How Much Do We Really Understand About U.S. Consumers?
And how many people really watch broadcast TV?
The sands of how we understand American consumers are shifting and growing in complexity. From the cracks in traditional polling to the conflicting data on TV viewing, every method we use to measure behavior seems to raise as many questions as it answers. As 2024 comes to a close, these challenges are particularly stark—not just for politicians but also for advertisers and researchers striving to make sense of an increasingly fragmented population.
At the heart of this issue lies a paradox: as tools for understanding consumers become more sophisticated, the picture they paint grows more contradictory.
Polling: A Barometer Losing Its Balance
Polling has long been our barometer for understanding public opinion, but its recent record has been shaky. As we approach another election season, the cracks in polling methodology are hard to ignore. Why are they failing us? The problem lies less in the concept of polling itself and more in how the fragmentation of American life has outpaced the tools used to measure it.
Americans today live in increasingly diverse media and communication ecosystems, making it harder than ever to capture representative opinions. Pollsters need larger and more diverse samples to accurately reflect this fragmentation. However, traditional polling methods—relying heavily on phone surveys or time-intensive manual processes—are too costly and inefficient to scale to the required level.
This disconnect has far-reaching implications. Polls no longer fully capture the broad spectrum of voter sentiment, leaving critical gaps in understanding. When polling misses the mark, it doesn’t just affect election forecasts—it impacts any decision relying on accurate insights into what motivates and drives the average American. Until polling methodologies evolve to meet the demands of a more fragmented world, this gap between what we need to know and what we can afford to measure will only grow wider.
The Over the Air Mystery: Measuring Modern Television Habits
Polling struggles are just one example of how our tools for understanding consumers haven’t kept pace with their behaviors. Television, once the most measurable media, now presents another puzzle: how do we make sense of cord-cutting and the resurgence of OTA broadcasting?
According to Nielsen and ARF Dash, 14% of U.S. households rely exclusively on OTA television. Yet the National Association of Broadcasters (NAB) claims that 27% of households have antennas, nearly double the other estimates. Further complicating the picture, Consumer Technology Association (CTA) data reveals 38 million antennas sold in the last four years alone.
Why such a disparity? Part of the answer lies in how we define “adoption.” Nielsen recently stopped counting households using virtual multichannel video programming distributors (vMVPDs) like YouTube TV in their OTA figures, causing their estimate to drop by several percentage points. Meanwhile, NAB includes mixed-use households combining OTA with streaming or pay TV in their broader definition of antenna users. These distinctions, while technical, have a significant impact on the numbers.
Even more troubling is the gap between sales and usage. Are millions of Americans buying antennas and not using them? Or are our surveys simply missing a large segment of the population? The answer might lie in local market variations. Anecdotal evidence suggests that OTA adoption is strongly driven by access to local programming—particularly sports—which varies widely by region. National averages fail to capture this nuance, creating a blurry picture that overlooks the importance of geography in consumer behavior.
Advertisers Caught in the Crossfire
For advertisers, these discrepancies aren’t just academic but practical problems. Misjudging consumer preferences can mean millions of dollars wasted on campaigns that miss their mark. At the heart of this challenge lies an overreliance on behavioral data—metrics like clicks, views, and conversions—that, while helpful, only scratches the surface of consumer engagement.
As an industry, we’ve historically focused on behavioral data to measure ad performance and validate engagement. These tools have been invaluable for understanding what consumers are doing—whether they’re viewing ads, scrolling past them, or completing actions like purchases. However, behavioral metrics alone don’t answer the more critical question: why consumers are engaging (or not) in the first place.
The rumored acquisition of Lumen Research by DoubleVerify is a positive step in the right direction. By incorporating Lumen’s eye-tracking capabilities, DoubleVerify would add a new layer to its insights—actual consumer research. Eye-tracking offers something behavioral data cannot: a glimpse into attention patterns, emotional resonance, and the contextual factors that drive engagement. It’s a move from merely tracking actions to understanding their motivations.
This combination of behavioral data and consumer research is essential. Advertisers armed with the what and the why are better equipped to design campaigns that resonate on a deeper level. However, this also underscores a broader truth: as behavioral data becomes less accessible due to privacy concerns, a return to more affluent, direct consumer research may be essential for genuinely understanding audiences.
Getting Granular on the What and the Why
Our understanding of consumers is fractured. No single method or dataset can fully capture the complexity of modern American life, and as consumer behavior becomes more fragmented, the limitations of traditional tools are laid bare.
The challenge isn’t just outdated methodologies; it’s scale. Americans live in vastly different media ecosystems shaped by geography, technology access, and individual preferences. National averages blur these nuances, creating the illusion of uniformity when the reality is far more intricate. To regain clarity, we must combine behavioral data with consumer research that directly captures attitudes and motivations. However, scaling such research to match the complexity of today’s audiences has historically been prohibitively expensive and resource-intensive.
AI-powered solutions, like those developed by MX8 Labs, are transforming what we can achieve with survey research (full disclosure: I’m a shareholder). By automating data collection, analysis, and reporting, AI makes sophisticated insights achievable at an unimaginable scale. For instance, tools that once required weeks of manual effort can now deliver tailored insights in hours. AI doesn’t just enhance speed; it expands scope, enabling advertisers and researchers to go beyond the surface-level metrics of behavioral data to uncover the deeper “why” behind consumer decisions.
The path forward depends on embracing these innovations while keeping critical principles in mind:
• Granularity is essential. Broad national surveys must be augmented by regionally specific data that captures local variations and consumer context.
• Scale must be sustainable. AI-powered tools make it possible to gather nuanced insights across vast, diverse populations without breaking budgets.
• Transparency builds trust. As we deploy advanced tools, clarity in how data is collected, used, and protected is critical to maintaining consumer confidence.
• Nuance drives understanding. Combining behavioral data with deeper consumer research allows for a richer, more actionable view of audiences.
Toward Scalable, Sophisticated Consumer Understanding
Understanding U.S. consumers has never been easy. But the inconsistencies we see today—from polling errors to OTA adoption discrepancies—aren’t signs of failure; they’re opportunities for improvement. By leveraging AI-enabled research, we can align the depth of consumer insights with the scale and diversity of the modern audience.
By embracing scale, nuance, and transparency, we can move closer to truly understanding the people behind the data—and ensure our insights remain as dynamic as the consumers they reflect.
