McKinsey declared 2023 the breakout year for generative AI, but 2024 will be the year predictive AI takes center stage for retailers. 

Advanced personalization has long been the dream of retailers worldwide. But at Untie Nots, the company I work for and part of the Eagle Eye Group, we believe this dream is close to being realized. As my colleague and Untie Nots co-founder Cedric Chereau recently said in an interview, “With AI, retailers are on the precipice of achieving the retail marketing holy grail, true one-to-one personalization.”  

The transformative potential of predictive AI to deliver relevant content to the right people in the right place at the right time is enormous. However, making this one-to-one future a reality will require rethinking how retailers harness, manage, and leverage their data across all touch points.   

Obtaining Customer Buy-In for Next-Generation Personalization 

Customers want their favorite brands to anticipate their needs and desires, which is why we see robust consumer support for personalization initiatives. In the past, retailers have pursued this by creating broad segments of similar consumers and targeting them with specific campaigns — many still do. Predictive AI turns those broad segments consisting of thousands of customers into thousands of segments composed of just a single customer. 

This is the dream for retailers, but how can they get their customers on board? Consumers are more demanding than ever regarding personalization. McKinsey reported that 71% of consumers expected personalized interactions, with 76% frustrated when they didn’t get them. Another study revealed that 72% of shoppers said AI would improve customer experience. 

Companies concerned about obtaining customer buy-in shouldn’t worry because customers already want advanced personalization. Retailers, however, must acknowledge some apprehension. In their recent 2024 US Retail Industry Outlook report, Deloitte found that eight in ten consumers had little to no trust in retailers’ ability to use AI responsibly.   

Beyond the Hype: Prioritizing Predictive AI 

Providing the advanced personalization consumers expect hinges upon high quantity and high-quality data. However, while generative AI offers retailers the tools to create engaging content and a near-infinite number of customized interactions, predictive AI integration offers in-depth insights that can generate sustained ROI. 

This is one area organizations have yet to exploit, with Gartner reporting that 55% of organizations remain in the piloting or production phase with generative AI. Most retailers use generative AI to produce content automatically, but they’re not exploiting predictive AI for hyper-focused customer targeting. 

One company that has made the transition is global E-commerce giant Amazon. They’ve used predictive AI to recommend clothing items to customers based on the best-fitting size. Amazon says their algorithm connects data points ranging from sizing relationships, sizing systems, product reviews, and customer fit preferences to recommend the best size for customers. This example is one way that predictive AI can make hyper-personalized shopping experiences a reality. 

Also Read: How Customer Data Management Empowers Your Business

Data Science in Action: Implementing Personalization for Increased ROI 

Personalization can occur across the buying journey and every channel, with significant rewards for companies investing in it. As we cite in our eBook, AI & the Current State of Retail Marketing, fast-growing companies derive 40% more revenue from implementing robust personalization. 

However, we also highlight several challenges retailers face in the current climate. For example, over a third of customers let their loyalty memberships lapse because of a lack of engagement, and just under a third believed these programs offered little value. 

In other words, predictive AI is a generational opportunity to offer both enhanced value and engagement.   

Predictive Personalization 

One of the most significant applications of AI is anticipating what customers want before they do. The ability to predict behavior and needs accurately can unleash new opportunities, like personalized cross-selling. 

Grocery giant Whole Foods incorporated this into its Just Walk Out stores, which already leverage AI to eliminate cash registers. Predictive AI analyzes shopping activity to predict future behaviors on an individual level. 

For example, suppose a customer regularly purchases Italian-related ingredients. In that case, Whole Foods can respond by automatically sending the customer promo codes for Italian-related products, calibrated to the optimal depth of discount and product-offer pairing to encourage that individual customer to redeem it. None of this requires human intervention. 

Engagement-First Loyalty Programs 

Personalized offers are one aspect of retail marketing that AI can impact; loyalty initiatives can also benefit. Lack of engagement and perceived value are two reasons customers leave loyalty programs. More than 90% of companies have a loyalty program, so having one isn’t enough for retailers to capitalize on brand loyalty. Loyalty program managers must do more, and predictive AI can play a significant role. 

European supermarket giant Carrefour is one example of a company that has leveraged predictive AI to revamp its loyalty scheme. To encourage more frequent engagement among its loyalty members, they utilized Eagle Eye’s personalization platform to power the Carrefour Challenges app. Today, the retailer uses predictive analytics to determine what will trigger the next customer action, known as “the nudge,” and then automatically presents that trigger to the customer through the app. 

Carrefour isn’t the first to recognize the benefits of gamification in building a more engaging retail experience, but it’s one of the standouts. 

Helping Customers to Save 

In a report released last year that examined global loyalty behaviors, Grocery’s Great Loyalty Opportunity found that 60% of consumers believe personalized offers enable them to save money when they shop. Saving on the products customers love the most has always been a primary driver in loyalty program memberships, but how does predictive AI help customers save? 

Again, it relies on uncovering trends to deliver personalized offers that may be invisible to the human eye. However, it can also be about perception. UK supermarket ASDA rolled out its first-ever digital-only loyalty program, ASDA Rewards, in 2022 under the tagline, “Pounds, Not Points,” to underscore the app’s ability to save shoppers money. 

Powered by Eagle Eye, ASDA Rewards now has over 6 million active members, and 49% of the retailer’s total sales were linked to the program. Again, this is another loyalty program rooted in predictive AI that provides personalized offers and includes gamified elements that yield significant results for the retailer implementing it.  

Predictive AI is the Future 

Predictive AI is the holy grail. Retailers have dreamed about a tool that allows them to use their customer data to deliver genuine one-to-one personalization, increase loyalty program engagement, and create more value for their customers. However, the ultimate impact of predictive AI is yet to be fully realized. As an evolving technology, the future may reveal new opportunities for predictive AI to improve the retail experience and drive bottom-line results for retailers.

Also Read: All You Need To Know: Google’s Privacy Sandbox

Challenges remain regarding implementation and maximizing its potential. Still, retailers that embrace predictive AI determine the optimal way to integrate it into their existing systems and workflows. Working with partners that can streamline the adoption process will gain a substantial competitive edge in the future. 

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