How AI Is Bringing Intelligence to TV Screens
Artificial Intelligence (AI) has been creating quite a stir across all industries, including the Connected TV (CTV) realm. In fact, it has already switched from being an attribute of siloed players to become something most actors dip their toes into.
While AI-driven data mining helps build predictions and foresee peoples’ attitudes to video content, machine learning algorithms segment viewers according to their habits. With such a slew of capabilities, no wonder AI has received a warm welcome in the CTV space.
Streaming Quality and Compliance Management
One of the most widespread use cases of AI adoption in CTV is in its ability to determine the optimum video quality per user depending on the network speed. Like in the case of Netflix’s smart video compression technology, AI then alters video settings to reduce the chances of annoying content buffering. This mines additional value for users who get a pleasant viewing experience with no interruptions.
Another important contribution of AI to the world of streaming is that it assists a great deal in quality assurance and control. They include humble checks to identify whether media content is aligned with technical parameters as well as a more profound moderation of compliance with local age restrictions, privacy legislations, and the like.
Hence, the technology can flag and remove off-putting elements from videos, such as scenes containing cigarettes or drug abuse, violence, etc. Ultimately by doing so, AI kills two birds with one stone, as it prevents viewers from being exposed to unwanted content and protects brands.
According to eMarketer, 39.4% of Americans already use AI-empowered voice assistants, and the technology is growing more popular every day. Having said that, in the CTV environment, speech recognition is mainly used for controlling the viewing via Google Assistant, Amazon Alexa, Apple Siri, Samsung Bixby and so on, built into streaming devices or smart TVs.
Although the technology still has some limitations and raises privacy concerns, it gives impetus for CTV consumers. Provided there’s a buffet of video content for viewers to browse through these days, enabled voice commands to offer sheer convenience.
Firstly, voice assistants eliminate the need to use remote control, which is more hygienic and essentially quicker. Secondly, they encourage human-like interactions via voice. Finally, they drive personalization, especially when users don’t mind interlinking their accounts and syncing data in order for AI to learn and evolve.
Another key aspect of AI deployment in CTV is programmatic ad buying and selling. This type of auction is expected to account for 54% of all CTV transactions in 2021, as per IAB. It automates matching publishers’ ad placements with advertisers’ campaign objectives to fuel the best deals. Additionally, it involves the complex use of machine learning for audience hyper-segmentation based on behavioral patterns.
Programmatic ad buying offers lucrative benefits to marketers by allowing them to break free from gross rating points (GRP). Moreover, it ensures a more intelligent and pinpoint way of placing ads in front of the right viewers at the right time. As for publishers, who are typically wary of impression scarcity, programmatic transactions are more cost-effective. This kind of ad buying is determined to sell all available ad spots to the most suitable buyers and minimize waste.
What’s more, automatic content recognition (ACR) with AI under its hood became an additional layer enhancing ads’ relevance. The technology is often embedded into streaming devices and smart TVs. It offers bespoke contextual targeting coupled with a cross-device reach. A good example here would be Roku that uses its self-accumulated ACR data to display ads to those consumers who have not seen them via linear TV. Samba TV, in turn, utilizes ACR to retarget mobile device users based on their IP addresses that would normally be the same as their smart TVs’.
AI’s key input into CTV’s development lies in it stemming the flow of default content libraries. Thanks to data-driven analysis, OTT services are capable of delivering addressable recommendations for their audiences.
With personalization in mind, Netflix, Hulu and Amazon Prime monitor all customers’ journeys down to the smallest details to gain a wealth of new ways to fine-tune content. For instance, they offer tailored trailers based on interests in certain actors, genres, reviews, and countries of origin. So, if a user has recently finished binge-watching The Queen’s Gambit with Anya Taylor-Joy on Netflix, this user is likely to be offered to watch Peaky Blinders with the same actress on the TV show’s cover.
Though it used to be the case, customized recommendations are not the prerogative of streaming giants with the deepest pockets anymore. To meet the needs of affluent users and stay ahead of the curve, OTT services of all calibers adopt innovative practices and experiment with new technologies.
Less in the robots’ embodiment and more in the form of machine learning algorithms, AI has penetrated our lives and so far, it’s decidedly friendly. It is poised to offer tremendous advantages to businesses working in CTV. AI excels where human effort is too expensive, time-consuming, or even inapplicable, as it can absorb information to discover meaningful patterns with minimal supervision and at a lightning speed. Thus, AI at this stage is definitely not about supplanting people, it’s about supporting them.
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