Connected TVs have revolutionized video consumption and transformed the digital advertising landscape. And as we’ve seen over recent years, an increasing number of streaming providers and broadcasters are turning to advertising to support growth.
However, to maximize this revenue stream personalization of ad content is key. When ads are tailored to align with the viewer’s preferences and behavior, they resonate more deeply, driving higher engagement and conversion rates. This benefits broadcasters by strengthening their appeal to advertisers, who naturally want maximum return on their investments. Yet personalization in advertising remains a huge challenge.
Ad personalization on CTVs relies heavily on the use of tracking cookies, but growing privacy concerns, regulatory shifts and a widespread aversion of third-party cookies are making this model unworkable. And so, the industry needs a new advertising strategy—one that respects user privacy while still delivering effective ads. Many are turning to contextual advertising as a potential solution. While this advertising model is itself not new, what is new, is the use of AI to significantly enhance it, making it much more powerful and effective.
Unlocking Contextual Advertising’s Potential
Rather than relying on personal data, contextual advertising works by tailoring the ad to match the content. As the name suggests, contextual advertising, it’s all about context. By matching ads to the content being viewed, contextual advertising aims to deliver an enjoyable ad experience that feels natural to the viewer.
For instance, if the viewer is watching sports content, then ads showing sports clothing brands might be selected. This alignment enhances the likelihood of viewer engagement, because the ads are relevant to the immediate context of the content they are watching. Importantly, this strategy also aligns with evolving privacy expectations, allowing broadcasters to provide personalized experiences without intrusive data collection.
While contextual advertising can be effective on its own, AI takes it to the next level by analyzing video scenes in incredible detail. AI can be used to identify key elements such as mood, setting and pace, as well as objects in the frame, to create a precise match between ads and content on the screen at any given moment.
For example, if a scene shows a person on a sandy beach heading to the sea to surf, with the power of AI, contextual advertising tools may suggest advertising for surfboards, watersports equipment, beach wear, and outdoor adventure activity vacations. Or if the scene features a person chopping fresh vegetables while preparing to cook a meal, suggested advertising may include kitchen knife sets, fresh vegetable delivery services, or healthy meal subscription service kits. Similarly, if the content shows a person practicing yoga, contextual advertising tools may suggest ads on yoga equipment, fitness apparel, wellness supplements, or healthy living and wellness apps and services.
Engagement = Conversion
The reasoning behind this approach is that if the viewer is already watching content that features the things being advertised, or similar, it’s reasonable to assume that they may appeal to or interest the viewer to some degree. If ads are delivered that the viewer is more likely to be interested in and engage with, this leads to higher rates of conversion.
Additionally, while standard contextual advertising works to identify objects in the scene, AI can analyze the content at a much deeper level. It can help determine what mood the viewer is in so that ads can be placed that they will be most receptive to at that moment. This enables streaming providers to select ads that resonate with a scene’s emotional tone, creating a more immersive and engaging experience for the viewer.
Pairing contextual advertising technology with prediction tools can also help video providers to optimize ad placement for maximum impact. These types of tools can measure conversion rates enabling video providers to track viewer engagement patterns to identify when viewers are most attentive or most likely to convert.
Shaping the Future of CTV Advertising
By incorporating AI into contextual advertising strategies, broadcasters can deliver hyper-personalized ads that have higher relevance to the viewer, at precisely the right moment when the viewer is most likely to take action. This combination of relevance and precision is reshaping the way media companies approach advertising, ensuring an enhanced viewing experience, improved conversion rates for advertisers, and increased ad revenue for service providers.
This approach offers broadcasters a solution to a major challenge: how to deliver impactful, personalized ads without relying on personal tracking data. As such, AI-powered contextual advertising has the potential to transform CTV advertising, and it is only going to get better as AI technology evolves and improves.
As the reliance on advertising to support growth intensifies across the media landscape, the adoption of AI-driven advertising solutions will become a critical differentiator. Broadcasters and video providers who invest in these technologies now will be well-positioned to lead the industry into a new era of smarter, more effective advertising.
