November 10
Let’s be honest. Over the last thirty years, marketing has lost some of its influence in the C-suite. Marketers have always struggled to make the case that the money they spend is an investment in growth and not merely a cost of doing business. Marketing’s contribution to the bottom line is often less clear than more tangible investments like the introduction of a new product line or store refurbishment or other alternatives. Most marketing leaders speak in terms that are alien to the holy trinity of the enterprise: the COO, the CFO and the CEO. For example, when CMOs talk about “brand health,” they rarely link it to goodwill, which CFOs accept to be the difference between share price and the underlying value of the company’s assets. All of this has created a dynamic in the C-suite where there is often more skepticism directed to the CMO than any of her peers around the leadership table.
I believe that is all about to change.
For large consumer-facing enterprises, marketing may be the single largest source of behavioral intelligence — insights into how consumers engage with content, brands and products — available to the organization. Yet most companies continue to evaluate advertising primarily through its contribution to sales, customer acquisition and brand equity, overlooking a potentially enormous additional source of enterprise value: the behavioral data generated by their advertising investments. This “advertising-derived intelligence,” when acquired compliantly and with the right permissions, and not withheld by the walled gardens or sourced from low-quality publishers, will be the equivalent of discovering gold in your backyard — a new source of wealth that costs virtually nothing to extract, filter and create a systemic enterprise advantage with.
Consider a major U.S. bank investing more than $5 billion annually in marketing. Depending on its media allocation and costs, those investments will likely generate hundreds of billions of advertising exposures each year. The resulting opportunities to observe consumer engagement, preferences, and responsiveness could surpass and would certainly augment the volume of interactions generated through the bank’s owned digital channels, and may well eclipse them. Importantly, this intelligence extends well beyond the bank’s existing customers, reaching prospective customers and consumers who have yet to enter the financial-services category.
The most consequential distinction, however, is the breadth and diversity of behavioral intelligence advertising can potentially generate, not merely its scale.
An enterprise’s proprietary data is largely constrained by the products it sells, the services it provides, and the interactions consumers have within its owned channels. A bank knows what its customers earn, save, borrow, spend, and invest. It can observe how they navigate its digital properties and why they contact customer service. These are enormously valuable signals, but they offer a relatively narrow perspective on the broader motivations, interests, aspirations and circumstances that influence consumer decisions. In short, they offer little if any competitive advantage over near-peer competitors.
Advertising operates across a much wider spectrum of human activity. Permissioned behavioral signals derived from advertising interactions across news, entertainment, travel, automotive, sports, wellness, technology and countless other environments can potentially reveal dimensions of consumer behavior that would never surface through a banking transaction or service interaction. A customer’s engagement with content about electric vehicles, international travel, home renovation, sustainable living or career advancement may reveal emerging priorities and aspirations long before those interests manifest into a financial transaction.
This is where advertising-derived intelligence becomes especially valuable to enterprise AI. When relevant, privacy-compliant, behavioral signals — sourced from high-integrity vendors — are incorporated into customer segments, predictive models or digital twins, they can add dimensions of context unavailable from the enterprise’s own transactional data. They can enrich understanding of consumer mindset, motivations, emerging needs and receptivity to different products and propositions. Critically, these signals can illuminate why consumers might behave in a particular way, rather than simply documenting what they have already done. They may also illuminate or validate emerging product opportunities or competitive offering gaps before they manifest in the marketplace. Of course, validating those motivations requires more than observing engagement alone, there must be an underlying linkage to an understanding of consumer mindset, but that is a surmountable problem that companies are already engaged in solving.
For a bank, this could mean recognizing that two customers with nearly identical financial profiles have fundamentally different motivations. One may be motivated by financial security and stability, while the other is focused on experiences, personal advancement, or entrepreneurial opportunity. Those differences may be virtually invisible in the institution’s first-party transactional data but potentially detectable through patterns of behavior and engagement across the broader digital ecosystem.
As enterprises increasingly deploy proprietary AI to improve product development, customer experience, demand forecasting, personalization and strategic decision-making, the ability to incorporate this broader understanding of human behavior could become a meaningful competitive advantage. Models informed by responsibly sourced, diverse behavioral intelligence may outperform those trained principally on historical transactions and interactions within the enterprise’s own channels. Two companies I consult with today have validated this already.
The financial implications are substantial. Advertising investments have traditionally been measured by the commercial outcomes they produce. But if the behavioral intelligence they generate can improve decisions across an enterprise — generating tens of billions of dollars in annual incremental revenue — the economic return on those investments would extend well beyond traditional marketing performance metrics.
Realizing that value will require more than accumulating data. Enterprises must establish appropriate access rights, consumer permissions, data quality standards and governance, while demonstrating that additional behavioral intelligence actually improves model performance and business outcomes.
The strategic opportunity is to recognize advertising as an investment in both commercial growth and enterprise intelligence. As AI becomes central to competitive differentiation, the ability to understand consumers beyond the confines of an enterprise’s existing commercial relationships could become one of marketing’s most valuable contributions.
The question CEOs and CFOs should be asking is whether they are systematically undervaluing advertising by measuring only what it sells while failing to account for what it teaches the enterprise about human behavior.
If marketing investments yield vast amounts of rich behavioral data capable of fueling enterprise growth in a way that other functional disciplines can’t match, yet directly benefit from, perhaps those investments, and by extension the CMO, will be seen in a new light. Will the CMO of the future be regarded as a trusted business partner who is creating real business advantage for peer functions through the data “exhaust” of advertising — and to a lesser extent, experiential and sponsorship investments? Will a new definition of ROAS be stretched to include the enterprise value of behavioral data generated? Will marketing, with its strong institutional muscle memory when it comes to cultivating customer relationships, be in the best position to connect those activities to catalyzing even more behavior insights through a robust zero-party data strategy (look that one up if you’re not familiar with the term)? I believe the answer to these questions is a resounding yes, and that’s why I believe we are standing on the precipice of the renaissance of marketing.
In part two, I will outline the necessary preconditions to fully realize this potential and suggest some organizational evolutions that will improve workflow, speed-to-market and creative, and offer optimization for segments that may be invisible to the enterprise today because of the rigid way in which market segmentation is developed and applied.
This op-ed represents the views and opinions of the author and not of The Current, a division of The Trade Desk, or The Trade Desk. The appearance of the op-ed on The Current does not constitute an endorsement by The Current or The Trade Desk.