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How to Compete in the Streaming Wars—Without Your Own Billion-Dollar Backing

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If you’re not a giant content provider like Disney+, Netflix, or Peacock, how can you expect to stay competitive in the increasingly intense streaming wars for loyal audiences and subscribers? The answer: targeted strategies backed by big data, but without the big spend.

Right now, the top three streaming platforms (Amazon, Netflix, and Hulu) own almost 80 percent of the subscription video on-demand (SVOD) market in the U.S. But subscriber churn hit a record high of 44% in 2021, and shows no signs of slowing down as consumers re-orient their post-pandemic spending habits in the face of rising inflation and a pending recession. Netflix saw its first subscriber loss in a decade in Q1 2022. Despite the now infamous statement, “No advertising [is] coming onto Netflix—period” by Netflix CEO Reed Hastings, the company is widely expected to launch an ad-supported tier by the end of 2022, joining Amazon’s Freevee (formerly IMDb TV) and Hulu’s ad-supported offering.

It’s no surprise that advertising video on demand (AVOD) and free ad-supported TV (FAST), are taking hold as major streaming services fight to meet customer demand and compensate for plummeting SVOD revenue. The companies that represent the other 20 percent of the streaming market today—including digital streaming apps and linear providers moving into OTT—are as eager as ever to seize their share, and the current environment presents a unique opportunity. Amid consumer demand for more choices, fragmentation of revenue models, and more accessible data analysis tools, the Davids of the market stand a better chance than ever in battling the Goliaths. There are three tactics that pave the way to victory.

1. Prioritize Content ROI

Would a channel for unicorn enthusiasts make money? What about 24-hour streaming tea parties? Or body-building TV in non-English languages? They all have huge potential to lure customers away from the competition, if your content appeals to their passions.

As the global streaming wars play out among industry behemoths and consumers tire of paying for multiple subscriptions, there are plenty of market opportunities to monetize your content. Collectively, the top 10 niche streaming services grew at more than twice the rate of major SVODs last year (74 percent and 30 percent, respectively). Contextualizing this within Netflix’s historically high content spend of $17 billion in 2021, there's a strong argument to be made for outsmarting—rather than outspending—the competition. To determine what that content will yield the best returns, you have to mine the data. Consider: What are the consumer segments, social phenomena or cultural obsessions that aren’t being served? What genre could use a 24-hour home for hardcore fans? Is there a regional play that could appeal to new audiences?

High-level correlations such as demographic genre affinity are no longer sufficient to drive ROI in a market where audience content preferences can change by the moment; anything from local weather to consumer moods can impact demand. Operational agility, including real-time data analysis, is key to finding the right audience for the content you own, or are considering investing in.

Market leaders like Amazon have sophisticated algorithms to understand and predict such phenomena, thanks to massive data science teams and integration with data sources spanning consumers’ online shopping behavior to payment profiles. But the industry is shifting; powerful artificial intelligence (AI) tools are available to organizations of every size seeking to measure and optimize content performance.

These high-tech tools can empower every part of the company to make better decisions for future growth, from content licensing to product development and marketing. Data is no longer the exclusive realm of data science teams; it is the lifeblood of successful companies.

2. Meet Customers Where They Are and Know Where They Are Going

There’s no single answer to where, how, or to whom you should make your content available; and the right answer today may not be the best answer next year. In fact, given the diversity of consumer behavioral trends—from boomers watching cable TV to Gen Zs scrolling through short-form, user-generated social videos—diverse distribution and monetization strategies are often necessary.

Content affinity is only one part of the picture. What about your audience’s fluctuating price tolerance or potential lifetime value? Some consumers are loyal to subscription platforms. Today, more are not. Rather than waiting for their subscription streaming service to offer a movie, some viewers are opting for transactional video on demand (TVOD) offers that allow them to purchase the film with the tap of a button the day of its theatrical release. Others are willing to trade an uninterrupted viewing experience for intermittent ads if it means catching the latest season of their favorite series free of charge, whether or not they plan to upgrade to a paid subscription to gain full access to that streaming platform’s library.

Targeting the right audience with the right model enables you to fine-tune your revenue optimization strategy, but it requires the ability to keep close tabs on changing viewer behavior at all times. Until recently, that insight was only accessible to companies that could invest in costly analytics tools and the extensive data science resources required to extract value from them. The rest of the market was left to make high-stakes strategic decisions based on general trends; networks that saw the writing on the wall as audiences cut the cord were early to ink deals with vMVPDs, while streaming platforms facing churn blasted every free trialist with the same subscription upgrade offer at the same time.

In the new era of plentiful data and accessible analytics tools, deep audience intelligence guides better customer-engagement decisions. Like content ROI, customer lifetime value can be precisely measured and even predicted. Customer retention is an obvious application; rather than merely predict which segments are likely to cancel and invest marketing dollars in retaining them, streaming services can identify which tactics will yield the greatest long-term revenue. Allowing a customer to churn may seem unthinkable, but if they are more likely to engage with a free ad-supported offer that yields even higher revenue than subscription fees, it’s the better choice.

Finally, there’s enough data at your disposal to begin understanding those tradeoffs and making the smartest choice for your bottom line.

3. Drive with Data, Steer with Technology

What’s a title in your library worth? It depends on the distribution platform, audience, and even time of day. No human can easily run such calculations 24/7. AI and machine learning can’t solve every challenge facing media companies, but they are very effective at scaling analysis to better monetize content.

Data can give streaming platforms a clear view into the potential value of assets, customers, distribution partners, and revenue models. The benefits are far-reaching: smarter content acquisition and production investments, higher ROI marketing promotions, and more profitable distribution partnership agreements. Unlocking those benefits requires powerful technology that’s finally becoming available at a cost mid-market companies can bear.

Netflix didn’t become the dominant force it is today solely through the advanced algorithms that are now their hallmark. They first focused on mastering supply chain logistics in order to displace competitors in the rent-by-mail DVD space. The lesson here is not to emulate everything Netflix does; as their recent challenges remind us, retaining market share isn’t always a winning battle. Rather, it reveals the importance of capitalizing on available technology at the right moment to gain a head start in highly competitive markets that are prone to disruption.

So, what other surprises are in store for the media and entertainment industry? That’s a data question, and the companies best equipped to answer it have never before included so many emerging and mid-sized players seeking a fair fight in the streaming wars; or in the case of players early adopting these technologies, and unfair advantage against those who do not.

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

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