Does Streaming's Future Success Depend On Discoverability?
As streaming has grown in demand and popularity over the last several years, 一个问题已经开始形成. But don’t get me wrong, it’s a good problem: too much content. 这不仅仅是单一提供商的内容. Netflix, Disney+, WarnerDiscovery, and Peacock all have deep and rich libraries of content. But it’s the combination of services and their deep libraries that create the underlying issue.
我们来算一下. If the average consumer has three streaming subscriptions and each streaming platform has 50,000种图书, the amount of available content is almost unimaginable. How does someone figure out what to watch–not only in a single service, 但是在这三个服务中?
Solving this problem will take a significant amount of effort. In fact, many streaming operators already provide some sort of recommendation engine. But that does not address the bigger picture of how content gets recommended across service providers. The answer, though, might not be one of functionality, but of data.
The core issue with unifying content discovery across service providers is that each service provider may represent title metadata differently, 这给搜索带来了一个核心挑战. 如果用户输入了一组特定的条件, 服务之间的元数据是不同的, 它不会返回最合适的标题. But searching for content is only half the battle. 在很多情况下, 观众可能不知道自己想看什么, 在这种情况下, the service providers must recommend content to them. 这就把我们带回到元数据. 如果提供程序之间的数据不同, then each service is recommending content differently, based on their own algorithms and their own approach. The result with this problem of search and recommendation is that viewers may ultimately reduce their streaming services to those that can more adequately provide them with content best suited to their needs and wants.
To solve this problem, then, requires a two-part solution. 第一部分是数据标准化. 一家科技公司, Vionlabs, is attempting to do this but with an added twist: relating the metadata to viewer sentiment. 通过逐帧分析内容, they can determine the emotion to which that frame–and ultimately the content–is best attributed. This allows them to more granularly categorize content for optimized recommendations. With this kind of sentiment analysis baked into a standardized set of title content (and technology that content platforms can use to do their own analysis), 建议可以更精细地调整. And if every content provider is using the same kind of classifications and metadata, recommendations are the same across all platforms.
The second part is for streaming platforms to open up their content library for search. 当然, 这已经开始发生了, 但在某些情况下, content pages are behind paywalls and access credentials, making them impossible to include in search results. 最终, 这没有多大意义, because if the content 信息 was exposed in search results, 它可以说服新的用户加入.
当然, the lack of content recommendations and search isn’t going to stop streaming from growing, 但它会改变观众的行为. 而不是三个, 四个, 或者五种服务, 他们最终可能只有两个，甚至一个, meaning it will be difficult for services to find and retain subscribers. 随着营销成本的上升, 内容生产可能受到影响, resulting in less unique and original content over time.
The future of streaming is about unification built on top of a single open standard of content metadata. Right now, it’s a matter of seeing the forest for the trees. Individual streaming operators see only themselves and their content (the trees), but neglecting to see their services from the viewers’ perspective (the forest) will ultimately keep industry conflict high and viewer satisfaction low, inhibiting the complete transition from broadcast to streaming.
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