Why European retailers are betting on AI
As shopping habits evolve, retailers are turning to artificial intelligence to help predict customer behaviour and offer a more personalised experience.
For today’s retailers, AI is fast becoming an invaluable tool to understand what shoppers want – and ensure their experience matches up with their expectations.
From supermarket chains with thousands of retail outlets to online clothes brands, fast-evolving AI technologies are helping them to increase sales, reduce excess stock and overall, improve profit margins.
“Retailers are under increasing pressure,” says Kate Edwards, Senior Research Analyst at JLL. “AI is a growing part of their business model to use the data they have to better understand their customers, predict future trends and boost business, from improving the customer-facing experience, to optimising supply chain processes.”
The growing focus on sustainability is equally driving uptake. For example, AI can help identify the opportunities for unsold products, reduce the levels of returned products and decipher optimal fulfilment options, delivering both cost and environmental benefits.
Food and fashion turn to AI
While AI applications are still in their infancy, retail spending on the technology is expected to reach $7.3 billion by 2022, compared to $2 billion in 2018, according to Juniper Research.
“Grocery retailers in particular have been quick off the mark to implement AI technologies in order to combat intense competition,” says Edwards. German grocery chain Kaufland uses dynamic pricing with digital shelf labels, with AI analysing large amounts of data such as competitors’ prices in order to instantly update prices and launch store promotions.
Fashion is another area where AI is helping to unlock value “Compared to grocery and daily goods, fashion retailers are under pressure to attract consumers’ additional disposable income – which can be aided by more personalised purchase recommendations,” Edwards explains.
Zara, for example, uses AI to analyse data on their customers’ buying history both online and in-store to buy in the appropriate quantities of products for optimum sales and produce more of its bestsellers. Similar technology recommends different store layouts for different locations based on localised updates that improve the customer experience.
In ecommerce, Asos, offers an AI-powered visual search that analyses images to suggest similar items, while a virtual styling app from Yoox allows users to try clothes on a digital avatar and makes recommendations for matching items.
AI also underpins other technologies that retailers are experimenting with – such as augmented reality or virtual reality experiences that can build brand awareness as well as encourage customer engagement.
Sephora is one omnichannel retailer that’s seen increased store visits thanks to its use of AI technologies - including a smartphone app and in-store augmented reality mirrors - that let customers virtually try on makeup.
Keeping on top of complex supply chains
For retailers with multiple stores across different cities or countries, AI is equally being used to improve efficiency.
“AI delivers far more accurate pricing and inventory forecasts than any person could do across a global business, and at the same time, alleviates the need to analyse data on a store-by-store basis, saving on labour and costs,” says Edwards.
In 7-Eleven franchises, AI assesses individual store performance and purchase trends. Employees use Microsoft Surface tablets to photograph store layouts in order to see how they differ, helping identify sales opportunities.
“AI, if implemented correctly, can help the role of the physical store and store performance,” says Edwards. This could prove a lifeline for struggling retailers facing a combination of rising costs and weaker consumer spending. Indeed, if AI can help drive additional sales and improve how stores function, retailers would be in a stronger position to withstand the challenges facing them.
Not all data created equal
A critical challenge for retailers is the quality of data required for meaningful analysis by AI.
“Retailers need to collect clean, substantial data in order for AI to deliver accurate recommendations,” says Edwards. “It isn’t enough to install an AI tool – there needs to be a human understanding of precisely what data is required.”
For most brands, this means acquiring a whole new field of expertise, whether in-house or on a consultant basis – which adds to the overall cost.
Growing concerns about data privacy and how corporations handle customers’ information create another hurdle: retailers must design and implement a user-friendly, transparent policy for collecting the data they need to power AI tools.
“Transparency in how data will be used – and a clear choice to opt-out – is vital to create and retain loyal customers,” says Edwards.
Data as the new digital currency for retailers
With technologies such as internet-connected sensors and augmented reality already generating new levels of information about how consumers shop online and offline, AI will become an integral tool for analysing these disparate data streams.
European retailers could follow the lead of high-profile U.S. chains that are increasingly making use of customer data to improve sales. North Face, for example, uses customer inputs such as planned activities to recommend products.
“A lot of data is available in retail – the next step is turning it into genuine insights,” says Edwards. “Within the next 10 years, AI will become more sophisticated, which will enable every aspect of the shopping experience to be personalised to individual shoppers’ tastes. Equally, it will streamline product design and stock delivery to help drive revenues for retailers.”