AI is a non-negotiable for retailers. As the driving force behind a new era of hyper-personalisation, efficiency and sustainable retail experiences, its impact on the way we shop cannot be understated. So as more and more retailers integrate the benefits of AI into their growth strategy, what will be next for this transformative technology? And how will it shape the way we shop? Today’s consumers are craving a truly unique shopping experience. Imagine a world where your shopping needs are not
re not just met, but anticipated, simplifying the decision-making process like never before. The idea of data as the new currency is nothing new, but what is really setting retailers apart is how this data is used. We are only at the beginning, and as brands begin to scale their AI utilisation, its full spectrum ofbenefits for consumers and retailers alike will be uncovered. AI is a business necessity for retailers wanting to make sense of massive amounts of data. Just look at Temple & Webster’s advancement of AI capabilities — the furniture and homeware retailer has reaped value through a strong impact on conversion rates, as well as improved customer interaction and overall efficiency. But first, let’s look at the bigger picture. The AI transformation has only just begun Large Language Models (LLMs) will transform retail, expecting a compound annual growth rate of 21.4 per cent between 2023-2029 (as found by The Global LLM Research Report). Its unparalleled boost to customer experience, ability to automate tasks and drive better decision-making are key influencers in this rise. The result is hand-in-hand benefits to each part of the retail equation. Many of us will have experienced the product recommendation algorithms, which is one of the most commonly embedded applications in retail. Even looking back at the past year, the uplift in sophistication of these models has accelerated the way we shop. This has seen many retailers successfully extending the personalisation of an in-store experience across their online platforms, resulting in increased conversion rates for products recommended on the homepage, and a happy, returning customer. That search is effectively always learning and always trying to predict the right results, for the right customer, at the right time. We are moving away from an “if this, then that” style of recommendation, and actually starting to use more like-for-like customer behaviours, looking at how customers are interacting with products and starting to pressure-test what is working and what is not. Enhancing the customer experience from the back end Improving product recommendations is just one layer to how AI and LLMs are transforming retail. There is so much more that it can do for the customer experience – particularly in terms of operations and the back end of the business. In supermarkets, AI can be utilised for fresh produce management, with a centralised model to enhance inventory optimisation and replenishment. This not only benefits consumers by offering higher-quality, more available products but also contributes to a more sustainable shopping ecosystem. One of the first places Gen AI is landing is in the day-to-day work of the many people who play functional support roles in retail. Category management – for example, range and assortment planning, pricing strategies – is a typical use case where AI can augment human decision-making. With the generally-available release of Microsoft’s ‘co-pilot’ and equivalent new products from other big tech providers, this is set to accelerate dramatically in 2024. Walking the tightrope of privacy and personalisation As Generative AI reshapes the retail landscape, it is not without its challenges. And one of the foremost concerns is security. Cyber attacks are surging across the globe, and with AI systems relying on vast amounts of consumer data to provide personalised experiences, there is a growing need for robust data protection measures and transparency in how this data is collected and used. Retailers need to work between a delicate line of striking the right balance between personalisation and respecting individual privacy. This also comes down to ensuring AI is being used responsibly and ethically. If these systems are not carefully trained and monitored, they can inadvertently perpetuate biases present in historical data, leading to discriminatory outcomes in product recommendations, pricing or access to services. So investing in diverse and representative training data to mitigate such biases is a must. Despite the hurdles, Generative AI’s power within retail is undeniable Picture having a virtual shopping advisor from a department store who not only helps you find the perfect outfit but also offers styling tips, recommends complementary accessories and ensures the entire ensemble is in stock and ready for purchase. Navigating these challenges will take a holistic approach and competitive vision. We’re crafting a new retail landscape that tailors itself to individual preferences, empowers customers with expert knowledge and offers a harmonious blend of online and in-store shopping options. For those who succeed, they will transform what retail looks like and how the customer experiences it.