For many years people have been predicting the end of movie theaters. And while that end has yet to come, it’s clear that once we return to some sort of normalcy in this country movie theaters may never be the same.
And this in part inspired Disney’s very interesting decision to release Mulan on its streaming service, Disney+.
While it recently dropped Hamilton to massive amounts of fanfare and eyeballs, it has a different, more lucrative strategy for the live-action version of its cartoon classic.
When the film starts streaming on September 4th, it will be available to Disney+ subscribers… for 30 bucks. That’s right, even though you already pay for the streaming service, this particular film is going to cost an additional 30 dollars.
The reasoning behind this is pretty obvious, as Mulan was set to be Disney’s big summer movie, and giving it away for “free” would have severely kneecapped a film that cost 200+ million to make.
But will it succeed? Will Disney make enough money doing this to justify not waiting until people could watch it in theaters? After all, a trip with the family to see a movie definitely costs more than 30 bucks. And on the other side, is it really fair to people who already pay for a streaming service to pay that much for a movie? Why not just give it away for free and use the press to convince more people to sign up for the service?
All of these questions are up in the air, and every movie and streamer will be different. But when it comes to such high-stakes decisions, AI can be an invaluable tool in deciding how this Premium VOD thing should actually work.
Much of this comes down to a streamer’s library and how their viewers interact with it. Some basic decisions can be figured out by looking at what customers are most interested in and predicting if an additional cost to a film would actually be something those customers are willing to pay for. But figuring that out requires more than just intuition; it requires a large amount of data analysis and machine learning.
Looking at how customers view the current library would not only determine what shows are popular but how they are truly engaging the audience. Then decisions can be made on if the potential PVOD title shares the attributes of other titles that have kept people watching, which means more value would be placed into something that requires a one-time payment.
But this kind of granular insight requires AI to make millions of connections between viewers and the content, which cannot be figured out any other way.
PVOD, in some form or fashion, is going to be a part of how people view films in the future. But to make that future as profitable as possible, you need analysis from Resonance AI.