NEW YORK (Reuters Blogs) -- Alexis Madrigal has a rollicking investigation into Netflix's movie genres -- all 76,897 of them, from category #1 (African-American Crime Documentaries) to category #91,307 (Visually Striking Latin American Comedies). His story is titled How Netflix Reverse Engineered Hollywood, and as such, it's the latest entrant to a well-stocked category of its own: Awestruck Narratives About Netflix's Technology and the Systematization of the Ineffable.
I'm something of a curmudgeon when it comes to such stories, however -- and it seems to me that there's an alternative reading to Madrigal's story, which tells a rather more bearish story about Netflix. Netflix's big problem, it seems to me, is that it can't afford the content that its subscribers most want to watch. It could try to buy streaming rights to every major Hollywood blockbuster in history -- but doing so would cost hundreds of billions of dollars, and could never be recouped with $7.99 monthly fees. What's more, the studios can watch the Netflix share price as easily as anybody else, and when they see it ending 2013 at $360 a share, valuing the company at well over $20 billion, that's their sign to start raising rates sharply during the next round of negotiations. Which in turn helps explain why Netflix is losing so many great movies. As a result, Netflix can't, any longer, aspire to be the service which allows you to watch the movies you want to watch. That's how it started off, and that's what it still is, on its legacy DVDs-by-mail service. But if you don't get DVDs by mail, Netflix has made a key tactical decision to kill your queue -- the list of movies that you want to watch. Once upon a time, when a movie came out and garnered good reviews, you could add it to your list, long before it was available on DVD, in the knowledge that it would always become available eventually. If you're a streaming subscriber, however, that's not possible: If you give Netflix a list of all the movies you want to watch, the proportion available for streaming is going to be so embarrassingly low that the company decided not to even give you that option any more. While Amazon has orders of magnitude more books than your local bookseller ever had, Netflix probably has fewer movies available for streaming than your local VHS rental store had decades ago. At least if you're looking only in the "short head" -- the films everybody's heard of and is talking about, and which comprise the majority of movie-viewing demand. So Netflix has been forced to attempt a distant second-best: scouring its own limited library for the films it thinks you'll like, rather than simply looking for the specific movies which it knows (because you told it) that you definitely want to watch. This, from a consumer perspective, is not an improvement. What's more, with its concentration on streaming rather than DVDs by mail, Netflix has given up on its star-based ratings system, and instead uses what it calls "implicit preferences" derived from "recent plays, ratings, and other interactions". Again, I'm not sure this is an improvement -- but it does fit in a much bigger strategic move chez Netflix. While Madrigal and I might still think of Netflix as an online version of your old neighborhood Blockbuster Video store, Netflix itself wants to replace something which accumulates many more viewer-eyeball-hours than Blockbuster ever did. It doesn't want to be movies: it wants to be TV. That's why it's making original programming, and that's why the options which come up on your Netflix screen when you first sign in are increasingly TV shows rather than movies. One huge difference between TV and movies is that audiences have much lower quality thresholds for the former than they do for the latter. The average American spends 2.83 hours per day watching TV -- that's not much less than the 3.19 hours per day spent working. And while some TV is extremely good, most of it, frankly, isn't. Television stations learned many years ago the difference between maximizing perceived quality, on the one hand, and maximizing hours spent watching, on the other. Netflix has long since started making the same distinction: It wants to serve up a constant stream of content for you to be able to watch in vast quantities, rather than sending individual precious DVDs where you will be very disappointed if they fall below your expectations. Netflix's biggest fans tend to be parents of young kids -- but in a sense, Netflix wants to turn us all into young kids, consuming an endless stream of minimally differentiated material. (Note that Netflix doesn't allow you to watch a trailer for a movie before streaming it; it just expects you to stop watching that movie, and start watching something else, if you don't like it.) Strategically, this move makes a lot of sense for Netflix. TV shows are cheaper to license than movies are, and people tend to be much more addicted to their TVs than they are to watching movies. And the rise of the micro-genre at Netflix only really makes sense once you understand its TVification. On Netflix, you can binge-watch one reality-TV show, and then watch another, and another; or you can do the same with, say, crime series. They don't need to be great, they just need to be the kind of thing you like to watch. Which explains why Lilyhammer just started its second season, despite the fact that no one was particularly impressed the first time around. The original Netflix prediction algorithm -- the one which guessed how much you'd like a movie based on your ratings of other movies -- was an amazing piece of computer technology, precisely because it managed to find things you didn't know that you'd love. More than once I would order a movie based on a high predicted rating, and despite the fact that I would never normally think to watch it - and every time it turned out to be great. The next generation of Netflix personalization, by contrast, ratchets the sophistication down a few dozen notches: at this point, it's just saying "well, you watched one of these Period Pieces About Royalty Based on Real Life, here's a bunch more." Netflix, then, no longer wants to show me the things I want to watch, and it doesn't even particularly want to show me the stuff I didn't know I'd love. Instead, it just wants to feed me more and more and more of the same, drawing mainly from a library of second-tier movies and TV shows, and actually making it surprisingly hard to discover the highest-quality content. It's a bit like what Pandora would be, if Pandora was severely constrained in the songs it could choose from. This move is surely great for Netflix's future profitability, and probably helps explain its resurgent share price. If Netflix can provide half of the service that traditional TV offers, at a tenth of the price, that's a deal which can go a very long way. But it's also a service aimed squarely at couch potatoes, not at movie lovers. I don't find myself with 2.8 spare hours to watch TV very often, and when I do, I want to make those hours count, by watching something great. For me, and for people like me, Netflix's micro-genres create little more than a frustrating slurry of mediocrity in which it is increasingly difficult to find the gems. I find it much easier to find something I want to watch on the iTunes rental library than I do on Netflix. Normally, I'll check canistream.it to see whether the film in question is available on Netflix before I click the "rent" button. But there's something a bit screwy about a world where I find iTunes to be a more useful discovery mechanism for Netflix material than Netflix itself.
Netflix has meticulously analyzed and tagged every movie and TV show imaginable. They possess a stockpile of data about Hollywood entertainment that is absolutely unprecedented...
When these tags are combined with millions of users viewing habits, they become Netflix's competitive advantage. The company's main goal as a business is to gain and retain subscribers...
Now, they have a terrific advantage in their efforts to produce their own content: Netflix has created a database of American cinematic predilections. The data can't tell them how to make a TV show, but it can tell them what they should be making. When they create a show like House of Cards, they aren't guessing at what people want.
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