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A Free Ad-Supported TV (FAST) Shakeout Is Coming. Deploy Your Data to Survive.

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Somewhere out there, a left-handed golfer is happy. After a few weeks of streaming their new favorite channel, Left-Handed Golf News, they’ve shaved 10 strokes off their average.

The success of one left-handed golfer may not necessarily bode well for the free ad-supported television (FAST) media market, however. The number of FAST channels in the U.S. alone doubled to more than 1,000 in 2021, and revenues are expected to double again by 2023 (to the tune of $4.1 billion). Compared to traditional linear television, the barriers to entry for FAST are low. That’s an appealing proposition if you’re trying to digitize your pay TV offerings or find an audience for your niche content. 

With this superheated expansion of entertainment options, the FAST market is headed for a shakeout in the near future. People only have so much time and attention; by some estimates, audiences in the developed world spend as much as one-third of their waking lives watching video. The laws of supply and demand dictate that as FAST programming proliferates, companies that have flourished in recent years will struggle to stay afloat if they can't maintain adequate viewer attention. 

Media companies that deploy their data can weather these disruptions, and even anticipate them before the industry changes under their feet. But it requires sophisticated analysis and prediction, ideally enabled by artificial intelligence (AI), to identify which content is likely to thrive and which will disappear in the rough.    

Free Ad-Supported Television Is Growing

The recent explosion of FAST is breathtaking. Successful providers such as Pluto TV and Xumo, are adding millions of viewers each year. It’s the ultimate antidote to both cord-cutting and subscription fatigue; consumers can choose from a multitude of linear viewing experiences at zero cost, with zero commitment.

That growth produces winners and losers. Just look at the more mature subscription video on demand (SVOD) space: Netflix and Hulu, which accounted for 75% of OTT subscriptions in 2019, have seen their dominance decline as HBO Max and Disney have invested heavily in streaming content. As of December 2021, Netflix and Hulu’s collective market share had dropped to just 38%; in the last two years, they made up only 9% of growth in the sector. 

Whether via FAST, SVOD, or over-the-air, all media companies are competing to turn eyeballs into revenue. But many are struggling to turn the corner. A recent study from Streaming Media and Unisphere Research found that 67 percent of OTT services (including FAST) attract fewer than 1,000 monthly viewers, and over one-third have annual revenues under $100,000.

That’s not a sustainable business model. Still, many remain optimistic. More than half of the companies surveyed by Streaming Media and Unisphere predict growth exceeding 25% over the next 18 months.

Still, the shakeout is coming for companies that lack a data-driven growth strategy to help them navigate this perilous landscape. Increasingly fierce competition for viewers requires forward-looking analytics that ensure your FAST investment pays off in the form of more viewers and increased revenue. 

Data Is Moving FAST 

Anyone operating in the media business knows that simply keeping your books is easier said than done. Most organizations embracing FAST already have established revenue streams; the majority are accustomed to straightforward cable and broadcast licensing revenue, which is reported monthly on a per-subscriber basis. By contrast, FAST requires tracking revenue per title across multiple platforms, monetization models, partners, and regions. For organizations that have not previously dealt with direct-to-consumer (DTC) distribution, FAST also brings a wealth of new audience data to contend with. It’s difficult to capture the whole picture in Excel, yet that’s exactly how many businesses operate today. 

The first step to deploying your data is to normalize it. Consider the seemingly simple example of how you label season one, episode one of your most popular series. The difference between “S1E1” and “S1 E1” is a single space, but such a minor inconsistency can confuse both humans and machines attempting to correlate and analyze their data. 

With cleansed and normalized data accessible via a single source of truth, be it a data warehouse or software platform, you can begin to track how various titles perform. If only it ended there. But content performance is just one aspect of your overall revenue. FAST data sets also include valuable audience insight that can reveal new revenue opportunities. Whereas traditional over-the-air content is delivered at the direct market area (DMA) level, FAST delivery is specific to households and individuals. Understanding content affinity – who’s watching what, and why – enables lucrative personalization tactics and business strategies.

Manage, Track, Predict, and Grow

It’s only through such detailed and accurate accounting of historic data that organizations can pivot toward predictive analytics. A genre that performs well with a specific demographic can represent significant revenue potential in the form of ad dollars and conversion to paid services. Predictive insight improves business decisions ranging from the content you invest in, to the timing of your promotions.

The pivot from reactive to predictive strategies will determine who survives the FAST shakeout. It’s why easily integrated data tools are an essential piece of the puzzle. Artificial intelligence systems trained on media-specific data can quickly detect patterns and anomalies that humans miss, revealing insights that power profit. Marketing, product, and content teams can more quickly take advantage of these insights in the moment.  

Suppose 40-to-55-year-olds in Australia are especially engaged with Friday night news. What’s driving it? How can you replicate that success elsewhere? Suppose that same segment is trending toward disengagement. What’s changed, and how can you pull them back in? Now scale that scenario to include every channel, region, and rapidly changing customer behavior. Given enough time and skilled data analysts, you’ll get the insight you need. But if you want it in time to capture the opportunity (but lack the budget for a massive team of data experts), you need AI. 

AI can also help you test various scenarios, solutions, and ideas. It bears repeating: FAST is only one of multiple revenue streams in most media organizations today. A portion of your FAST viewers are primed to become loyal customers, perhaps even paying subscribers. Do you know which ones? To seize the revenue opportunity, you have to know when and how to win audience attention in real time and over the long term.

Breaking Through the Crowd 

When high-definition television hit the market, the existing cable infrastructure didn’t have the bandwidth to carry all those pixels at once. Engineers had to create dynamic workarounds. As streaming began its ascension, the challenge was how to make these new options easily accessible through one device. Enter connected TVs (CTVs). Today, 34 percent of global households have one. By 2026, that will rise to 50 percent

How can Left-Handed Golf News find the 2.43 million left-handed golfers in the United States via CTV, and what might an advertiser pay to reach them?

The great challenge in the CTV era is how to connect with your potential audience sooner, and more frequently, than the competition. When a consumer can literally call up thousands of content options using with a remote, your FAST content has to break through and rise above the others.

Though standard grid guides remain the tool of choice for many platforms and cable channel surfers, they are no longer sufficient to command audience attention. Leaders in the streaming space are developing interfaces that can predict which shows will match the interests of particular audience members and generate revenue. FAST providers should prepare to leverage data to reach CTV viewers the same way SVOD providers apply content recommendation algorithms. Take hero content, for example. The clip you select will be displayed just pixels away from your competitor’s. Predictive insight gives you the advantage when it comes to selecting the content to attract the right viewers. 

Savvy data strategy enabled by AI gives you the power to pinpoint the content, preferences, and trends that will win over loyal viewers who feel like your FAST channel was created exclusively for them. In the media industry, the organizations that make smart bets are the ones that survive the shakeouts. FAST will be no exception. 

[Editor's Note: This is a contributed article from Symphony MediaAI. Streaming Media accepts vendor bylines based solely on their value to our readers.]

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