Anusha Couttigane, senior analyst at Kantar Retail, insists AI isn’t simply the latest tech gimmick.
She envisages an ever-growing pool of customer data, combined with Generation Z’s relaxed attitude to data sharing, heralding a ‘huge opportunity’ for retailers.
Retail Connections caught up with fashion and luxury goods expert Anusha to get her insight on the latest AI-driven developments, ahead of her participation in our event this November – Artificial Intelligence: the new game changer in retail.
Anusha, what are the big fashion retail trends being driven by AI technology?
At Kantar Retail, we believe there are five big AI trends impacting the fashion industry right now:
Predictive analytics. This always brings pureplays to mind, but it’s far wider than that. If retailers adopt predictive analytics it affects the supply chain as well. With AI, suppliers can better adapt their lead times and capabilities to meet consumer demands in real time. It can also help retailers, especially in the fashion sector, identify the styles and types of products a particular shopper will like. Players like Fabletics do this well.
User experience. There are lots of examples of how AI can improve shopper experience, for instance the use of chatbots. AI can cut the time agents spend delivering customer service, but retailers need to think carefully about how this impacts the human service they offer. Luxury brand Cartier, for example, still has human agents using Facebook Messenger because they feel it’s an important part of the premium service it offers. It’s about being able to deliver a personalised service. Yet AI can do this too; the more developed AI is, the better those personal interactions will be.
IOT in the home. People who buy tech products such as Amazon Echo and Google Home are generating massive levels of data. By accessing that data, retailers have previously unknown insights about how customers behave at home, when they replenish items etc. They can use this to go beyond just blanket marketing to consumers, by being more targeted with the products it recommends and the timing of its marketing activities. Retailers need to use the data delivered by IOT to really get ingrained with the lifestyle needs of their customers.
Generation Z. This generation has grown up with technology and therefore it doesn’t have the same fears about sharing data compared to older shoppers who’ve had to adapt. In a few years’ time children born in the early 2000s will be going to university or graduating, and we will have a huge data set spanning the entire lifetime of this new generation of shoppers just as their disposable incomes are rising – it’s going to present a major opportunity for retailers.
Inversion of roles. Consumers currently tell technology what their needs are, for instance reordering essential products through their smart speaker when they’re running out. However, in 2-5 years the growing pool of data will enable retailers to predict key events in shoppers’ lives, like upcoming birthdays, or trends in purchasing patterns, such as when consumers will need to replenish items, so the technology will be telling consumers what they need before they even realise.
Do you think the retail industry is too focused on AI at a theoretical level, when it should be discussing practical use cases?
Retailers should always be focused on how AI solves problems, rather than using it purely as a marketing gimmick. I think one of the challenges that is currently limiting the progress of AI is that many retailers are struggling to see how it fits into their business; they aren’t quite sure how it can be incorporated into their strategy, or how to prioritise their technology investment.
The best thing retailers can do is embrace AI as a solution to a specific problem – and some are very good at this. Shop Direct, for example, will only introduce a new technology to solve a problem, instead of innovating for the sake of it.
AI will play a role in making certain technologies and functions more useful. Chatbots, for example, have been around for at least a decade, but now AI is now making them slicker and more responsive, enabling them to identify problems quicker and also provide a bigger variety of solutions in a more tailored fashion.
Tom Pattison, Kantar Added Value’s UK’s Cultural Insight Editor, described AI as ‘the hottest new collaborator’ for brands. Where do you think AI technology collaboration can deliver the greatest value for the retail sector?
Predictive analytics is very important, particularly for understanding factors like weather patterns and historical sales data.
In the fashion industry, one of the biggest emerging trends we’re seeing is a surge in shopping around cultural events such as the Chinese New Year, Diwali and Eid. These gifting occasions were not big in the West a few years ago, yet with so many consumers now shopping internationally, AI will help retailers to track consumers across continents and build a better understanding of global shopper behaviours. This will enable them to globalise more effectively by using that understanding of multinational events.
How do you think attitudes and approaches need to change to overcome barriers to AI adoption?
Cost is a pretty obvious barrier to AI adoption. The technology is evolving rapidly, so some retailers are hesitant about joining the bandwagon while it’s so fluid. They want to wait to see how it develops over the next couple of years and invest in solutions that emerge as secure winners.
However, the early adopters will reap the initial benefits of AI; firstly, because in an environment where many are still hesitating, those who step up will be seen as the real innovators taking an avant-garde approach. Secondly, the quicker retailers adapt, the longer they have to build up a digital picture of their customers and truly see the pay-off in the next 2-5 years.
To hear more insights from Anusha Couttigane, register for our upcoming retailer event – Artificial Intelligence: the new game changer in retail – on 16th November. It’s free to attend.