Measuring audience reactions in more detail than is present today will be a big part of the future of streaming video. To that end, I predict that streaming video services like Netflix, Amazon, Disney+, and YouTube will display an option to use emojis to react to streaming videos in real time within the next few years, if not sooner. These reactions will be tied to a time stamp when you click, and collected by streaming services as data points. Your reactions and the reaction of others may even appear on your screen as you watch. The interface on Netflix might look something like this:
This trend will first allow content hosts like Netflix, Amazon, YouTube, and Disney+ to see how their viewers respond to their content in real time with emojis. Eventually hosts will share this data with creators to optimize content creation.
The data generated from this technology will shape how video content is produced, and give everyone more data on how content is being consumed.
The Current Statistical Limitations
The current viewer statistics across most platforms are largely limited to total views, how long a person streamed a video for, and demographic information for the viewer. These statistics are valuable, however, they don’t tell the whole story behind a user experience. Currently there are very few ways to measure how successful specific jokes or emotional story beats are landing with audiences across specific demographics.
So, for example, Netflix may know that the TV show ‘Breaking Bad’ got X number of viewers per episode, and Y amount of people 22-30 years-old watched each episode all the way through, but Netflix currently does not have a way of measuring what makes audiences stop viewing. They also don’t know what keeps people viewing up through the end of an episode. Do they stop because they find a particular storyline or character boring? Are they more engaged in episodes that focus on one character over another?
In the future of streaming video, generating data using this reaction/timestamp model will be a way for streaming services to ascertain that information and so much more.
Examples Of Benefits Of Reaction/Timestamp Model
- A streaming services like Netflix can compare actors to the emojis that come up during the time stamps they are on screen. A comedian getting lots of laughing faces would be a good indication that their jokes are working, and you can see which jokes are working based on the time they appear. Netflix could then use that information to continue publishing work from comedians with positive reactions and lots of views, while avoiding working with comedians whose material does not generate audience reactions.
- A streaming service like Amazon can compare the age groups that leave laughing emojis against the same comedian’s screen appearance times, noting which demographics react across age, location, race, gender, and all the other data the streaming platform has about their audience. They can then use that data to market comedy specials to specific demographics that have already demonstrated interest in that comedian’s work.
- A content creator can use this reaction/timestamp data to see trends surrounding which parts of a production that their audience doesn’t like as well. If a piece of content as a whole gets reactions consistently, except during one scene, that type of scene may be something to consider reworking or cutting entirely in the future.
The future of streaming video will see the creation of more granular information for streaming services and content creators to analyze. As a result, audience members will be able to get more of the content they express interest in, while material garnering fewer reactions will be less attractive to the streaming services.
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