Making the Most of Moviepass

15 Sep 2018

In August 2017 Moviepass announced an offering of 1-movie-per-day in any supported theater for $9.95/mo. Given that 1 movie-ticket-per-day over 1 month costs $350 in my area the offer was an extraordinary value. How does one make the most of this?

The offering naturally lead to a number of questions: What should I watch and when? How can I watch as many of the “best” movies? How does one define “best”? How many can one practically attend anyway? How many movies are there in my area in a month? Do all theaters just play the same movies? If not, how do they differ? How many movie theaters can I actually get to? Are movies the new tv? What is consuming a movie actually worth to me? Is it better to watch a “worse” movie more cheaply, or spend more to travel farther to see a “better” one? How accurately can I predict what I will like? Should I adjust my expectations to fit the films that are available the most cheaply, or, given greater access should I increase my selectivity? Should I focus on stuff I’m more likely to enjoy, or should I take greater risk by broadening my horizons? And perhaps most importantly – how do I take maximum advantage of this offer before it inevitably ends?

Given this paradox of choice I ended up building a “TV guide for my local movie theaters” a daily-generated custom report listing the cheapest showing of each movie that day, taking into account the Moviepass discount, transportation cost and travel time:

report

The report is a custom synthesis of data across a number of sources – Fandango for movie listings, Moviepass for supported films by day, RottenTomatoes for critic reviews, Cinemascore for opening weekend audience exit polling, Metacritic for critic and audience reviews, Festival and award and “best of” lists for cultural indicators from a number of sources, BoxOfficeMojo for box office stats from and costs from my own theatrecost spreadsheet. The report also outputs a number of factors which are currently hardcoded into formulae; eventually these could be used for machine learning to derive better algorithms.

Alas, with Moviepass switching from 1-per-day to 3-per-month to curtail their unsustainably high burn rate it means this type of daily reporting will be much less valuable – extracting max value will be more dependent on forecasting the most “interesting” movies between billing periods in a highly personalized way, and then deciding what is worth paying for… a lot less “juice for the squeeze” for cinephiles on a budget. Oh well, it was fun while it lasted :)

Further Reading

  1. Moviepass topic on news.google.com
  2. The Paradox of Choice