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It has become the Internet’s defining business model: free online services make their money by feeding on all the personal data generated by their users. Think Facebook, Google, and LinkedIn, and how they serve targeted ads based on your preferences and interests, or make deals to share collected data with other companies (see “What Facebook Knows”).

Before the end of this year, Web users should be able to take a more active role in monetizing their personal data. Michael Fertik, cofounder and CEO of startup Reputation.com, says his company will launch a feature that lets users share certain personal information with other companies in return for discounts or other perks. Allowing airlines access to information about your income, for example, might lead to offers of loyalty points or an upgrade on your next flight.

The idea that individuals might personally take charge of extracting value from their own data has been discussed for years, with Fertik a leading voice, but it hasn’t yet been put to the test. Proponents say it makes sense to empower users this way because details of what information is collected, how it is used, and what it is worth are unjustly murky, even if the general terms of the relationship with data-supported companies such as Facebook is clear.

“The basic business model of the Internet today is that we’re going to take your data without your knowledge and permission and give it to people that you can’t identify for purposes you’ll never know,” says Fertik.

Fertik says he has spoken with a range of large companies and their marketers who are interested in his impending “consumer data vault,” as the new feature is called. He won’t yet give specifics about what data people will be able to trade, or what for, but he did tell MIT Technology Review that major airlines like the idea. “All of the airlines we talked to would like to be able to extend provisional platinum status to certain types of fliers to get some kind of loyalty,” he says. “It’s very hard for airlines to gain a sense of who is worth [it] today.”

Reputation.com was founded in 2006 and has received $67 million in investment funding. It currently offers products that help individuals and companies find information about themselves on the Internet and in various proprietary databases. For a fee, the company will also try to remove records or information, a service enabled in part by deals that Fertik has struck with some data-holding companies.

Fertik says those existing products, which have around one million users, mean that many people already have data in Reputation.com’s service that they could trade with other companies in return for special offers. That data can include home and family addresses, buying habits, professional histories, and salary and income information.

Reputation.com has far fewer users than Facebook, of course, but Fertik says the data people have given his company can be more valuable to marketers than clicks on a like button. Reputation.com has also filed patents on data-mining techniques intended to identify valuable insights in people’s data vaults.

Peter Fader, a professor at the University of Pennsylvania’s Wharton School of Business, who specializes in the use of data analysis to help marketing, is skeptical that Reputation.com’s approach offers enough to tempt either consumers or companies.

“Despite the ways that companies delude themselves, demographics and other personal descriptors are rarely useful,” he says. Data that captures customer behavior is much more important, says Fader, and many companies already have plenty of that flowing in from the various ways they interact with customers.

As for consumers, Fader predicts that, even as companies like Facebook expand how they share and leverage information gathered from users, relatively few will be motivated to actively manage and trade a portfolio of their own data. “The effort required to manage your personal data will be seen as greater than the benefits that arise from doing so,” he says.

Shane Green, CEO and cofounder of startup Personal, which provides a website and apps for people to store personal data, disagrees. His company currently has less than a million users, and he says the growing prominence of privacy issues in the media shows that many people do care about what happens to their data.

Green once spoke of launching a service similar to the one planned by Reputation.com (see “A Dollar for Your Data”) but now has different plans. Still, he says that Fertik’s vision makes sense. “I think there will actually be a lot of those marketplaces,” he says. “Marketing will shift toward more permission-based opportunities.”

Green cites the date that a person’s car lease expires as an example of a piece of personal data with an established value that people control themselves. “There’ll only be one car company that knows that,” he says. “But companies will pay hundreds of dollars, if you are seriously going to buy a car, to incent you to do that.”

Personal, based in Washington, D.C., and founded in 2009, has raised $15.7 million in investments and debt financing. The site currently focuses on helping people collate and reuse data—for example, for completing applications for college and loans.

Green says that he intends to develop infrastructure so people can selectively share data with another company, perhaps in return for discounts or other benefits. Similar to how a person might use a Facebook or Google account to log into a website, he might use a Personal account to connect with a company. He could then control exactly what data that company could access, and for how long. An early iteration of this idea can be seen on the website Car and Driver, where its already possible to log in with a Personal account. Doing so leads to a permissions screen where the site requests access to details including the make, model, and year of a person’s vehicle. “[Data] marketplaces are going to be incredibly valuable, but we’re focused on portability,” says Green.

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Credit: Maximilian Bode

Tagged: Computing, Communications, Web, privacy, big data, personal data, data science

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