Netflix Uses AI to Figure Out How Much to Pay for Content

Image source: Netflix

Netflix's (NASDAQ: NFLX) content library isn't just some mashed together pieces of disparate content the streaming video leader could get its hands on for cheap. Netflix has crafted several computer algorithms to determine what shows to produce, what shows and films to license, what content to show to each user, and apparently how much to pay for each piece of content.

In a recent Business Insider article detailing how documentarian Craig Atkinson ended up not selling his film to Netflix, he revealed an interesting detail about Netflix's negotiation tactics. Specifically, he said a Netflix lawyer told him an algorithm determined the price of his film, "and that basically was the end of the discussion."

AI is an integral part of Netflix's business. It says its content recommendation engine saves it $1 billion per year. Who knows how much it saves by using AI to determine how much it should be paying for content?

Netflix uses its biggest competitive advantage to stick to a budget

There's a bit more pressure on Netflix to stick to a content budget compared to other players in the digital video space. Amazon (NASDAQ: AMZN), for example, can fall back on its retail and cloud businesses to subsidize its content budget. Alphabet's (NASDAQ: GOOG) (NASDAQ: GOOGL) Google can support big cash outlays from YouTube. Facebook (NASDAQ: FB) has also gotten into content acquisition recently, and has a big advertising business to support it.

Netflix, on the other hand, only generates revenue from its streaming service. In fact, it's using debt to support its content spending as it expands overseas. Amazon Instant Video, YouTube, Facebook, and HBO can all draw from the piles of cash at their respective companies.

As such, Netflix needs to be exacting when it comes to how it spends its content budget, eking out any efficiencies it can. And it's using its biggest competitive advantage to do so.

Netflix has an unrivaled amount of viewer data. It has nearly 90 million viewers -- nearly 50 million in the U.S. -- spending an average of around two hours streaming movies and TV shows every day. And it's careful about whom it shares that data with.

Developing an AI algorithm to make content purchasing decisions based on its user data is one of the keys to Netflix spending its budget wisely.

Netflix's competition is growing, and they have deep pockets

Netflix completed its global expansion earlier this year, but the competition isn't far behind.

Amazon just launched its Instant Video service globally, and represents one of the biggest threats to Netflix. Analysts expect Amazon to spend between $4 billion and $5 billion on content next year after doubling its spend in the second half of 2016. Netflix expects to spend $6 billion next year. But Amazon is also charging less than Netflix at just $5.99 or 5.99 euros per month compared to Netflix's standard $9.99 per month. It's able to undercut Netflix because it doesn't need to make a direct profit from streaming video.

YouTube and Facebook are also competing for consumers' attention. Both already have large global presences and engaged user bases.

YouTube has reportedly explored licensing TV shows and films for its premium YouTube Red subscription service. It's also reportedly planning to launch a digital pay-TV service with livestreaming networks early next year.

Facebook, too, is getting more serious about video content. It's reportedly in talks to produce its own original shows to support its new dedicated video section in the flagship Facebook app.

The common threads between all of these video platforms is that they're not under significant pressure to generate a profit as a stand-alone service and their parents have piles of cash. Nobody is really digging into their financials like the Street does with Netflix every quarter. If management really wants a piece of content, they can probably get it.

On the other hand, Netflix needs to be more restrained with how it spends. With some of the best AI and one of the largest sets of viewer data to feed it with, it's well positioned to spend its budget more efficiently than its competitors.

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