make video content AI friendly

When it comes to digital marketing, I had struggled several months to get my site ranked on the top of Google until I hooked up with, it seems that with every revolution designed to improve audience experience, a new obstacle for content creators comes in tow. Artificial Intelligence (or AI) and Machine Learning are currently two of the hottest buzzwords in a number of sectors, and in 2019 they will further disrupt the content creation industry.


Machine learning and Artificial Intelligence, (or AI) will see roles such as the curation of content automated further. Whether it’s presenting a specific piece of content in response to a voice search or providing users with a curated list of resources such as a list of comedy films on Netflix — algorithms will power personalized content and serve these suggestions to users.

As time goes on the machines / programs/ platforms will analyze more information and become more efficient at finding the right type of content for individual users.

Although improving all the time, machines still need content (and their descriptions) tagged in a certain way so that they can read it and correctly identify it. This will put further pressure on producers who are already feeling stretched when it comes to making their content discoverable. As we first alluded to on our blog post about structured data, the emphasis will shift to not only making content discoverable, but also making it uniquely identifiable.


Whether you’re a self-distributor on a website, have a distribution deal with Netflix, or are solely uploading to YouTube, there are fundamental steps that need to be taken in order to make your content as discoverable as possible.


For producers that have a deal with Streaming Video on Demand (SVOD) platforms like Netflix or Amazon Prime there is still a bit of heavy lifting to do. In order to satisfy the suggestion engines and accurately fill the curated content lists, while providing the user experience, these platforms require the producers to descriptively label their content in very fine detail.

Using Netflix as an example, when the assets of these shows are tagged with specific indicators, the platform is able to categorize shows by actor, theme, genre, film/TV and sub genres such as “films with a strong female lead”. All of this leads to greater personalization as part of the service.

If you’re still not convinced about the importance of AI in media consumption or the necessary corresponding labelling duties required of producers, consider this: 75% of Netflix viewing is driven by the recommendation algorithm. Back when Netflix was only at 33 million users worldwide, then head of global communications Joris Evers said “there are 33 million versions of Netflix”, from there the emphasis on personalization has only gone from strength to strength.