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Personalization Is 更多的 Than What You Think It Can Be

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这些年来有很多关于 making the streaming video experience more “personalized.” 但这到底是什么意思呢? 在很大程度上, personalization has been about content recommendations. When the viewer can come to the streaming platform and see content that might be more relevant to their likes or behavior, it can feel like the platform is more personalized for them and offers a different experience than another viewer might have.

Personalization has been applied to elements within the video experience as well. For example, ads are targeted based on demographic or
地理数据. These can be within the video asset itself or in the area surrounding it. 但视频个性化是关于修改
视频本身适合观看者, 比如换颜色, 切换图像(例如, 特定品牌), 甚至修改
the video flow itself based on a user’s specific predilections.

But that vision has faltered over the years—stumbled, if you will. 在过去的15年里, I have seen plenty of attempts at dynamic image recognition (through sequential frames), which have just failed to materialize in a meaningful way. Oftentimes, they required player plugins or other proprietary technology.

作为执行董事 SVTA, I get to see a lot of up-and-coming technology providers, 尤其是作为我们资助项目的一部分, 哪家公司主要关注创业公司. 其中一家公司, 注入的视频, has demonstrated the next phase of personalizing the video experience:
dynamically replacing elements of the video itself.

注入的视频 使用的组合 缝合 and just-in-time rendering to deliver customtailored experiences to the viewer. The platform utilizes segmented streaming and deduplicates segments that are common for multiple users, thereby enabling audience segmentation and personalization at a sustainable scale.

Let me distill that down to a use case: enterprise marketing videos in the pharmaceutical industry. 为了提高观众的参与度,
视频不可能是放之四海而皆准的方法. 以及更高层次的参与, such as watching the entire time and even clicking on a call to action, can equate to medication uptake: the viewer talking to their doctor about a certain medication and even asking for it to be prescribed.

But this kind of engagement requires tailoring the messaging to the viewer. So imagine that these videos are animated explainer videos.
Rather than having a white man deliver the message to a Black woman, a Black woman doctor is the one delivering the 信息.

当然, this can equate to hundreds or even thousands of different variations, which would be cost ineffective to produce manually. 注入的视频’s platform allows this to happen dynamically, leveraging video “templates” (which really just represent the words and the flow) to create the different variations and stitch them together in real time based on data about the viewer. This can possibly leverage generative AI (when using digital avatars). The different variants can be created around B-roll or other filmed footage produced by an agency. Think about a car model being featured with a different color depending on the viewer.

Studios could make use of this as well by allowing their viewers, through a set of clickable filters in a streaming player, 删减:删减电影中的元素. 不要裸体? 查看者可以点击过滤器, and a platform like 注入的视频 would stitch in alternate frames (which may include objects blocking the questionable elements).

随着生成式人工智能的进步, just-intime代码转换, SSAI缝合, 以及其他流媒体视频技术栈组件, companies like 注入的视频 are demonstrating that the true vision of video personalization—changing the video content itself—is finally at hand.

Go ahead, enterprise video marketers and movie studios—take my data. If it means I get content dynamically built for me, it’s well worth
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