How AI & ML Can Address Emerging Streaming Monetization Challenges
Learn more about AI and streaming at Streaming Media East 2022.
Read the complete transcript of this clip:
Eric Bolten: We work very closely with our entire customer base to try to attack the problem sets that are--to use that industry jargon--a lot of pain points. But within that, the thing that you don't trust is the thing we're trying to actually solve for. We're looking to find correlations and patterns that, if I pulled up one of our top engineers, they could look through a set of data and say, "Well, this means this and this correlates to that, and this is why this happened."
How do you do that at scale? And how do you bring those things up so that people can have one extreme data visualization to look at things in multiple dimensions that you would be impossible to look at. We pull a hundred different dataset types that we're trying to just harvest and bring together.
And while we're solving our world in this larger ecosystem, I think you can hear the diatribes. So we want to solve today's problems of, "How do I have broadcast streaming, and video in general, maintain a certain level of quality?" But beyond that, how do those things intersect with more future-setting monetization and cost goals of any organization? And I think that's a journey and, predictive versus prescriptive versus autonomous. I completely understand in a sense, but you're going to have the idea that someone's watching a piece of programming and they're gonna do what television doesn't like--change the channel, which today is not how that exactly works. But how does one maintain that audience interaction through the varieties of programming available? You are gonna have data available that tells you what that person is, what their demographic is.
Nielsen ratings ran the television is industry forever. I know that the Weather Channel and other things is look at much more smaller market segments that would break the United States into much tighter areas. How does Discovery or any other client find that I can say, "I know what your weather is. I know what your sports were." And all of that has to come together to make a compelling video experience. And I think that when we talk to our clients, we accept that this is an ongoing worki-in-process. AI and ML is not, as you held up your little speaker, this mythical black box that waves, pixie dust on it and goes away. It's an ongoing evolution of what the technology that was available and is now being applied into the media to entertainment.
All too often, the monetization discussion revolves around a simplistic binary that expands only slightly on the old ad-supported broadcast model for home-based media and entertainment: subscription vs. advertising. Savvy publishers, rightsholders, and streaming services see a more nuanced landscape. Gamification, interactivity, merchandising, and direct-to-consumer apps let both publishers and advertisers super-serve fans with content that goes beyond live linear or VOD.
The uses for artificial intelligence (AI) and machine learning (ML)—from text identification to contextual advertising to cultural sensitivity—are multiplying. Here's a look at some of the most compelling offerings on the market today.
Zixi Head of Product Tim Baldwin discusses Zixi's approach to live linear over IP in this clip from a Live Streaming Summit panel at Streaming Media West 2019.
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