Predictive Analytics

How Predictive Analytics Is Fueling Subscription-Based Businesses

By Sriram Parthasarathy
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These days, you can’t go 10 minutes without hearing about a subscription service. We have video streaming services (Netflix, Hulu), meal delivery services (Blue Apron, Hello Fresh), movie passes (MoviePass), and subscription “boxes” for everything from beauty items (Birchbox) to pet supplies (BarkBox). Subscription-based business models are everywhere—and they’re tapping into an increasing stream of data. In today’s digital world, information on people’s buying habits is readily available. And thanks to predictive analytics, that data can be used to grow a business.

Today’s most successful subscription network businesses are those that keep user acquisition costs low and quickly scale in order to negotiate premiums with retail establishments. As an example, let’s look at MoviePass, a $9.95-a-month subscription service that lets users watch up to three movies per month in a variety of theaters.

Leveraging Predictive Data

MoviePass collects demographics on its subscribers during signup, and then collects even more information when a subscriber uses the app to buy a ticket (time, location, theater, movie, etc.). Once they’ve scaled to a sizable number of subscribers, MoviePass can employ predictive analytics to answer questions such as:

  • What kind of movie does this person typically see?
  • Will this person see this movie this Friday at 7:00 pm?
  • How many people will see this movie this Friday at 7:00 pm at this specific location?

Armed with this predictive information, MoviePass has the power to navigate users to a specific theater—and therefore can more easily negotiate lucrative deals. For example, if there are three theaters within a five-mile radius, the theater that gives the best deal to MoviePass could be the lucky one at the top of MoviePass subscribers’ lists to see a particular movie at 7:00 pm.

Expanding Offerings

Why stop at movies? Many moviegoers may also go to a local restaurant for dinner. MoviePass could again use the power of numbers in their ecosystem to negotiate deals with retail businesses and rapidly expand its offerings. Predictive data can answer questions such as:

  • Which subscribers go to a movie and have dinner at a nearby restaurant?
  • Which subscribers travel to a movie using Uber?

MoviePass then essentially becomes “RetailPass,” where any related retail service—dinner, transportation, etc.—can be packaged as part of the subscription for an additional one-time or monthly cost. In kind, these transactions would provide even more data that could be used to tweak the offers that make the most sense for consumers. 

We might see more subscription businesses cropping up soon—maybe an UberPass, DinnerPass, LunchPass, and so on. Every service industry is a target for the subscription model as companies use the power of predictive analytics to drive user adoption and future business.


Originally published October 4, 2018; updated on July 31st, 2020

About the Author

Sriram Parthasarathy is the Senior Director of Predictive Analytics at Logi Analytics. Prior to working at Logi, Sriram was a practicing data scientist, implementing and advising companies in healthcare and financial services for their use of Predictive Analytics. Prior to that, Sriram was with MicroStrategy for over a decade, where he led and launched several product modules/offerings to the market.