In our latest exclusive conversation with Intel, GDR’s SVP Global Innovation Alex Sbardella finds out how brands can harness the power of technology.
As we learned in the previous article in this series, retailers today have an abundance of technology and data available to them; the challenge is knowing exactly how and when to apply this wealth of possibility to properly understand, and meaningfully change, the relationship they have with their customers. “We live in an era where a tremendous amount of data is being generated every day and the numbers are only growing,” says Azadeh Yazdan, Director of Business Development at Intel’s Artificial Intelligence Products Group. “Just collecting or having access to larger data sets, however, doesn’t lead to improved business results – being able to extract meaning from big data to solve problems and be productive is the key to success.” With Fitch predicting that retail default rates will rise to 10% in 2018 (an increase of nearly a quarter on 2017), meeting this challenge is vital to remaining competitive in an increasingly brutal retail marketplace. But what does this actually mean for legacy retailers? Should they be looking at a truly different service proposition enabled by the proliferation of technology, or just an evolution of what has come before?
Stacy Shulman, Intel Retail’s Chief Innovation Officer, advises retailers to think in terms of practical changes, not magic bullets. “Modern technology and Innovation should be iterative and based on a foundation of feedback and learning. Embracing technology is a must in today’s competitive landscape, but you need to start from insights on real customer pain points, not innovation gimmicks – solve the customer pain points, and you’re guaranteed ROI even if it’s not immediately apparent”. In other words, the transformative nature of these technologies means retailers need to be considering their impact at a much deeper level than in the past, and in the context of the entire customer experience, not something simply tacked on to what had gone before. Shulman gives an example from fashion: “Buying a new look is an inherently social process for many shoppers, who use photos to get input from their friends. But the mistake made in the past was to respond to that customer behaviour by putting “selfie station” kiosks into stores. If they knew their customer, they’d know they’re going to want to take those photos on their own phone and use their own tools, not a retailer’s device”. And this means solving a completely different set of pain points to fulfil the same outcome – from Under Armour offering free charging for customers whilst they shop, to Jooos Fitting Room providing selfie sticks, soft lighting and seating in their fitting rooms, to a whole host of restaurants designing their interiors for how “Instagrammable” they are (according to the owners, the average diner at Media Noche in San Francisco spends ten minutes taking photos before they even order).
It’s this sort of insight-based problem solving that data-driven retailers are particularly good at, and as more formerly pure-play e-commerce retailers open physical stores, they are using their inherent grasp of technology and lack of legacy overhead to outmanoeuvre incumbents. But rather than just trying to compete with Amazon and the like on every front, Shulman thinks “the best retailers will be the ones who take the time to understand the unique needs of their targeted customer base, has a dialogue with those customers, and does everything they can to cater to those needs. For most shoppers, that’s a friction-free shopping experience.” But that’s not to say all innovation has to be serious – “Intentional gimmicks are fine, as long as you know that going in – it’s unintentional gimmicks that are the issue”. Using data science to build creative outputs may seem counterintuitive, but what links them is the opportunity for personalisation – amplified through their data, the customer reveals themselves to the brand; not just what item they want or what price they’ll pay, but what moves them, their emotional state before and after purchase, and other signals previously too weak to detect or act on. This can have powerful results – from Spotify’s playful use of both broad and narrow aggregated listening data to create memorable advertising or deliver personalised bursts of nostalgia direct to its customers, to Audi’s live billboard that changes its message based on weather, time or traffic to ensure the most resonance with viewers, better use of data means the boundaries between “functional” and “emotional” activities (or “operations” vs. “brand”) are blurring.
One area that will undoubtedly change retail propositions in the next few years is automation. “I was actually very sceptical about the need for robotics in retail stores until recently,” says Shulman, ”but I am impressed with the retailers who have started using robotics to handle administrative needs such as back stock put away, picking, ship from store and shelf compliance tasks.” Aside from Amazon, who have their own robotics division and more than 45,000 robots working in their warehouses, one such retailer is Walmart, who announced last October they will be using autonomous shelf-scanning robots from Bossa Nova Robotics in 50 stores. Trundling around the aisles (and able to dodge obstacles), the robots use the latest advances in computer vision and a host of sensors to instantly identify which products are on the shelves, assisting in a range of tasks from stock checking to planogram and pricing compliance – freeing up human employees for more valuable work. As Shulman points out: “Unfortunately, due to the cutback of store labour over the years, the customer has been widely ignored so that the associate can manage an array of administrative tasks. With the proliferation of technological automation in the store, the associate can get back to focusing most of their time on the customer.” Whilst the Walmart robots are designed to retrofit onto existing store designs, the opposite approach is also emerging: designing the store around a robotic stockroom – as seen in Asics’ Regent Street flagship created by Brinkworth and the Au Pont Rouge department store in Russia – although as of right now these focus more on the theatrical display of watching the robots at work as a differentiator and talking point, rather than delivering major efficiency gains.
Whilst Walmart assure that the robots’ introduction won’t lead to any job losses, with between 30-50% of retail jobs deemed “at high risk” of at least some automation according to the World Economic Forum, and virtual humans becoming more realistic by the day, are retail workers right to fear that increasing use of robotics will put them out of a job? Shulman is optimistic: “I think the role of the store associate is to take care of the customer and make sure their visit is so engaging that they come back. Retail workers who prefer that their job is evolving to be more consumer-centric and less administrative-focused will appreciate automation.” Still, it’s likely that many retailers, conditioned over many years to use each new technological advance as an excuse to reduce headcount, will be tempted to do the same thing with robotics – and that’s probably a mistake. “Competition today is about more than just price and location. Informed, credible and inspiring store associates are a major differentiator,” says Shulman. What remains to be seen is whether those same retailers are prepared to invest in more training for their employees: both on how to effectively work alongside robots and AI, and to reskill to deliver the expected improvements in customer service; as with any new technology inside stores, impacts on the retail experience need to be considered as part of a delicate balance, and, for now at least, examples of the concrete benefits to customers from automation are hard to come by.
From a practical perspective, although getting the most out of the technology they have access to may seem challenging, retailers shouldn’t be afraid to have an honest conversation about their capabilities and seek outside help where necessary. “Data is accessible to everyone, and the tools are much better than they used to be,” explains Shulman. “Our role as a partner is to bring together an ecosystem of providers and technology for retailers to leverage; we’re not going to be creating the experiences, but we’ll ensure you can measure the impact of them, and that’s vital to learning and improving from everything you do.” It’s clear that where remaking retail is concerned, there’s never been a better time to start that journey – as Yazdan puts it: “Possibilities are endless and we are just getting started.” But what do those possibilities look like? Read the final article in our series to find out.