The Future of Personalization Is Connected: 4 Priorities for Marketers in the AI Era

Retailers have more customer data than ever before. They have sophisticated technology, talented teams and increasingly powerful AI tools, yet delivering truly personalized experiences across every customer interaction remains a significant challenge.

We sat down with Michael Hood, Chief Technology Officer at Wunderkind, to discuss how AI could reshape marketing infrastructure over the next three years. From the growing demand for real-time customer intelligence to the challenges of connecting fragmented systems, Michael believes the next phase of personalization will depend on how effectively brands bring their data, technology and customer experiences together.

As AI changes how software is developed and how consumers interact with brands, retailers face a new set of challenges. Customer expectations are moving faster than the infrastructure supporting them, while the emergence of agentic shopping creates even more places where brands need to recognize and respond to individual intent.

For marketers, that raises some important questions. How can brands deliver one-to-one personalization when customer data sits across disconnected systems? Will AI make sophisticated technology more accessible? And how can retailers build more intelligent experiences without taking on increasingly complex software projects?

Here are four areas Michael believes marketers need to be thinking about.

1. AI Will Change How Marketing Technology Is Built

Marketing technology has traditionally been shaped by the economics of software development. Building new capabilities requires significant investment, meaning technology providers have typically prioritized features that serve the broadest possible customer base.

Michael believes AI could begin to change that equation. "It may be possible to ship bespoke things to your clients that maybe only a handful of them care about, which you previously wouldn't have been able to justify an investment in."

As AI changes how software is developed, more tailored solutions could become commercially viable. Rather than relying exclusively on standardized functionality, brands may have greater opportunities to access technology designed around their specific needs.

For marketers, this could mean more flexibility in how they approach personalization and customer engagement. But the opportunity isn't simply to introduce more tools. It's to make existing technology work harder, with capabilities that address specific business challenges.

The next generation of marketing infrastructure could be more adaptable, helping brands respond to changing customer needs without continually rebuilding their technology stacks.

2. Connecting Data and Teams Will Remain a Major Challenge

Retailers aren't necessarily short of data or technical expertise, the difficulty is bringing those resources together across organizations that have evolved over decades.

Michael points to the complexity of established retailers, where physical stores, ecommerce operations and digital teams often developed independently. "Crossing those boundaries can be quite difficult in those companies."

Even when organizations overcome internal barriers, the technical challenges remain significant. Customer information is distributed across multiple systems, applications need access to real-time data, and experiences must respond quickly enough to meet consumer expectations.

For retailers, bringing everything together can become a substantial software engineering project. Michael expects this complexity to drive demand for more integrated solutions that brands can connect to their existing infrastructure. "I think increasingly we'll see folks, especially in the legacy retail space, but even the new wave of online-only retailers, reaching for highly integrated, custom solutions that are off-the-shelf from their point of view."

For marketers, the priority is finding ways to activate customer intelligence without creating additional operational complexity. Better personalization shouldn't require brands to start their technology strategy from scratch.

3. Real-Time Data Is the Biggest Barrier to One-to-One Personalization

Personalization has been a marketing priority for years. But delivering experiences that genuinely reflect an individual's complete relationship with a brand is far more complicated than tailoring a message based on a single interaction. For Michael, the biggest obstacle is clear: data. "The biggest challenge that I believe retailers will face as they try to deliver true one-to-one personalization is data."

True personalization requires brands to understand more than what a customer is doing in the moment. It means taking account of previous purchases, browsing behavior, expressed interests and interactions across different channels, then using that context to inform what happens next.

The challenge is making that information available wherever and whenever it's needed. Many existing systems weren't designed to receive and process customer data in real time. Even those that can must still overcome the complexity of connecting information across their wider infrastructure.

Without that connection, personalization remains fragmented. A brand might recognize a customer's interests on its website but fail to carry that understanding into another interaction.

For marketers, the opportunity is to move beyond static segments and disconnected campaigns towards experiences that adapt to customer behavior and intent. The goal isn't simply to collect more customer data. It's to make the information brands already have more useful.

4. Customer Context Will Define the Next Generation of Experiences

As AI becomes more embedded in customer interactions, the quality of those experiences will increasingly depend on how much context brands can provide. Michael sees an immediate opportunity in customer support.

Today, consumers can interact with a brand repeatedly and still find themselves explaining their history from scratch when they contact support. AI-powered chatbots may be capable of answering questions, but without relevant customer information, their responses can feel disconnected from the relationship.

Michael believes giving those systems access to customer context could make a significant difference. "There's no reason people should be starting over with a cold experience." That context might include purchase history, previous support tickets or products a customer has considered but not purchased. With a more complete understanding of the individual, AI-powered experiences can become more relevant and useful.

And the opportunity extends well beyond customer service. Rather than treating each interaction independently, brands could recognize interests customers have expressed over time and use that understanding to shape future experiences.

It's a direction that also becomes increasingly important as agentic shopping introduces new ways for consumers to discover and purchase products. For marketers, the shift is from responding to isolated actions towards building experiences informed by the wider customer relationship.

Building the Infrastructure for More Intelligent Personalization

AI could fundamentally change what's possible in marketing over the next three years. More tailored technology, increasingly intelligent customer interactions and new shopping channels all create opportunities for brands to deliver better experiences.

But realizing that potential will depend on solving a familiar problem: connecting customer data and making it actionable in real time. Preparing for that future doesn't necessarily mean replacing the technology marketers already use. It means making it more connected and intelligent.