Share this post:
At IRIS.TV we’re using machine learning to enable the biggest transformation of how people watch video since the evolution of cable television.
I know that’s a bold claim. But let me show you why we believe it.
For decades, succeeding in the biggest media business in the world – television – came down to having great content and owning a distribution channel. Once that was in place, the research and programming department would say this program should be on at 7 p.m., and this one at 8 p.m., and so on.
Build it and they will come – and they did. In the millions.
The end of entertainment
That model was based only on entertainment. But now we’re all watching more and more content on mobile devices and computers, so instead of having one channel on TV we have thousands of videos that we could watch on a single site, like CBS News or the Los Angeles Times.
These changing viewing habits and new technologies are forcing businesses to shift their focus to engagement as much as entertainment. Advertising revenue depends on video views, so the bottom line suffers if media companies can’t keep people watching. But making this happen demands a paradigm shift in understanding and inferring which content to serve next.
This is the research and programming department of the future – and it’s what IRIS.TV does, supported by AI computing from IBM Watson.
How IRIS.TV uses AI computing to improve video engagement
At IRIS.TV we’ve developed video personalization technology that consumers typically associate with Facebook, Amazon, Netflix, and Google, except we license it to broadcasters, telcos, marketers and publishers for use on their owned and operated platforms.
One way in which AI computing plays into this is with IBM Watson as we found opportunities to build larger datasets around our customers’ videos.
Often the datasets on short-form videos are sparse because they may only be geared toward finding related assets in content libraries, or improving search. At the time, our customers weren’t necessarily thinking about programming or creating a personalized playlists to drive engagement over the long term.
But with IBM’s APIs, IRIS.TV can ingest whatever information is available and, using Watson’s Natural Language Understanding, start to build out deeper datasets about the content itself, which in turn feeds into our AI and machine learning systems. The result is smarter recommendations.
A very large European publisher saw video views increase by more than 87 percent when it enriched the metadata on its videos in this way. This in turn drove a direct revenue increase because they’re serving ads on those videos. Significantly, it also proves the concept at scale; we’re talking tens of millions of video views per month.
Advice for entrepreneurs looking to be disruptive with AI
If you’re an entrepreneur starting a new business, the most precious asset you have is time, which you need to be using effectively. And the next most important thing is making sure you’re in a market segment that’s large enough to support your ambitions – if you’re trying to be the next most disruptive company in the world, you need to make sure you’re in a very large market.
After that, look for partnerships that can augment and accelerate your development. This is what we at IRIS.TV like about IBM.