Posted by: structureofnews | August 23, 2013

The Data Economy

forbes-cover-7_16-232x3001111So I’m not really a LinkedIn kind of person. Sure, I’m signed up, and have a couple of hundred connections at last count.  But I don’t go to the site a lot, and if anything’s up on my screen regularly, it’s probably Facebook.

Guess who makes more money off me?

Or more precisely, who makes more money off my data?

There was a recent piece in Fortune (behind a paywall) about LinkedIn’s fortunes, and one last summer in Forbes, that put the company’s business strategy in perspective.  It’s all about user data, and how you can repurpose it for much more than serving up targeted ads.

Last year’s piece in Forbes, by George Anders, makes that clear:

(LinkedIn chief executive, Jeff) Weiner draws three concentric circles to show how LinkedIn makes its money. The outer one is subscriptions. Next , marketing and advertising. And in the center is LinkedIn’s richest and fastest-growing opportunity: turning the company’s 161 million member profiles into the 21st-century version of a “little black book” that no corporate recruiter can live without.

“That’s the bull’s-eye,” he says.

It certainly looks that way.

There’s no better way to understand LinkedIn’s quiet savvy, in the midst of Facebook’s noisy clatter, than to compare the two sites’ financial efficiency. With ComScore Web-usage data and public financial filings, it’s now possible to figure out how much revenue the two rivals collect for every hour that each user spends on the site. LinkedIn’s tally: $1.30. Facebook’s: a measly 6.2 cents.

The point is that, while Facebook depends on having users visit its site to generate advertising revenue, LinkedIn is busy monetizing your CV data to recruiters, whether you ever log on again or not.  And that, of course, doesn’t mean it can’t sell you advertising as well; what this means is that the company has two product lines and revenue streams.

Call that the difference between playing in the attention economy and the data economy.

Which offers up a useful lesson for journalism organizations as well.  Rather than focus mainly (or only) on the stories we write, and the attention they attract (and hence the advertising we can sell), why not focus as much on the data we can generate – either from the content we’re producing, or from the audience we’re attracting?

There’s certainly work being done on the latter front – in terms of thinking about the real value of news organizations as brokers of the relationships it enjoys with its audience; but we haven’t done a huge amount in terms of thinking how we could re-use and monetize the data we create every day as part of our daily work.  That’s the basic theme of structured journalism – and in many ways it’s not far different from LinkedIn’s core strategy.

And there’s more: Having more data, and in a structured form, can help begat even more connections and value.

In a follow-up piece this summer, George Anders adds:

Consider LinkedIn’s uncanny ability to suggest extra contacts with people you might know. In April, I reported that LinkedIn can now alert recruiters about other candidates they should pursue, thanks to careful analysis of earlier job search patterns. Running a job search has never been so easy! LinkedIn isn’t likely to stop there. Its ability to use its algorithms to help us grow connections — and prioritize the ones we already have — is likely to make heads turn in the next few years.

For journalism organizations, substitute the idea that, as we build up newsroom databases of content, we can discover more connections and ideas that make reporting better and faster; and that these can also power new products (ala Connected China).

(Someone once described the idea behind Connected China as LinkedIn for the People’s Republic, which I thought was wildly off.  But then again maybe the business idea behind that comment isn’t that far off…)


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