Executives in the media and entertainment space are working hard to keep up with the Joneses—Netflix being the Joneses, in this case. The merger of Warner Bros. and Discovery, Amazon’s acquisition of MGM, and the growth of Disney+, Peacock and other streamers are attempts to consolidate enough market heft to compete against Netflix, and each other.
That heft comes from subscribers, which means the same executives working to grow their subscription numbers are also thinking about how they can maintain those numbers when they know churn is already happening as more folks put the Covid-19 pandemic behind them, return to normal life and reassess how many video streaming services they want to keep paying for. M&E companies need content—good quality content, and a lot of it—to keep and grow their subscription numbers.
Three Routes
Executives have three paths to consider taking as they compete to see who becomes a market leader in the post-pandemic economy. They all involve content, of course. They also involve artificial intelligence, an essential, often unsung tool that supports media and entertainment companies’ subscription growth.
The first of these paths is to invest in good, original content. From House of Cards to Fleabag, we’ve seen the success of this approach. We’ve watched in recent years as streaming services have given traditional Hollywood studios a run for their money at the Oscars. Those kinds of award-winning, much-discussed shows draw in new customers.
I’ve watched AI facilitate this renaissance, helping M&E companies develop valuation strategies so they know the kind of original and distributed content viewers like, and want, the most. AI manages the massive data flows necessary to compile average revenues per user, average revenues per content and the many indicators, like actors and genres, that are necessary to identify new audiences and suggest content to them. The right AI modeling can help limit the risk of releasing original content that receives poor viewership data and can contribute to customer retention.
But original content has its limits. Films and television series can be extremely expensive to produce. Only one out of many becomes a blockbuster, meaning that programming budgets are full of loss leaders. The result is that streamers never produce enough to meet demand. Original content is important, but it won’t necessarily keep subscribers.
Another option is content licensing—engaging with content owners and signing distribution deals for specified periods to stream a specific volume of their content assets on their platform. AI plays an important part in these licensing deals, helping to determine the content that will draw the most subscribers. It also supports back-office needs, providing the insights and functionality that are needed to manage the deals. But this approach also has its limits.
The third and final path is the one that we’ve seen a lot of lately: Buying more content that is relevant to more subscribers. Streamers with access to sophisticated AI data analysis know the kinds of content that their subscribers want—they just have to purchase it. It’s a more cost-effective and immediate way to solve the subscription growth/loss problem.
MGM and its Epix television network will give Amazon rights to over 20,000 films, television series and other content for its Prime streaming service. (Netflix, in comparison, has 15,000 titles.) Sheer numbers are only part of the story, though. Warner Bros. Discovery will marry HBO Max’s prestige dramas with the Discovery Channel’s documentaries, a nice combination that provides audiences with complementary content.
Disney bought 21st Century Fox in 2019 with the same synergies in mind. Comcast bought Sky to bring together American and European programming. And Univision bought Televisa to create a consolidated Spanish-language media titan. Many of these newly combined companies are especially interesting because they didn’t originally set out to focus on video streaming—and yet, they’re aggressively competing in that space.
That prompts the question: how are these giants going to sell subscribers on their content?
The answer, like many answers in the tech world, comes from data.
Managing the Data
Even before this period of mergers and acquisitions began, M&E companies maintained deep data lakes of viewing habits, user and payment info, support tickets from CRMs, quality of experience, and lifecycle marketing campaigns—but they still struggled with having strong data management strategies in place to organize all of that information.
All this data creates troves of insights for streaming companies. But companies lack the tools to be able to consolidate it, analyze it, and take action against it. A specific example is marketing teams lacking the tools to conduct proper A/B testing on actionable data that their data scientist teams produce. Often, their data comes from different silos that aren’t integrated. Even if it’s sorted, manyM&E companies lack the solutions to create actionable intelligence from this data.
AI, in contrast, can tackle those problems. Data management through AI leads to insights in real time, unifying disparate strands of data and information and creating more opportunities to increase revenues as the market shifts. Every M&E company already knows that AI is the best way to assign value to content, original or not. That makes it easier to produce, acquire, or license programming that will generate subscriptions and reduces the risk of delivering unpopular shows that will drive folks away.
The pace of mergers and acquisitions in M&E has made one thing very clear: The arms race for the best content is on. Harnessing the latest innovations in AI to manage data and uncover impactful insights is the best way to meaningfully grow your content libraries.
Andrew Thompson is Senior Vice President of Sales & Marketing at Symphony MediaAI.
