> Helios and Matheson, an analytics company which has a majority stake in MoviePass
This here is the juice: Big data. The more customers they have, the better - they have validated full names, birthdates, addresses and CC numbers (and most likely also ethnicity) linked with the data when they visited what movie and even if the customers repeatedly visited a movie.
MoviePass has, effectively, four distinct customers:
a) the moviegoers themselves, where MoviePass makes a profit on everyone watching less than 1 movie a month
b) the vast amount of adtech/big data/consumer analytics companies for which this data is a goldmine
c) the movie studios which can (as shown in the article) use MoviePass to promote movies
d) the cinemas which profit off the customers wanting to eat and drink
They have, of course, monetized a) and begun to discover how to monetize c) - it will be interesting if they find a way to monetize the data.
Is that data that valuable though? Its not that unique, off the top of my head there are several companies that have similar datasets, Every movie theatre chain, every online movie booking service, every movie review site
- the theatre chains only have mostly generic datasets (the audience for movie X is mostly young white males) while MoviePass can do far more detailed analysis (and, in theory, could pass detailed questionnaires after you watched a movie, thus gathering more personalized data)
- online movie booking services (at least in my social bubble) are only used for movies where people think they don't have a chance to get a ticket without an early reservation
- movie review sites only have tiny bits of data about the readers, and the reviewer dataset is skewed - it only provides data about the people caring enough to do a review.
I agree with this mostly. However, the data coming from MoviePass may be flawed. I'm much more likely to see a movie I would never normally pay to see with a MoviePass subscription.
> I'm much more likely to see a movie I would never normally pay to see with a MoviePass subscription.
That is the exact thing that makes the data actually interesting: it removes the risk factor, aka "do I want to see a movie for $12/person and risk that it's trash?", from the viewer's decision process.
There's a lot more interesting data to mine there.
I'm a lot more willing to walk out of a movie I didn't pay for. There's not really a way to capture this data right now, but the MoviePass system requires you to have an app on your phone, and check in shortly before the movie, at the theater.
If I was them I'd be looking at putting audio fingerprinting on the phone to determine whether people leave before the movie ends.
Chains have data only for the times people visited their own chains (and might not have much info for counter sales), online booking services have a similar problem, movie review sites are much more limited in that not everyone writes a review for any movie they watch, leave alone all the movies they watch.
Their data is useless. They have no way to tie purchases to the movie viewed. I just pick the first thing it’ll let me check in for, not the movie or time I want, and it always works.
Do me a favor and turn off your GPS after purchase so the app doesn't track the viewing time of the movie you actually went to. Abuse of the service like what you're doing may force them to add restrictions. Not cool, IMO.
This here is the juice: Big data. The more customers they have, the better - they have validated full names, birthdates, addresses and CC numbers (and most likely also ethnicity) linked with the data when they visited what movie and even if the customers repeatedly visited a movie.
MoviePass has, effectively, four distinct customers:
a) the moviegoers themselves, where MoviePass makes a profit on everyone watching less than 1 movie a month
b) the vast amount of adtech/big data/consumer analytics companies for which this data is a goldmine
c) the movie studios which can (as shown in the article) use MoviePass to promote movies
d) the cinemas which profit off the customers wanting to eat and drink
They have, of course, monetized a) and begun to discover how to monetize c) - it will be interesting if they find a way to monetize the data.