The Future of Content Creation: Keyword Research on Steroids
Wired this week published a fascinating profile piece on a company called Demand Media: "The Answer Factory: Fast, Disposable, and Profitable as Hell." The company's approach to content generation almost sounds like science fiction or satire, but it's real, and it works. It's a purely algorithmic, data-driven method of prioritizing content designed to rank on the first page of the Google SERPs: basically keyword research in hyperdrive. And like it or not, this may be where we're all headed.
Demand Media, however, has taken this process to another level:
Pieces are not dreamed up by trained editors nor commissioned based on submitted questions. Instead they are assigned by an algorithm, which mines nearly a terabyte of search data, Internet traffic patterns, and keyword rates to determine what users want to know and how much advertisers will pay to appear next to the answers.
The algorithm, created by Byron Reese, works like so:
To determine what articles to assign, his formula analyzes three chunks of information. First, to find out what terms users are searching for, it parses bulk data purchased from search engines, ISPs, and Internet marketing firms (as well as Demand’s own traffic logs). Then the algorithm crunches keyword rates to calculate how much advertisers will pay to appear on pages that include those terms. (A portion of Demand’s revenue comes from Google, which allows businesses to bid on phrases that they would like to advertise against.) Third, the formula checks to see how many Web pages already include those terms. It doesn’t make sense to commission an article that will be buried on the fifth page of Google results.
Content is then assigned to freelancers who work fast and on the cheap. Content quality takes a backseat to content targeting: According to Reese, "the most valuable topic in Demand’s arsenal" is "Where can I donate a car in Dallas?" That just happens to be their most profitable keyword—no expert could guess that based on intuition or even figure it out with less sophisticated data analysis.
This is super-long-tail targeting—and the effectiveness of Demand's approach should make us all stop and think. Originally, the company was driving content creation through a combination of algorithmic keyword research and editorial insight:
But once it was automated, every algorithm-generated piece of content produced 4.9 times the revenue of the human-created ideas. So Rosenblatt got rid of the editors. Suddenly, profit on each piece was 20 to 25 times what it had been. It turned out that gut instinct and experience were less effective at predicting what readers and viewers wanted — and worse for the company — than a formula.
Kind of creepy, huh? What's that clanging sound? Just the sound of robots coming to take your job.
Speaking of creepy, the article also gives us a peek into the life of Richard Rosenblatt, the cofounder, chairman, and CEO of Demand Media. His email signature includes the phrase "Go big or go home." He's friends with Lance Armstrong (You might be a douchebag if…). Check out his bio page: He looks like the Rob Lowe character in Wayne's World!
To be fair, the guy supposedly only seems sleazy:
Numerous executives told me that when they first met Rosenblatt, they were immediately repulsed: He was too slick and seemed to be missing the geek edge. “Then in five minutes you’re like, ‘Holy cow, this guy has it all to back it up,’” says Quincy Smith, CEO of CBS Interactive.
I love that: the geek edge. Give me geek edge over Rob Lowe hair any day.
Bringing it back to search … I recommend reading the piece, and giving some thought to your own content creation priorities and practices. If you think you know what your readers want without digging into the hard data, think again. I.e., watch your back (for robots).
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