HYPER-PERSONALISATION
Retail's new battleground
Personalisation has become a critical area for brands, particularly hyper-personalisation, enabling retailers to leverage AI and real-time data to increase relevancy, deepen customer relationships and drive loyalty.
But there is work to do.
According to this year’s Adobe consumer survey, just 26% of respondents described their digital experience with a brand they have an existing relationship with as “excellent” while nearly two-thirds expressed frustration “with brands that know a lot about me but don’t take my preferences into account”.
This deep-dive article is the second in our six-part series Consumer 2025 – from acquisition to advocacy produced in partnership with Bloomreach, which, powered by AI, personalises the ecommerce experience, unifying real-time customer and product data across channels so businesses understand what customers really want. The series is designed to analyse how the retail sector will rise to meet the evolving and growing expectations of consumers.
In this deep dive, we look at why personalisation should be an increasing area of investment for retailers and how to get it right.
Read the first deep dive on the path to purchase
Changing consumer demands
Consumers today expect personalisation and the bar is continually being raised. As Tom Youldon, partner at McKinsey, says: “When consumers observe something that works well digitally in one part of their lives, such as social media or computer games, they want to know why their experience buying shoes or groceries isn’t similar.”
He adds that pressure is piled on disruptors to introduce it in a retail context. “With that comes much better levels of service, much higher consumer expectations,” he says.
This strong desire has spawned hyper-personalisation. This takes personalisation to the next level, leveraging real-time data, advanced analytics and AI to drive more engaging customer experiences from unique adverts to customised landing pages and product recommendations, as well as dynamic pricing.
Retailers can step up their game
Retailers can leverage AI to drive hyper-personalisation to benefit numerous areas of the customer experience – and ultimately the business. For example, by driving customised content and product recommendations at scale, the technology can enable a more efficient and intuitive experience.
Retail Week data and insights director Lisa Byfield-Green cites Amazon’s Gen-AI shopping assistant, Rufus, as an example of a retailer applying hyper-personalisation. She says: “Amazon uses AI to improve its product listings and to summarise reviews to provide a better customer experience. It also offers personalised size recommendations, which is very helpful in the fashion category, as well as an AR virtual try-on for shoes.”
She adds that Walmart has introduced a smart AI-driven shopping assistant that allows customers to shop across categories based on natural language. For example: ‘I’m organising a birthday party for my five-year-old with a dinosaur theme. What do I need?’ The resulting experience is fast, intuitive and tailored to the consumer’s very specific request.
The Very Group offers customers personalised incentives and communication to customers
The Very Group offers customers personalised incentives and communication to customers
How The Very Group delivers on consumer expectations
Nicole Dutton, head of performance marketing at The Very Group, explains:
“Through CRM and digital, we engage with customers throughout their journey with us. It starts from the moment they open an account. Data underpins the programme and allows us to deliver tailored individual communications triggered by behaviour. This can help us drive purchasing intent and create cross-category selling opportunities.
“Part of this is our always-on retention programme. It uses machine learning to define the point at which a customer could stop shopping with us. In turn, the programme automatically offers up personalised incentives to continue shopping, delivered at the right time, in the right channel for that customer.”
Driving loyalty can also be supercharged by AI. Many consumers demand a more sophisticated offering than points or discounts. Instead, building relationships that demonstrate that a brand knows and understands its customers, and can anticipate wants and needs, is even more powerful.
Youldon says: “By understanding when a consumer is nearly out of pet food or olive oil, for example, or by engaging with them when they know they are in the market for a product rather than simply bombarding them, retailers can show that they understand consumer needs and build that trust.”
How Popeyes UK inspired loyalty
Fried chicken specialists Popeyes wanted to create a loyalty programme to drive retention, increase in-restaurant visits and spend throughout its 35 UK outlets, and ensure customer satisfaction. The concept centred around incentivising return visits and increasing spend by offering benefits such as complimentary appetisers or drinks, discount vouchers, and branded merchandise.
But the retailer was using separate systems for data management and customer communication, and was unable to integrate offline data from kiosks, tills and surveys into the loyalty programme.
Working with Bloomreach Engagement, Popeyes UK created the ‘Winner, Winner, Chicken Spinner’ loyalty programme, powered by all-in-one data management (combining online and offline customer data), a single customer view and marketing automation.
Popeyes UK customers who ordered via kiosk or till (via scanning the QR code on their receipt) as well as those who ordered online, could ‘spin the wheel’ on Popeyes’ mobile website to win prizes including a chicken sandwich, a meal giveaway and even free chicken sandwiches for a year.
The offline data generated from customer participation in the loyalty programme flows into Bloomreach Engagement, which updates each customer’s unique profile using AI. Since July 2023, Popeyes UK has awarded over 300,000 rewards to loyal customers. The retailer is also gathering offline customer data from guest Wi-FI in restaurants, as well as from post-purchase surveys.
Popeyes UK’s loyalty programme has improved its in-restaurant customer experience and increased customer retention, as well as driving positive financial results. Loyalty programme customers are three times more likely to make a repeat in-restaurant visit within 30 days than guests who do not.
Popeye's loyalty scheme improved the in-restaurant experience as well as customer retention
Popeye's loyalty scheme improved the in-restaurant experience as well as customer retention
Devising the right strategy
The ability to personalise messaging – on multiple channels – can also be hugely powerful.
As Youldon says, retailers’ hyper-personalisation strategies demand an investment in data and analytics as well as human capabilities. “You need to organise your operating model in an agile way,” he explains.
He adds that compelling use cases will depend on the retailer. “It could be that you invest heavily in ‘next product to buy’ recommendation engines and that probably makes sense in a context of relatively frequent purchases in which you have enough information about a consumer. The digitisation of sales journeys is another use case, as catalogue technology is almost obsolete. These things are top of mind for retailers when they come to think about how to implement personalisation at the coalface.”
Meeting the data challenge
Critical to effective hyper-personalisation is clean, well-organised – and consensual – data. Andrew Hood, founder and chief executive at analytics consultancy Lynchpin, says: “Data is critical to both the planning and execution of personalisation at any scale. It’s data that brings understanding to the range of different customer preferences and behaviours, and therefore that level of personalisation might bring a valuable increase in relevance for both consumers and retailers.”
Hood adds that data is the fuel for executing relevancy: “Understanding when someone is in or out of the market for a particular category and how their attributes and recent behaviours imply their current needs and desires.”
Gathering relevant customer data is an increasing challenge for businesses, particularly since the introduction of GDPR and Google’s phasing out of third-party cookies. Offering a clear value exchange to consumers, as well as being transparent about the use of data for personalisation, is key.
A range of different data sources are required to drive relevancy, from behavioural, demographic, transactional and social signals, and one of the biggest challenges lies in bringing that data together coherently. Hood says this presents a technical and an analytical challenge: “This typically requires consolidating it from different technical platforms, and then having good mining and modelling to pick out and continue to test next best actions for personalisation.”
Data can be consolidated in several different ways for personalisation. “Retailers may leverage existing CRM systems and cloud data warehouses or look to customer data platforms as separate platforms,” says Hood. “Irrespective of this, mapping the key data flows and the value of those data points for personalisation is essential to keeping any integration work focused on practical use cases.”
AI has supercharged the sophistication of every digital experience across multiple sectors, raising consumers’ expectations in the world of retail. For retailers who get it right, the benefits of hyper-personalisation are numerous, enabling them to better understand and deliver on their customers’ needs and thus engender trust and loyalty.
But it isn’t a quick win and companies must first crack the data challenge, ensuring they have a wealth of clean, consensual, consolidated data to drive engaging experiences and feed the AI machine. Once they have achieved this, the sky’s the limit.
In our next instalment of Consumer 2025, we look at the power of content. Watch out for it in August.
How to get hyper-personalisation right
Expert Analysis from Amanda Elam, Chief Marketing Officer at Bloomreach
A shifting landscape
Since consumers are using their mobile devices to browse and shop significantly more, brands must be focused on connecting shopping journeys and experiences across every channel. Whether it’s on mobile, desktop or both, personalised experiences are critical.
In the age of AI, consumer expectations have soared, and a disjointed customer experience puts brands at risk of churn more than ever. You can ensure you’re offering a connected experience to customers by having all of your customer and product data combined and powering your customer engagement strategy with a consolidated tech stack designed to make personalisation profitable.
How websites are evolving
No matter what you’re selling online today, if you aren’t using AI to personalise your customers’ experiences, you are likely falling behind your competition. Hundreds of AI-powered personalisation use cases are now accessible to ecommerce brands that are designed specifically to retain customers and make them feel more valued.
AI can be used to power seamless ecommerce experiences across every channel, in real-time, and at scale. Adopting AI-powered use cases will allow you to supercharge marketing campaigns, merchandising efforts, site search and content, while not sacrificing the efficiency and effectiveness of your commerce-driving team. The possibilities for profitability and growth have never been more limitless.
The growing role of social media
In modern ecommerce, being authentic and showcasing that authenticity to your customers is extremely important. This can be best done through your social media channels. It is every company’s goal to foster meaningful connections with customers but that has become increasingly difficult as the singular customer archetype has largely disappeared. Most customer bases now have diverse niche audiences that each have specific needs, interests, and preferences. Digital connectivity is shaping consumer behavior and showcasing who your brand is on social media will help your brand loyalists better get to know who they are buying from.
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