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Since Microsoft announced its $26 billion acquisition of LinkedIn, there has been predictable skepticism about how the company will recoup its investment. In fairness, we’re talking about a social network that generally loses money. And while it has some synergies with its new parent, they’re probably not enough to justify the price tag in traditional terms.
The problem with this way of thinking is that it looks at the acquisition tactically. The real value of LinkedIn does not lie merely in integration with Microsoft technologies. It lies in the long-term use of the data it has collected. Marketers and advertisers like me should be salivating over what we’ll soon be able to do.
The real value of LinkedIn does not lie merely in integration with Microsoft technologies. It lies in the long-term use of the data it has collected.
LinkedIn data is remarkable for a number of reasons. In the first place, it’s accurate. People lie on Facebook all the time; they don’t on LinkedIn. What’s more, they tend to keep their accounts scrupulously up to date. In the second place, it’s economic data. It’s about the education, training, career paths and professional content preferences — things we really want to know. Finally, it’s geographic and allows you to zero in on what matters where.
Taken together, the data adds up to something LinkedIn has been calling an economic graph. According to the company, this is a digital map of the global economy. It includes students, employees and upper management at schools and companies across the globe. More importantly, it shows not just who these people are and what they do, but how they are connected with one another.
Theoretically at least, this gives us powerful capabilities that we just haven’t seen before. Once complete (and to a lesser degree now), the economic graph could influence everything from career choices and marketing messages to educational institutions and public policy.
A few examples can probably help, so let’s start with B2B. Often in B2B marketing, you need to influence different people in a company in a sequence to get them thinking about the same goal. Right now, we can’t do that efficiently. But the graph could tell a B2B marketing team how to target information to the right people, so that it could more quickly align an organization.
LinkedIn data is remarkable for a number of reasons. In the first place, it’s accurate.
A much different example comes with public policy around middle-skills jobs. These are jobs that require specialized technical training, such as respiratory therapists or computer repair technicians. The graph could show how many people were moving in and out of such fields, and where gaps might exist. That knowledge could be of great value to governments and educational institutions trying to ensure that key jobs are filled and that people will be employable after they graduate.
The economic graph could also give companies greater insight into where to look for talent. It could tell them whether people with anthropology degrees do well in sales or if historians make good market researchers. It could also show how certain kinds of military experience translate to civilian jobs — something that employers and the armed forces would love to know.
We could also think about employee attrition. People who are looking for a new job typically go on a LinkedIn connection spree before they leave their existing company. If a CEO had insight into that risk (though hopefully not on an individual level), she could activate a company-wide save-program before losing key talent.
The economic graph could also impact investment by answering questions, such as who and where will my customers be in four years. It could suggest new locations for overseas facilities or give us ideas about where our products might be welcome. In fact, the possibilities for its use, not to mention monetization, are nearly endless.
Today, of course, the graph is still limited. LinkedIn has 400 million members, and relatively few in China, where it would need to be to deliver a full picture of the global economy. But the groundwork is already laid in North America and parts of Europe, where researchers using the data have uncovered where professionals are moving for work, what the gender gap is in various fields and industries where word of mouth matters most.
Rather than looking tactically at the ways in which the Microsoft’s and LinkedIn’s puzzle pieces fit now, we should be thinking strategically about what the combined companies could do with this data set in the future. When that happens, $26 billion may well look like a steal.
As CEO of Possible, Shane Atchison leads the company's long-term strategic vision of working with leading financial service organizations, consumer brands, startups, nonprofits and community-based organizations, helping each realize the potential of the internet and its impact on their business. Reach him @shanePOSSIBLE.
This article originally appeared on Recode.net.
