It’s July 1, 1941. A baseball game between the Brooklyn Dodgers and Philadelphia Phillies flickers on TV screens in New York City. Suddenly, the game cuts away. A Bulova watch appears, accompanied by a voiceover intoning, "America runs on Bulova time." In just 10 seconds, the world's first TV commercial airs, forever changing the advertising landscape.
For decades, TV advertising evolved steadily. Color replaced black and white. Cable expanded channel options. But now? Technology has catapulted TV advertising into a new era.
Today, Statista reports there are more TV households in the US than ever before. Time spent with TV is also growing, with the average American spending just over 5 hours a day consuming TV content. Plus, people still buy based on what they see on TV. 81% of TV viewers say a TV ad has influenced a purchase decision, and 63% report finding new brands and products through TV commercials.
Clearly, TV still captivates.
But the way we create, deliver, and measure TV ads has undergone a seismic shift. Let's explore six ways technology is flipping TV advertising on its head to produce increasingly effective campaigns.
It’s TV, but not as we knew it a decade ago. Nielsen reports that in just five years, the number of U.S. households accessing TV content via the internet has increased by more than 210%. Today, more than 70% of homes have a smart TV, and 83% of Americans are subscribed to a video streaming service.
And for good reason. Streaming and Connected TV reimagine traditional TV without boundaries. There are no schedules. No cables. You watch what you want, when you want.
For advertisers, the rise of streaming has resulted in new ways to engage potential customers. CTV allows for more interactive ad experiences, enhancing the viewer experience and ideally leading to higher conversion rates. For example, 70% of viewers who've engaged with a shoppable ad proceeded to make a purchase.
The other good news is streaming viewers are increasingly open to ads. In 2024, only 13% of consumers said they’re opposed to ads in streaming, down from 36% in 2022. And 70% of consumers say watching ads on streaming is just part of the typical viewing experience. 69% say they even prefer FASTs (Free Ad-Supported Streaming TV) over ad-free subscriptions.
Automatic Content Recognition (ACR) is a technology used in smart TVs to identify and track the content being viewed, providing advertisers insight into audience behavior and preferences.
Smart TV users must opt in to allow ACR tracking, so this data doesn’t account for everyone, but those who opt in are a large enough group to provide strong indicators of viewing behavior. Vizio alone had more than 18 million ACR-enabled TVs already by 2021.
After ACR recognizes the content being viewed, it can tie that to a specific household, helping advertisers understand the audiences they reach, how they’re responding, and make sure campaigns gain unique reach across linear and streaming TV rather than hitting the same homes too many times.
Invented in 1994 to track automotive parts, QR codes have evolved into a versatile marketing tool. Today, more than half of people ages 18-59 scan a QR code at least weekly.
When integrated into TV commercials, QR codes create a direct line between brands and consumers, instantly connecting viewers to promotional offers, exclusive content, or specific products featured in the ad. This direct engagement and interactivity cuts through traditional barriers to action, leading to higher short-term response rates.
They also provide a new way to track ad performance. With QR codes, TV gets a taste of digital-like insight into consumer response. Marketers can gauge the success of a campaign based on the number of scans, duration of engagement, and subsequent consumer actions, such as filling out a lead form or making a purchase.
And as one of the most trusted marketing channels, TV provides an environment where viewers feel comfortable scanning QR codes. In fact, 67% of people say they'll engage with a QR code displayed during a TV commercial if it resonates with their interests.
Gone are the days of gathering a bunch of people in a room to watch your ad and share feedback. Large Language Models (LLMs) can now forecast how well an ad will perform before it ever hits viewers’ TV screens. Yes, accurately. In 2023, academic research found agreement rates between human- and LLM-generated datasets reached over 75%. And as AI evolves, that number is only expected to improve.
AI creative pretesting tools test TV scripts against synthetic audiences to identify which will drive the greatest response from its intended audience, letting advertisers refine their messages for maximum impact.
The greatest advantage of using synthetic audiences is simply faster access to results. LLMs can test an unlimited number of concepts in minutes rather than the weeks or months that an in-person focus group or online survey could take. Plus, creative concepts can be tested with as little as a script while traditional methods typically require a produced spot, or at least animatics, for predictive results.
AI isn't just changing how we create ads. It's also transforming how we target them to each brand’s perfect audience. Today, machine learning can analyze vast amounts of data to identify the most receptive audiences for a given ad. This approach combines the best aspects of contextual targeting and look-alike audiences without the need to target specific user profiles or grapple with inaccurate IP addresses.
Here's how it works. Advertisers use machine learning to analyze data including geography, viewing habits, app usage, daypart, and device type. Advanced algorithms then identify patterns that indicate which factors correlate most strongly with ad engagement. These patterns become the foundation for media buying decisions. For example, it could discover that people who watch cooking shows on Tuesday evenings are extra likely to buy kitchen gadgets.
This AI-driven approach reduces reliance on third-party data, which can be expensive and inaccurate. And while this solution is relatively new, early adopters have already seen it outperform traditional targeting methods.
Consumers in the U.S. can now find content on more than 32,200 linear channels and 89 streaming video sources. This fragmentation makes it increasingly difficult for advertisers to identify the buys.
After all, when buying manually, the sheer effort required to plan and purchase thousands of lesser-known intersections is deeply intensive. This means top networks and publishers can become the “easy” button by default. Which in turn causes advertisers to fight for the same limited inventory, driving up prices and driving down ROI.
Enter AI-powered media buying platforms. These advanced systems handle the complex task of purchasing TV media by analyzing billions of first- and third-party data points across real-time viewership, historical spend, and performance data. The tech’s analysis then identifies the most valuable media opportunities for advertisers across the TV landscape, optimizing for factors like cost, reach, and predicted ROI. All based on each advertiser’s unique performance criteria and target audience.
Learn how brands are achieving the same reach as some of the biggest advertisers on TV at half the cost with Annika’s unique approach to media buying.