WRAL Techwire: Streaming’s dirty secret - you’re still the product

Last week, the Texas attorney general filed a lawsuit against Netflix, accusing them of misleading their subscribers in violation of the Texas Deceptive Trade Practices Act (DTPA). This legislation protects consumers from “false, misleading, or deceptive acts or practices” in commerce. The lawsuit accuses the streaming giant of secretly collecting and monetizing customer data while publicly presenting itself as a privacy-conscious alternative to traditional advertising platforms.

Texas claims Netflix tracked detailed viewing behavior, shared information with advertising technology partners, and designed engagement features specifically intended to maximize viewing time and user dependency, including among children. Netflix denies the allegations, but the case itself points to something much larger than a legal dispute between a state government and a streaming company.

The lawsuit captures a broader transformation that has quietly reshaped the entire technology industry over the last three decades. Netflix is not suddenly behaving differently from the rest of Big Tech. It is following a familiar economic progression that consumers continue to underestimate. Technology companies launch with one story, spend years accumulating behavioral data under the banner of convenience and personalization, and eventually pivot toward monetizing that data once they achieve sufficient scale and market influence.

We have seen this movie before.

Google began as a remarkably useful search engine whose mission was to organize the world’s information. Facebook emerged as a digital tool for connecting friends and family. Amazon promised unprecedented convenience when shopping for books. Netflix positioned itself as the escape hatch from the bloated advertising ecosystem of cable television.

In each case, consumers embraced these platforms because the value proposition appeared straightforward and mutually beneficial. The services were useful, often revolutionary, and usually inexpensive. None launched with advertising, and Netflix and Facebook were vocal in stating that part of the value proposition was that there were no advertisers on the platform. In the early years, the focus was growth rather than profitability. Trust mattered more than monetization.

What most consumers did not fully appreciate was that another process was unfolding quietly beneath the surface of these platforms. Every search query, viewing session, product purchase, location ping, social interaction, and engagement pattern became a behavioral signal feeding increasingly sophisticated prediction systems. Over time, the platforms themselves became less valuable than the behavioral intelligence they collected.

The data became the business.

That transformation is particularly important in the streaming industry because television occupies a uniquely intimate role in modern life. Social media scrolling, web search, and e-commerce shopping capture fragmented attention in short bursts. Streaming television captures sustained emotional engagement over long periods of time. Families gather around it. People relax around it. Viewers lower their defenses around it. For decades, television advertisers understood the power of emotional storytelling, but they relied on crude approximations of audience behavior through statistical measurement systems like Nielsen ratings. Streaming platforms change that entirely.

Modern streaming ecosystems collect enormous amounts of behavioral information. Platforms can measure how long viewers watch a program before disengaging, which scenes trigger rewinds, what time of day audiences become most receptive, and how different genres correlate with purchasing behavior or emotional engagement. Recommendation systems continuously refine themselves using these signals, learning not only what consumers prefer but how to hold their attention longer. The result is that television is no longer simply an entertainment medium. It has become a behavioral analytics platform.

This transformation becomes even more significant when viewed through the rise of connected television, often abbreviated as CTV. Most consumers still think of televisions as relatively passive devices, but smart televisions are actually software platforms embedded directly inside the home. Companies like Roku, Samsung, LG, Amazon, and Google are no longer merely manufacturing televisions and streaming hardware. They are operating data collection ecosystems connected to sophisticated advertising infrastructure.

Here’s how it works. The obvious level is that the application through which you are watching content, like Netflix, captures what you watch. Most consumers understand and accept that their streaming provider captures streaming history just like your web browser captures browsing history. But what is less obvious is that your hardware may be doing the same thing.

Most smart TVs deploy Automatic Content Recognition, or ACR, which can identify what users are watching regardless of source. ACR captures a subset of pixels from the content you are streaming and analyzes them against cloud databases. The same way a vision AI system can detect objects it is trained upon, ACR detects content from libraries of data it has been trained upon. This allows ACR-enabled screens to monitor viewing activity across streaming platforms, live television, and even external HDMI-connected devices. The television is no longer simply displaying content. It is observing behavior. Even intermediary devices like Chromecast and Firestick are likely capturing information about what content streams across them.

In 2017, television manufacturer Vizio settled a lawsuit filed by the FTC for $2.2M over allegations of this kind of data collection without proper user consent. Vizio was then processing and selling data to advertising brokers. Looking back, $2.2M is a really tiny slap on the wrist, and it did nothing to stop Vizio from continuing to collect user viewing data. Vizio simply updated their end user license agreement and out-of-box setup workflows to meet the minimum of user consent.

Vizio’s current policy states that Vizio OS products collect “viewing data, activity data, app usage, advertising interactions, device identifiers, network identifiers and information from connected devices”. Even more strikingly direct, Vizio specifically says its ACR systems can monitor “audio and video programming, ads, gaming content, third party apps in real-time and devices connected to the VIZIO OS, like a streaming stick plugged into an HDMI port.

The next time you stream a corporate presentation to your conference room television, consider that the TV might be capturing and analyzing what’s on-screen to mine data for advertisers.

I’m not picking on Vizio here, all the TV manufacturers are doing this. But it is worth asking yourself why Walmart chose to buy Vizio for $2.3B in 2024? Well, Walmart wasn’t deceptive. They stated openly that the acquisition was intended to accelerate the growth of Walmart Connect (its advertising business) through Vizio’s SmartCast operating system and connected-TV data infrastructure.

The value of your user data is a huge reason why flat panel televisions are so inexpensive to purchase. Connected television enables direct behavioral measurement. CTV platforms understand not merely what households watch, but how viewing patterns correlate with shopping habits, political interests, entertainment preferences, and consumer decision-making. The television is a node inside a much larger behavioral network linking entertainment, commerce, advertising, and artificial intelligence together.

The real significance of the Netflix lawsuit lies in the fact that consumers believed streaming platforms operated differently from the advertising-driven business models that dominated social media and search. For years, Netflix cultivated an identity built around subscriptions rather than surveillance advertising. Customers believed they were paying directly for a service rather than becoming the product themselves. The introduction of Netflix’s advertising-supported tier fundamentally altered that relationship because advertising businesses require far more detailed audience segmentation, behavioral targeting, engagement measurement, and identity matching than subscription-only services.

To be fair, Netflix held on much longer than most of their big tech peers. They sustained without advertisements for 25 years, before succumbing to the massive profit potential of selling user data. Google only waited 2 years to launch AdWords to monetize your personal search data. Facebook held off 4 years before turning on ads, which it timed to the launch of the “Like” button. Mark Zuckerberg was quite vocal about his concerns that advertising would kill the vibe and slow user growth. But it was always the master plan.

For Netflix, the incentives were simply too powerful to ignore. Content production costs continued to rise while subscription growth slowed. Advertising revenue offers far greater scalability than subscriptions alone, particularly when combined with sophisticated behavioral targeting systems. Once platforms possess detailed user data, the temptation to monetize it becomes almost unavoidable.

The deeper issue extends beyond advertising itself.

What we are witnessing is a new form of economic concentration that traditional antitrust frameworks are poorly equipped to address. Historically, monopoly regulation focused on companies dominating single market verticals. Railroads controlled transportation. Oil companies controlled energy production. Telecom firms controlled communications infrastructure. The industrial monopolies of the twentieth century were relatively easy to identify because their power was concentrated inside clearly defined industries.

Modern technology companies operate differently. Today’s largest platforms increasingly expand horizontally across adjacent industries while quietly integrating data between them. Amazon is simultaneously a retailer, logistics company, cloud provider, advertising platform, streaming network, AI infrastructure company, and healthcare participant. Google controls search, maps, browsers, mobile operating systems, video platforms, advertising infrastructure, and increasingly artificial intelligence systems that connect those services together. Apple combines hardware, software, payments, media distribution, and device ecosystems into a tightly integrated network.

Individually, these markets may appear competitive enough to avoid traditional monopoly scrutiny. Walmart certainly wasn’t challenged in antitrust court for their acquisition of Vizio. Purchasing an electronics manufacturer wasn’t obviously making them more dominant in the retail vertical. Collectively, however, combined behavioral intelligence creates extraordinary power.

This is what I would describe as a monopoly loophole within the Data Economy. Companies no longer need total dominance inside a single market vertical to achieve overwhelming influence. Instead, they gain leverage by accumulating enough cross-market behavioral data to distort competition itself. Data collected in one industry becomes an advantage in another. Viewing behavior informs retail advertising. Search history informs pricing strategy. Location data informs recommendation systems. Consumer attention becomes measurable, predictable, and increasingly steerable across multiple sectors simultaneously.

That shift changes the nature of economic power in ways policymakers are only beginning to understand. The industrial monopolies of the past controlled supply chains. The emerging data monopolies increasingly control decision chains. Behavioral data enables companies to personalize prices, shape recommendations, optimize advertising, prioritize products, and influence consumer choices at an individual level. Artificial intelligence accelerates this dramatically because AI systems become exponentially more powerful when paired with real-time behavioral history and predictive analytics. Data no longer merely describes consumers. It increasingly anticipates them.

This is why the future of antitrust regulation may require an entirely different framework. The central question may no longer be whether a company dominates a single industry. Instead, regulators may eventually need to ask whether a company possesses enough cross-market behavioral intelligence to undermine competitive fairness itself. Consumers should absolutely be informed when their data is being collected for use in a totally different industry vertical. It isn’t fair for the average consumer to assume that their TV viewing habits might inform a risk prediction algorithm that impacts their insurance premiums.

The Netflix lawsuit, regardless of how it is resolved in court, represents an early political signal that society is beginning to grapple with these questions. Consumers once viewed streaming services as an escape from the surveillance-heavy advertising systems of traditional media. Now the streaming platforms themselves are evolving into sophisticated behavioral analytics ecosystems connected to a broader network of data-driven influence.

Television shaped culture throughout the twentieth century because it controlled what people watched. Connected television may shape the twenty-first century because it watches us back.