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Artificial intelligence (AI) and connected TV (CTV) have a perfect synergy that’s revolutionizing how advertisers connect with their audiences. CTV serves as a medium for streaming content, while AI acts as a sophisticated technology that improves the performance of CTV advertising campaigns. The integration of these two technologies has paved the way for advertisers to reach their target audience more effectively, making CTV advertising a powerful and efficient tool.
In this blog post, we’ll dive into how these technologies work together —and why you should jump on board with AI for CTV advertising if you haven’t already.
Why AI and CTV are a great match
CTV and AI are transforming how advertisers connect with their audiences and improving the performance of their advertising campaigns in the CTV space. They work together to make advertising smarter and more enjoyable for everyone involved. AI uses sophisticated computer programs to analyze and understand data, while CTV refers to the streaming services that consumers use at home. But what makes them a great match in advertising?
AI uses data to determine which TV ads are most exciting and relevant to certain people, and it can even adjust ads in real time to ensure viewers are always getting the most personalized experience. AI can provide suggestions to viewers based on previously watched content to help them find what they’d enjoy watching next. To sum it up, AI allows for:
- Precise targeting: AI uses data to determine which TV ads are most exciting and relevant to certain people.
- Personalization: AI can adjust ads in real time to ensure viewers are always getting the most personalized experience.
- Effective ad insertion: AI can provide suggestions to viewers based on previously watched content to help them find what they’d enjoy watching next.
CTV facilitates these AI-driven strategies for enhanced user engagement and satisfaction.
The rising popularity of CTV
CTV has become increasingly popular as people change the way they watch TV. Instead of the traditional approach, more viewers are now choosing CTV platforms for their entertainment. One of the main reasons for this shift is that CTV offers greater flexibility and lets viewers watch content at their convenience. The ability to skip ads on many CTV platforms also improves the experience.
CTV offers a great opportunity to interact with your target audience in a more engaging way. CTV allows for highly targeted advertising capabilities so you can reach specific demographics and households with tailored messages. Additionally, CTV provides valuable data insights that enable you to measure campaign effectiveness accurately.
If you haven’t embraced this advertising channel yet, you may be missing out on a growing and engaged audience. Here are three reasons you should add CTV to your advertising strategy.
Global video ad impressions
As a global platform, CTV has the unique ability to reach audiences worldwide. Unlike traditional TV, CTV transcends geographical boundaries and brings marketers a global audience, which makes it an ideal channel for global ad campaigns. No matter your target audience, they’re consuming content on CTV. In fact, a recent study showed that 51% of global video ad impressions came from CTV in 2022.
This abundance of global video ad impressions generates vast amounts of data, which AI can process in real time to help you make data-driven decisions and optimize your campaigns for diverse international audiences. AI can analyze viewer data from various regions, identify audience preferences and behaviors across borders, and tailor ad content accordingly. These data analysis capabilities ensure your ads get in front of the right viewers.
Viewers prefer ad-supported CTV
In 2020, the viewing time of ad-supported CTV surged by 55% while subscription video on demand decreased by 30%, according to TVision Insights. Viewers have a well-established preference for ad-supported CTV due, in part, to cost-effective access to premium content. Viewers are more engaged and less resistant to ads, as AI tailors ad content to viewer preferences and behavior to enhance ad relevance.
AI-powered insights can also aid in viewer retention and help you optimize your CTV campaigns. By accommodating viewers’ preference for ad-supported CTV and harnessing AI to improve the ad experience, you’re more likely to be successful in your marketing efforts.
CTV outpaces mobile and desktop for digital video viewing
eMarketer recently reported that U.S. adults spend 7.5+ hours each day on CTV —more than half of their digital video viewing time. Comparatively, they only spend 37.5% of their viewing time on mobile and 10% on desktops and laptops. These statistics demonstrate that CTV has become the preferred platform for digital video consumption, as viewers enjoy larger screens with superior quality for an immersive experience.
It’s important to note that AI is an essential CTV marketing tool, as it allows for precise targeting and content optimization. By utilizing AI on CTV, you can take advantage of this trend and deliver more engaging and effective campaigns to a growing and engaged audience.
How is AI already being used in CTV?
CTV has been integrated with AI across various facets and has revolutionized the television landscape. Here’s a look at how AI is already shaping the CTV experience:
Generative AI ads
Generative AI ads are taking CTV personalization to a whole new level. These innovative ads are customized versions of the same CTV ad to suit individual viewers. Some AI tools can generate several versions of the same CTV ad — swapping the actor’s clothing and voiceover elements like store locations, local deals, promo codes, and more — and can create up to thousands of personalized iterations in just a few seconds. Such capabilities are a game-changing approach to connecting with your audience.
Next, we dive into the advantages and impact of generative AI ads, and explore their transformative role in CTV advertising.
Contextual ads vs personal data
Generative AI ads use personal data, such as viewing history and demographics, to create highly personalized ad experiences. This sets them apart from contextual ads, which rely solely on the content being viewed. Using AI to harness this data, you can move beyond traditional contextual targeting and ensure your ads connect with viewers on a more individualized level.
Generative AI ads can be used to A/B test
Generative AI ads are not just about personalization; they also open the door to A/B testing. Being able to create several versions of one ad quickly allows you to experiment with various ad elements, such as messaging, visuals, and calls to action, to identify what works best for different segments of your audience and drives the best performance. This flexibility is especially valuable for refining ad campaigns and maximizing their impact.
What’s next for AI-generated ads like this?
The potential of AI-generated ads is exciting. As AI technologies constantly advance, we can expect even more personalized and automated CTV advertising. It’s a good idea to keep up with the latest AI-driven innovations to create more effective ad campaigns in the fast-evolving CTV space. The possibilities are endless, and you’ll likely find the most success when you embrace AI in CTV advertising.
Optimize streaming quality
AI helps viewers enjoy more seamless CTV experiences. By assessing network speed and user preferences, AI optimizes video quality in real time to reduce buffering interruptions. For instance, streaming platforms use AI to adjust video settings based on a user’s connection speed. This guarantees an uninterrupted and enjoyable viewing experience.
Review content for compliance
AI also has a part to play in quality assurance and compliance management. It assesses content alignment with technical parameters and moderates compliance with local age restrictions and privacy regulations. This means AI can identify and filter out unsuitable content to provide a safer and more enjoyable viewing environment for audiences while safeguarding brands from association with undesirable material.
Voice command
AI-powered voice command technology is increasingly used to control CTV viewing. This technology is embedded in streaming devices and smart TVs and allows viewers to interact with their CTV content through voice-activated commands. This personalizes the viewing experience and improves convenience, as it eliminates the need for remote controls.
CTV-integrated voice assistants like Google Assistant, Amazon Alexa, Apple Siri, and Samsung Bixby offer a more human-like interaction with the television, allowing users to give commands and receive tailored responses.
Content recommendations
AI can offer content recommendations that provide viewers a more personalized and engaging experience. Major over-the-top (OTT) services like Netflix, Hulu, and Amazon Prime use AI-driven data analysis to deliver tailored content suggestions to their audiences. By analyzing user habits in detail, AI can recommend content based on factors such as actors, genres, reviews, and countries of origin. This personalized approach helps viewers discover content that matches their preferences and enhances their viewing experience.
Advertising
Programmatic ad buying, driven by AI, automatically matches ad placements to specific audience segments based on behavioral patterns. It improves ad delivery by moving away from gross rating points (GRP) to more intelligent and targeted placements. This benefits marketers by ensuring ads are seen by the right people at the right time. It’s also cost-effective for publishers, as it maximizes the sale of ad spots to suitable buyers.
Automatic content recognition (ACR) technology, which AI powers, is integrated into smart TVs and streaming devices to improve ad relevance. It provides contextual targeting and extends the reach of ads across multiple devices. For example, platforms like Roku use ACR data to display ads to viewers who haven’t seen them on traditional TV. Similarly, Samba TV retargets mobile users based on IP address and aligns their viewing habits with their smart TVs.
Demand-side platforms
CTV advertising relies heavily on demand-side platforms (DSPs) to efficiently manage and optimize ad campaigns. These platforms use machine learning and AI in several important ways:
Using machine learning and AI to address data fragmentation
Data is abundant but fragmented when it comes to CTV advertising. DSPs are flooded with a massive amount of data, including information about households, viewer behavior, and viewing patterns. This data is far too much for manual analysis to handle effectively, which is where AI comes in.
By integrating machine learning algorithms into DSPs, AI can harmonize this fragmented data and provide valuable insights and a holistic view of your audience. AI can process zettabytes of data in real time, which streamlines the decision-making process and empowers you to compete quickly for limited CTV impression opportunities.
Predicting advertising outcomes with AI
AI is quickly changing the way we predict and optimize advertising outcomes. TV buying and optimization platforms are now using AI to improve ad performance. With machine learning, these platforms can anticipate which ad creatives will produce the best results based on various non-creative factors. These include the context of the ad, the audience’s profiles, the time of day it is displayed, and the frequency of the ad display.
By relying on AI to make these predictions, you can make sure your campaigns are highly optimized for success and deliver more relevant, compelling ads to viewers.
Optimizing generative ads
AI is also driving optimization in generative ads. These personalized versions of the same CTV ad can be tailored to suit individual viewers. By utilizing AI-driven analytics, DSPs can process extensive amounts of data in real time and optimize generative ads to ensure they align with viewers’ preferences and behaviors. This level of personalization is a game-changer in CTV advertising that boosts engagement and delivers content that truly resonates with the audience.
Add AI to your CTV strategy today
Integrating AI into your CTV strategy can help you stay competitive and ensure your ad campaigns are effective and engaging.
At Experian, we’re ready to help you elevate your CTV advertising and implement AI as part of your strategy. Our solutions, such as Consumer View and Consumer Sync, provide valuable audience insights, enhance targeting capabilities, and optimize engagement on TV. Plus, our partnerships with leading media marketing solutions can help you achieve greater success through effective advanced television advertising.
As you incorporate AI into your CTV strategy, you’ll be able to make more data-driven decisions, deliver more relevant content, and reach the right audience at the right time. Explore Experian’s TV solutions and empower your CTV advertising with AI today.
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In our Ask the Expert series, we interview leaders from our partner organizations who are helping lead their brands to new heights in AdTech. Today’s interview is with Samantha Zhang, Senior Data Scientist, and Jim Meyer, General Manager of the DASH TV Universe Study at the Advertising Research Foundation (ARF). DASH is an annual tracking study conducted by the ARF to define and better understand TV audience behavior and household dynamics. What does DASH measure, and how does it help the industry understand TV consumption today? By capturing hundreds of individual- and household-level data points from each respondent in a rigorous and nationally projectable sample, DASH creates a comprehensive picture of U.S. consumer TV “infrastructure” – how America watches. Core elements in DASHElements that create context in DASHTV setsLocation | brand | smartness | service modes | sources DemographicsConnected devices Game consoles |video players | streaming devicesYesterday viewing Daypart | TV/device genre | Out-of-home viewingMobile devicesOwners | sharing usersShoppingOnline and in-store | Exposure to major RMNsInternet serviceModes | ISPs | connectivity by device Streaming audio Streaming TVSVOD/AVOD tiers and sharing | FAST Email accounts and apps Live TV Modes of access | including casting from devices Social media For example, DASH gathers: Data on every TV set, including brand, room location, age, “smartness,” and connection devices and modes Household connectivity and video service data, even in homes with no TV set Internet Service Providers (ISP) and TV service usage, including Multichannel Video Programming Distributors (MVPDs), virtual vMVPDs, streamers (ad-supported and premium), and Free Ad-Supported Television (FAST) channels Person-level ownership and usage of video-capable mobile devices, including smartphones, tablets, and laptops Measures of viewing and co-viewing across dayparts, devices, and services Additional modules covering shopping and retail media networks, streaming audio, social media, email, and apps Broad coverage and granularity make DASH a uniquely robust source of truth for practitioners across the industry, including measurement experts and ad programming strategists. DASH also reports regularly (and publicly) on key industry dynamics. DASH identified a growing segment of device-only viewers – now nearly 9 million households that watch TV, but do not own a TV set – and highlighted the implications of that trend for traditional ratings systems based only on households with TV sets. Households (HHs – million)2025 HHs (M) U.S. penetrationChange vs. 2024 (M)Total US134.8100%+2.7Connected TV (CTV)114.685%+2.1TV (Set)124.292.2%+1.1Device-only8.86.6%+1.6TV-Accessible133.198.7%+2.7 DASH called out the rise in app-based pay TV and proposed a new connection framework that better represents the modern TV world, in which linear and streaming overlap. DASH also defines the universes of households reachable with advertising. This graphic, for example, shows how all ad-supported linear and streaming properties in aggregate define the true scale of TV advertising. While 35 million households (and growing) are reachable only with streaming ads and 13 million (and falling) only with linear ads, most households are reachable with both, underscoring the importance of understanding the “overlap.” Who uses DASH data, and what decisions does it help inform? There are three primary users of DASH, each with its own use cases: Measurement providers, including Nielsen, use DASH to calibrate viewership data, turn household data into persons data (and vice versa) and estimate potential reached audiences–what the providers call media-related universe estimate (MRUEs)–for the calculation of ratings. Not surprisingly, measurement companies were the first to see the value that an independent TV universe study could provide. Media companies, including major broadcasters and streamers, use DASH to add context and color to their ad sales presentations – and to track the measurement providers, whose ratings play a major role in valuing ad inventory. AdTech companies, including Experian, use DASH to create high-value audience segments for activation. The recent accreditation of DASH by the Media Rating Council (MRC) and adoption by Nielsen as an input to its TV ratings have generated interest from a broad range of companies. We are actively pursuing new licensees and partners to make DASH more useful within, and even outside, the TV ecosystem. What does MRC accreditation signify, and why is it meaningful for DASH? MRC accreditation means DASH passed a rigorous audit conducted by Ernst & Young over many months, which validated our methodology, controls, and data quality. MRC accreditation establishes that DASH is an industry-standard dataset. While the service provider normally announces its own accreditation, the MRC took the unusual step of issuing its own release on DASH, announcing the accreditation of DASH for TV universe estimation and endorsing the study for broader, cross-media use. How does Experian use DASH data to build audiences? The segments combine specific TV usage habits and behaviors from DASH with Experian data on demographics, spending, and other contextual inputs to create a fuller view of consumer viewing behavior. They are designed to be valuable to advertisers in many categories and planning contexts – and to be customizable to fit advertisers’ media targets. The segments can be used to: Apply or suppress audiences to improve target coverage across a campaign Better align media and creative Reach elusive but high-value viewers, such as Ad Avoiders Drive valuable consumer behavior Achieve specific advertising objectives What are some practical use cases for DASH-based audiences? Here are some practical use cases for four different kinds of DASH segments in five different advertiser categories. Travel Co-WatchersA couples-only resort uses TV Co-Watching Households without Children to strengthen target reach and ad memory recallA big theme park destination uses TV Co-Watching Households with Children to reach families in moments of togetherness Home Entertainment TV Owners and Brand LoyalistsA premium TV manufacturer uses the overlap of Multi Brand TV Owners and Single Brand TV Loyalist Households to market its newest TV model to its most loyal consumers. Fast Food Screen Size ViewersA fast food chain with a high-impact new brand campaign uses Large Screen TV Viewers to better align the media and creativeThat same fast food chain uses Small-Screen TV Viewers to drive store traffic by increasing exposure of its retail campaign among on-the-go viewers Financial Services Cord Cutters A personal cost management app and a cash-back credit card target Streaming-First Cord Cutter Households to reach young, tech-savvy, cost-conscious consumers Thanks for the interview. Where can readers learn more about DASH? We started work on DASH seven years ago, and it’s been fun to watch it “grow up.” Our partnership with Experian is a big step toward putting DASH to work for advertisers and agencies. To learn more, visit our site at https://theARF.org/DASH or contact us at DASH@theARF.org. Contact us About our experts Samantha Zhang, Senior Data Scientist at ARF Samantha Zhang is a Senior Data Scientist at the Advertising Research Foundation working on the DASH TV Universe Study, with additional research spanning areas including attention measurement, digital privacy, and artificial intelligence. Jim Meyer, General Manager, DASH, at ARF Jim Meyer is general manager and co-founder of the ARF DASH TV Universe Study and managing partner of Golden Square, LLC, which advises media and research technology companies on growth strategy and development. Latest posts
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