But hey, I'm an ex-finance MBA turned business development type. The revenue channels, the capital structures and the corporate ownership end up driving the product. My technically minded co-host has pointed out that I usually ascribe all product outcomes to underlying business models. In 2018, it was 57.2, steadily increasing since 2010 (with a slight dip in 2012-13). The average rating from 1997-2010 for all movies that were widely distributed (1000+ screens) was 44.6.
#ABOVE SUSPICION 1995 ROTTEN TOMATOES MOVIE#
This recent study from a movie marketing consultant validated my suspicion that there has been ratings inflation: A 90%+ movie is still pretty good, but not that lightning strike it once was. Not just a decent movie, but one so good it makes you spend a few hours on Reddit afterwards, trying to learn more. Regardless of the genre, it almost always delivered. For a while, if I saw a Rotten Tomatoes movie with a rating above 90%, I watched without hesitation. On the other side of the dataset purity spectrum, you have Rotten Tomatoes. It's like this weird dataset, trapped in amber, built by a very specific audience that was never corrupted by external influences, and is allowed to currently exist courtesy of an exogenous business model. But it never got to an IPO-level revenue push that forced them to build in aggressive ad products. They seemed to live in the pre-monetization purgatory of late-stage growth funding for a while, and now, I think they're selling my location data to hedge funds, or something like that. The company never had a massive, operational advertising model built on the ratings. That's what Yelp and Google Reviews are for. I'm guessing no black hat marketers ever spent time going after Foursquare. It was never overrun with spammers because it never became that important a platform.
For a few glorious years you had moderately affluent, tech-forward, urban professionals roaming the world and actively reviewing places. I'm guessing the only demographic that ever really used it have similar tastes as me.
There are a few things that make it a really intriguing dataset:
We agreed it can still deliver better than a TripAdvisor or Yelp, all over the world. I brought up how when I visited, I was shocked at how good Foursquare was for recommendations. My co-host Can is heading to Beirut this weekend. Ranjan here, talking about datasets stuck in time, Rotten Tomatoes, and internet reviews.
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