NICK CICERON: What I want to know is what a movie looks like 21 jump street suddenly make it to the top of Netflix’s top 10 for a week?
I see that in Hulu’s “most watched” list similar features on other services and wonder why these really random shows end up bubbling up?
Which is really interesting because you have the hits you expect and the hits you don’t.
The hits you predict will be the ones you spend the most money on, the ones you promote the most.
Yes, your research has shown that this is the right content to acquire, and so this is one of the shows you invest everything in. These shows are your marquee content.
But then you have all the rest of that content. And what Conviva solves because we have second-by-second session-level data is that we can actually see how these patterns are changing and their impact.
So if you take any of your hits – any of the hits that you anticipate – or even the ones that you don’t – you can actually use Conviva’s data to unpack that and figure out “how are you- have you come to this point?”
You can use the viewer-level journey to understand that people may have gone from not watching anything to watching an NFL game to watching Yellowstone and this pattern was more prevalent than anything else.
Or maybe – I’m going to use Paramount+ as an example here, maybe you have a whole new segment of people who came in and all of a sudden they joined Paramount+ because they wanted to watch Yellowstone.
And in six weeks all of a sudden paw patrol is back at the top of the charts.
Them, you can use Conviva’s data to see that paw patrol had a very strong inbound path of new viewers watching Yellowstone and that those viewers then switch to paw patroland you can use this data to your advantage to understand why paw patrol going to be a success and why it’s going to be a great thing for your department and how you can plan for it in terms of promotion.
If you think of a show like squid game as another good example, squid game often it seems like it came out of nowhere.
But it didn’t come out of nowhere. It started with a small group of people who started watching it, then informed an algorithm that recommended it to a larger group of people, and then to an even larger group of people.
This is one of the powers of the Conviva sensor.
And that’s why we’re working with so many of these different publishers right now, because we can actually unpack all of these hits to help them understand how they come back and manufacture success.