By R. Larsson, Advertising Week
For years, marketers have talked about fragmentation as if it were an unfortunate side effect of modern media. Channels multiplied. Platforms proliferated. Audiences scattered. Measurement became more difficult. Yet today’s fragmentation challenge runs much deeper than a growing number of media touchpoints. It is increasingly a data problem, an activation problem, and perhaps most importantly, a customer understanding problem.
The rise of retail media has accelerated this reality. What began as a highly effective model for closed-loop attribution has evolved into a broader industry expectation. Marketers have become accustomed to environments where they can directly connect media exposure to purchasing behavior and prove business outcomes with unprecedented precision. Once that capability exists, it becomes difficult to accept anything less.
“The ability to show that a customer saw an ad and then purchased a product is a marketer’s dream,” explains Steve Rowbotham, CEO and Founder of Navigator. “It’s created an expectation around accountability and measurement that every sector now wants to replicate.”
The challenge is that not every category resembles retail.
In grocery, a handful of major players control significant market share. In e-commerce, Amazon dominates. In mobility, platforms such as Uber provide substantial scale. But industries like travel, healthcare, financial services, and many other sectors are fundamentally different. Market share is distributed across hundreds, thousands, and sometimes millions of individual providers, platforms, and booking environments. No single player possesses enough reach to create meaningful scale on its own.
This creates a paradox. The data exists. The customers exist. The signals exist. But the ability to unify those signals into something marketers can actually activate remains elusive.
For brands, the implications are significant. Traditional approaches to audience building increasingly struggle in environments where customer journeys span multiple disconnected platforms. A traveler might research a trip on one website, book a flight through an online travel agency, reserve a hotel directly through a brand site, and engage with countless other touchpoints along the way. Each interaction generates valuable data, but without a mechanism to connect those moments, marketers are left with fragmented snapshots instead of a complete picture.
“The reality is that these aren’t travelers,” says Rowbotham. “They’re consumers who happen to be traveling.”
That distinction matters because the value of commerce data extends far beyond the category where it originates. A luxury traveler booking first-class airfare may be a highly relevant prospect for a premium fashion brand. A consumer researching family vacations may represent an opportunity for financial services, automotive brands, or healthcare providers. The transaction itself is often less important than the insight it reveals about the individual behind it.
The next phase of commerce media, therefore, may not be about building more individual networks. It may be about aggregation.
Effective aggregation goes well beyond simply collecting data from multiple sources. The real challenge is creating a unified and de-duplicated view of the customer. Multiple transactions occurring across multiple environments must be recognized as belonging to the same individual. Only then can marketers begin to understand behavior patterns, purchase intent, and long-term customer value with meaningful accuracy.
This is where the conversation shifts from volume to intelligence.
Many marketers already have access to enormous quantities of data. What they often lack is the ability to connect it, operationalize it, and integrate it with their own first-party customer understanding. The opportunity lies not in replacing a brand’s knowledge of its customers, but in enriching it through broader behavioral signals.
Yet solving the data challenge is only half the equation.
Audience intelligence and creative effectiveness have long existed as separate disciplines. Media teams focus on targeting. Creative teams focus on messaging. But in an increasingly fragmented environment, those worlds can no longer operate independently.
As Rowbotham notes, even the most brilliant creative execution fails if it reaches the wrong audience. Conversely, the most accurate audience targeting in the world cannot overcome irrelevant or uninspiring messaging.
The problem is that fragmentation often forces brands toward generic solutions. When marketers lack confidence in audience understanding, they default to broader targeting. Broader targeting typically leads to broader messaging. The result is creative that feels increasingly interchangeable, designed to appeal to everyone and therefore resonating deeply with no one.
This is where artificial intelligence enters the conversation—not as a replacement for marketers, but as a mechanism for managing complexity.
For decades, digital marketing promised the ability to deliver the right message to the right person at the right time. In practice, that promise has often fallen short. Data became overwhelming. Audience segmentation remained limited. Creative production could not scale to match the granularity that modern targeting required.
AI has the potential to change that dynamic.
The ability to analyze billions of data points, identify meaningful patterns, and generate tailored creative variations at scale creates possibilities that simply did not exist before. Rather than testing a handful of campaign variations over months, marketers could potentially iterate thousands of creative combinations in near real time, continuously learning what resonates and adjusting accordingly.
“The feedback loop has historically been too long,” says Rowbotham. “What AI gives us is the ability to learn faster, optimize faster, and create at a scale that wasn’t previously possible.”
That does not mean the industry’s future is guaranteed.
Like many industry leaders, Rowbotham remains optimistic about AI’s potential while remaining cautious about execution. The technology itself is not the primary challenge. Governance, interoperability, workflow integration, and incentives may ultimately prove more difficult than the algorithms.
“The more you unpack it, the more complex it becomes,” he says. “Anyone who claims to have all the answers right now probably understands the least.”
That humility may be one of the most important lessons for marketers navigating the next phase of industry transformation.
The shift toward AI-powered media, audience intelligence, and agentic systems will not happen overnight. Despite the excitement surrounding autonomous media buying and intelligent optimization, most experts acknowledge that meaningful adoption will likely take years rather than months. The infrastructure, standards, and guardrails required to support these systems remain works in progress.
Still, the opportunity is difficult to ignore.
For perhaps the first time since the early days of digital advertising, the industry has a realistic chance to revisit its original vision. Not simply to automate existing processes, but to create marketing systems capable of understanding audiences more deeply, delivering more relevant experiences, and generating more meaningful business outcomes.
Whether that future becomes reality may depend less on the technology itself and more on the choices the industry makes along the way.
“If we focus purely on making money, we’ll mess it up,” Rowbotham says. “The outcome for the brand and the customer has to come first.”
In a marketplace increasingly defined by fragmentation, that may be the most important form of alignment of all.
