AI: The Secret Weapon for FAST Channels Competing in a Crowded Market
AI Use Cases
The landscape of Free, Ad-Supported Streaming Television (FAST) channels has significantly shifted in the last 12 months. Once dominated by niche content providers, the market has witnessed a surge in activity from major studios and broadcasters. This influx of premium programming has brought a new level of competition, forcing FAST channels to adapt and optimize their offerings to stay afloat.
Source: 3Vision FAST Tracker (December 2023)
Of the more than 1,600 unique channels live on major U.S. platforms in March 2023, over 40% have since been dropped by at least one, while 16% are no longer live on any platforms altogether. This increased channel churn suggests that the FAST market is maturing quickly and moving into a new phase where data-driven efficiencies will be key to the survival of any channel.
Source: 3Vision FAST Tracker (March 2024)
This is where Artificial Intelligence (AI) steps in as a game-changer. By leveraging data and machine learning algorithms, FAST channels can gain valuable insights into viewer behavior, personalize content delivery, and increase engagement and advertising revenue.
Here's how AI can be the secret weapon for FAST channels competing against the content powerhouses in a saturated market.
Automating Channel Schedules
Traditionally, channel scheduling has been a manual process, relying on past performance data and gut instinct. More recently, companies have utilized software to automate scheduling and distribution. The next evolution is applying AI to analyze vast amounts of viewer data, including time of day, demographics, and content preferences, allowing for the creation of dynamic schedules that cater to viewers in real time.
According to research conducted by Parks Associates and SymphonyAI, almost 70% of content executives report that they evaluate data for each distribution service separately. AI can combine data sets, such as peak viewing hours for specific demographics on various platforms, and schedule content accordingly. This data-driven approach ensures that viewers are presented with content they are most likely to engage with, ultimately leading to higher viewer retention.
Ads are the primary source of income in FAST, so viewing hours will remain one of the most important KPIs for evaluating channel performance. When competing against the major studios and broadcasters, channel owners must look to maximize audience retention using these innovative technologies.
Optimizing Ad Placements
AI can also be a powerful tool for advertising, the lifeblood of FAST. Analyzing viewer behavior patterns can determine the optimal placement of ads within a program, influencing factors like content type, ad length, and frequency.
Specific applications can also strategically place ads within the programming during natural pauses, resulting in higher ad completion rates and increased revenue for the channel. When competing against large media companies that already have strong relationships within ad markets, it is integral that channels optimize their ad performance.
This leads to other potential use cases, such as AI-matched contextual advertising. Machine learning algorithms can dynamically assess the genre and mood of content preceding an ad break, enabling the placement of thematically consistent ads. Think of showing a car ad just after a car chase scene or an ad for chocolates during a romantic movie.
The resulting efficiency gains in ad placement and engagement hold significant potential to enhance the overall effectiveness of channels. Ads placed using AI-assisted technology can improve the matching process by more than 92% and even improve ad recall by up to 22% compared to more manual approaches[1].
Forecasting Streaming Performance
Predicting the performance of newly acquired content can be a gamble for FAST channels, especially when competing with premium content from NBCUniversal, Warner Bros. Discovery and MGM. AI can mitigate this risk by analyzing viewing data and identifying trends. This allows FAST channels to forecast the viewership and potential ad revenue for new content before it's even aired.
With this information, channels can make informed decisions about content acquisition strategies, focusing on programs with the highest potential return on investment. Moreover, AI can inform content strategies by predicting and comparing its linear and VOD performance and estimating its success on certain FAST channels and platforms.
With the currently unpredictable economics of the FAST market, channels must pick their opportunities wisely. AI allows players to create effective targeted distribution strategies and remain successful in a crowded market amongst giants.
The Future of FAST Channels
The integration of AI represents a significant leap forward for FAST channels. By harnessing the power of data and machine learning, FAST channels can compete effectively in a crowded market, optimize revenue streams, and ultimately deliver a superior viewing experience for their audience. As AI technology evolves, we can expect even more innovative applications that further revolutionize the FAST channel landscape.
While the logical hype around AI has dominated headlines over the last few years, we have yet to see large-scale adoption in the FAST space. However, this will only be a matter of time as understanding the possibilities of highly targeted AI solutions becomes more widespread.
[1] https://www.adweek.com/sponsored/why-contextual-ai-will-shape-the-future-of-advertising/; https://digiday.com/sponsored/what-the-future-of-contextual-advertising-looks-like-in-a-privacy-first-world/
[Editor's note: This is a contributed article from SymphonyAI. Streaming Media accepts vendor bylines based solely on their value to our readers.]
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