Are Data and AI Retail’s Secret Weapon?
How AI is transforming UK Retail.
The return of the Victoria’s Secret fashion show in October is a major cultural moment for the brand, capturing the attention of a new generation of young shoppers. Using AI to analyse purchase trends and predict fashion preferences, means Victoria’s Secret adjusted its inventory and marketing, turning a trend into its strongest quarterly sales growth in three years. This isn’t an isolated success, it’s a glimpse into how retailers could be capitalising on data-driven strategies to stay competitive.
The UK retail landscape is undergoing a seismic shift as data and AI redefine how businesses operate and connect with customers. Imagine a world where everything you buy is tailored to your preferences, whether you’re shopping online or in-store. This isn’t just a futuristic vision – it’s already happening.
How UK Retailers are leaving money on the table without embracing it
By Genevieve Broadhead, Global Lead, Retail Solutions at MongoDB
Imagine walking into your favourite clothes shop and the product displays are tailored to your exact size and favourite colour, allowing you to purchase your items without the need for cash, cards, or even your phone. This is the future of personalised omnichannel retail – where physical and digital experiences blend together seamlessly. Smarter use of real-time data and advances in personalised interactions are driving this shift, allowing brands to navigate market volatility and key retail moments like Black Friday, all while offering their consumers more emotional, deeper interactions.
UK online retail sales are forecast to rise by 4.5% in 2025 to £128.8bn, the strongest annual growth since 2021, driven by non-food online sales, which are projected to rise 4.1% next year, outpacing online food and grocery spending, according to Global Data. When looking at the year ahead, retailers must prioritise customer experience to secure long-term business prosperity and growth. One of the most transformative innovations is the use of AI and data, particularly its emerging search capabilities.
Matching rising consumer demand with data management
Customer expectations are constantly changing in retail, especially when it comes to personalisation and convenience. For example, Marks and Spencers has adapted to these changes by building its loyalty platform Sparks in-house so they can leverage data across their 7million customers to offer personalised rewards and offers., making shopping more relevant and engaging for customers. The shrinking of delivery timelines is another example of this.
While we may have waited a week or so for packages to arrive a few years ago, we now expect it the next day, or even on the very same day- look at the rise in last mile delivery via apps like Wolt who have moved from delivering food to groceries and now offer “(Almost) Everything Delivered” . We expect deliveries to be tracked to our door and to arrive at the time we specify. Similarly, we expect every interaction we have to be personalised. For example, when I open a chat box, the retailer already assumes I’m going to ask about my order and have an answer straight away on where it is. But these are difficult to deliver if you are a legacy retailer with decades of technical debt and siloed data.
Retailers need a centralised view of orders, logistics, customer information and preferences available in real-time. By combining data in a flexible way, it becomes far easier to meet these customer demands. Traditional tracking and order management approaches rely on static historical data, offering quite often outdated information with no interactivity aside from a call centre. Generative AI, by contrast, can be used to tap into real-time data streams – such as live tracking orders and user interactions – to create personalised conversational chatbots. The same inputs can be used for the next interaction, allowing retailers to create dynamic, personalised shopping experiences every time.
Having the right products in the right places
Retailers face immense pressures to operate more efficiently in a volatile market – rising costs, a highly competitive industry, and calls to be more sustainable. They are turning to technology and data to make smarter decisions. For instance, Lidl now uses real time data to power its automatic goods reordering platform for supermarkets and warehouses- the auto-dispo software will be used to increase efficiency along the supply chain when placing orders, which was challenging in the past due to complex data structures and the enormous volume of data to be processed.Similarly, Waitrose employs AI-driven cameras to monitor stock levels, improving operational efficiency and sustainability. AI, powered by advanced data analytics, enables data-driven decision-making at every level that can help businesses navigate all of this and get the right products in front of the customer. Vector search changes the game by analysing complex data sets through large language models (LLMs), enabling retailers to understand the complex relationships between products and customers.
But how does that really play out for the everyday retailer? A fashion retailer may analyse sales trends from previous years – what jackets sold particularly well? – alongside current fashion trends and real-time weather forecasts to predict which items will be in high demand for the upcoming season. A popular grocery chain may use AI to monitor perishable dairy items and automatically order replacements when stock levels dip below a certain threshold, ensuring customers have fresh products.
Generative AI enhances these predictions through its capability to understand the unstructured data in a retailer’s systems, for example, bills of material, product PDFs, images, and supplier descriptions. It can also generate synthetic data that fills in gaps, simulating market conditions and future trends. This allows UK retailers to be proactive, ensuring they always have the right products in the right places, thereby avoiding both overstock and stockout situations.
The price Is right
Price is now the leading factor governing UK consumer brand loyalty. According to a recent survey by PwC, 59% of UK shoppers rank price as their top consideration when deciding where to shop, highlighting the importance of competitive pricing strategies.
And backing these vital price decisions are swathes of data – that can be very challenging to properly analyse. Without knowing the parameters of your customers’ comfort zone, how can you properly set your price tags? Advanced data analytics enables retailers to analyse the price elasticity of their products and how sensitive consumer demand is to price changes. AI can help determine the optimal price point for retailers looking to maximise both sales volume and profit margins.
Editors closing:
AI is completely shaking up the retail game, helping businesses stay ahead by giving them a clearer picture of what customers want and how to boost their profits. As UK retailers continue to lead the charge in using AI, the industry is heading toward a future where every interaction, whether online or in-store, is smart, seamless, and sustainable. The businesses that embrace data now won’t just survive, they’ll define what retail success looks like in the years to come.
