the young technology firms in the field is inVRsion that has developed a solution to help merchants virtually visualise their in-store environment and use this as a merchandising tool to determine the optimum positioning of goods on the shelves. By linking it to a retailers’ back-end inventory and merchandising systems the solution can overlay key sales data and relevant KPIs on top of the 3D visuals.
VR-commerce potentially the next frontier
Many technology firms like Facebook and Google are developing VR solutions but there has not yet been mainstream acceptance. However, when there is then Matteo Esposito, CEO of inVRsion, believes this will drive the adoption of VR-commerce whereby shoppers can enter virtual stores in the comfort of their own home and make purchases.
This has already been used by Alibaba through its Buy+ platform onto which it created virtual shops of retailers like Target and Macy’s. Customers could navigate around the outlets and buy products through Alibaba’s online marketplace T-mall.
Such developments certainly represent an interesting future for retailers but they also bring equally massive challenges because established merchants need to balance the new ventures with their existing infrastructures and cultures. Jamie Ovenden, director of digital and retail IT at Arcadia, says: “We’ve reached peak complexity at a time when our customers are their most demanding.”
The digital transformations that retailers like Arcadia are currently undertaking involve a complex mix of technology and cultural change – both from a customer and employee perspective – and how they handle this tough situation will undoubtedly determine the winners from the losers.
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