How to Partner Better in a Data-driven World

DISCLAIMER: I have no inside knowledge into what may or already have been discussed, or data analyzed by either AMC Theaters or MoviePass. This article is purely based on my thoughts as a movie-goer, marketer, and product manager.

This article in The Verge caught my attention:

MoviePass threatened with lawsuit after slashing subscription fees to $10 a month 
by Thuy Ong

"AMC Theatres has threatened MoviePass with a lawsuit, less than a day after the subscription cinema service dropped its subscription fees to $9.95 a month, reports Variety. That means subscribers are able to watch one movie every day for a month for only $9.95. MoviePass would still have to pay AMC full ticket prices each time someone uses the subscription, though. An average ticket is priced at $9.33, so a subscriber would only need to attend two movies a month to put MoviePass at a loss.

In 2016, the service started at $15 per month and ran up to $50 per month for unlimited movies in bigger cities. AMC, which is the largest theater chain in the US said in a statement that MoviePass’ model is unsustainable. The company argued that ticket prices below $10 a month over time wouldn’t be able to generate enough cash to operate quality theaters, nor produce enough income that would allow film makers to make movies of value.- Source The Verge

I never knew about MoviePass as a subscription for unlimited movies. As a father of twins my wife and I barely get to go to the movies but once every 2 months, and it costs us an extra $100 in babysitting to go, and there's nothing really compelling as far as "good" movies in our opinion, but I digress! Moviepass' offer of $9.95 a month does seem to be very compelling, and ultimately very disruptive.

My first reaction in seeing that AMC is suing MoviePass for this action is to wonder out loud whether AMC had gone to MoviePass and offered to jointly analyze their respective datasets in order to see if there might be synergies in such an action.

An Outsiders Product Manager's Perspective:

  1. Showtimes of movies (beyond opening week of new blockbusters) are rarely full, meaning there is unused inventory in every single time slot 
  2. Pricing strategies to try and fill these slots don't appear to have changed much beyond off peak time discounted ticket offers
  3. Loyalty and rewards programs have now started to become more prevalent so efforts are ongoing to capture consumer profiles
  4. Concession sales per customer are  lucrative with a large popcorn and drink often costing more than the standard ticket (letting MoviePass fill shows to capacity could yield more in concession revenues than tickets itself)

Clearly I would need more data to find patterns and analyze this information to form the right conclusions. The steps would be to:

  1. Form a Reliable Data foundation - leading to a 360-degree view of the consumer/movie-goer profile, with demographics, attribution, captured in part through AMC's loyalty programs, but also could then be cross-referenced (Matched and Merged) with MoviePass' subscribers to enrich both data sets.
  2. Benefit from Commercial graph technology to find friends and family affiliations to drive offers (see marketing perspective later) to make it more of a social/group movie-going experience
  3. Generate Relevant Insights - by bringing together the transactions processed via the tickets bought through MoviePass vs. walk-ins, and other avenues such as Fandango, promotions etc. Stanalone Master Data Management profiles are insufficient as the real valuable insights are in the transactions/behaviors exhibited by those movie-goers, and they need to be analyzed and seamlessly aggregated back into the master profiles for marketing segmentation
  4. Deliver Recommended Actions - So marketing teams can jointly highlight how AMC and MoviePass could gain synergies from the increased traffic to theaters. Applying machine learning and data science to the reliable data foundation, not just at a macro-level, but to generate the right programs that can take advantage of the identified profiles, to drive more personalized experiences, and revenue-generating concession sales
  5. Leverage Data as a Service - to securely share insights between AMC and MoviePass, preserve consumer privacy, and to bring in more data from suppliers of concessions to negotiate discounts and for synergies such as just-in-time ordering to improve margins

An Outsiders Marketing Perspective:

Once all this data is aggregated, made reliable, and analyzed, the joint market teams of AMC and MoviePass could work on promotions and programs using data-driven applications. With a Modern Data Management foundation they would be able to correlate  Recommended Actions back to actual outcomes. Personalizing and improving customer experiences are just the cusp of benefits that can be realized. New business models that could easily be supported might include:

  1. Making it more of a social experience - convert real-estate into Starbucks-like hangouts, with good coffee, wireless, and a place to meet. Offer better higher-end desserts so people come 30 mins before the movie with family and friends after dinner, or stay afterwards to chat about the movie and what they thought about it
  2. Increased kids focus - more tie-ins and kids activities, pre- and post-movie with merchandise sales in a movie "store" with branded items tied-ins. Sales immediately after the event for instant gratification is the a way to command a premium over online sales and their lower prices

Given the fact that VOD, Netflix, Virtual, and Augmented Reality are literally right in the face of and challenging the movie theater going experience, AMC and other theater operators face being disrupted. A Modern Data Management Platform as a Service is essential to not only improve revenue, margins and partner better, but possibly survive.

How do you think the experience could be improved as a movie-goer?

As a Product Manager, how would you use data to gain better insights and possibly partner better. Have you used shared data and insights in similar situations between partners, or perhaps in M&A scenarios? Please share.