This is the second part in a three-part series that will run this week at HuffPost on why lost privacy online matters for economic equity in our economy. The first part looked at the ways lost privacy leads to greater economic inequality in our economy and how Google users are encouraged to give up that personal data without recognizing its real value.
While many commentators focus on how individuals use various Google tools, but those tools are not Google's business but a way to encourage those individual users to part with personal data, which can then be resold to advertisers. The question is why user information is so useful to companies and why they pay Google so much for the precision in user targeting that it can deliver.
"Pain Points" and Price Discrimination: The nicest version of why companies pay so much is that it helps them find the customers most likely to be interested in their products, and that's no doubt part of it. But the darker version is that it also helps them differentiate between different customer segments and target particular offers to different audiences. One great advantage of online marketing is that it facilitates what economists call "price discrimination", selling the same exact good at a variety of prices. This is based on the reality that people have different maximum prices that they are willing to pay, a so-called "paint point" after which they won't buy the product.
The ideal for a seller would be to sell a product to each customer at their individual "pain point" price. With public advertising, a customer willing to pay a higher price will demand the lower price advertised to someone else. However, datamining and targeted Internet advertising allows sellers to make different advertising offers to particular groups of consumers based on correlations derived from past behavior. The New York Times recently profiled how web coupons are used in a similar manner to target offers based on user behavior. As Ed Mierzwinski, consumer program director for the United States Public Interest Research Group (USPIRG) noted, companies "offer you, perhaps, less desirable products than they offer me, or offer you the same product as they offer me but at a higher price." USPIRG is asking the Federal Trade Commission for tighter rules on all online advertising precisely because of this problem.
Behavioral Tracking and Google: Such an approach does not require sellers to know who any individual user is -- and Google makes a big deal about not sharing personally identifiable data about individuals with advertisers. But given a company database on how different groups interact with their product, any general data shared by Google with advertisers will pay off in maximizing profit extracted from customers.
Technology consultant Ahmadali Arabshahi gives an example of how such behavioral tracking works for Google in creating a profile for advertisers: "If a user frequents websites with information on how to save money then Google would know that the user is price sensitive. But if a Gmail user receives a reservation confirmation email from a very expensive restaurant then Google would conclude that the user is price insensitive." He sees Google's launch into Groupon-like Offers working with local businesses as a way for the company to directly cash in on that data.
As early as 2005, Google was applying for patents on how to sell advertising based on such behavioral tracking, where as one patent specified, "advertisements are personalized in response to a search profile that is derived from personalized search results. The search results are personalized based on a user profile of the user providing the query. "
Google is now working with advertisers so they can coordinate datamining information those companies have created based on particular demographic groups independently with the profiling Google develops on users based on their previous browsing activity, behavior and location. Google began a beta test of this capability two years ago back in 2009 and has been introducing it to different groups of advertisers over time.
All of this means that companies working with Google can more and more effectively divide the market into thousands of segments and target advertising and offers to maximize the price paid by each demographic and interest group they can identify.
Reempowering Racial Discrimination: This targeted price discrimination based on behavioral tracking, unfortunately, directly enhances the most traditional kinds of racial discrimination. Study after study has shown that employers, financial lenders, car salesmen and other merchants continue to charge black and Hispanic customers more for the same service when they can identify them.
For example, a study by the Urban Institute using paired "testers" -- one white person and one person of color with similar economic profiles -- found that non-white homebuyers received less favorable financial terms from mortgage lending institutions. Job seekers face similar discrimination with one study, where nearly identical resumes were sent to 1300 help-wanted ads, found that resumes with a "white-sounding" name were 50 percent more likely to get a call for an interview than one with a black-sounding name.
The Internet was supposed to let people escape such easy discrimination, but behavioral tracking makes such identification trivial. Add together someone's taste in music and a few more characteristics and you have an almost perfect proxy for race. As Rebecca Goldin, a George Mason University professor, argued in a 2009 article, it's clearly illegal to discriminate based on race, but if companies offer loan rates based on their shopping habits, it raises the question of "would it be legal or ethical to use the kind of music one buys to determine his or her loan rate?"
Given that we know straight up racial discrimination happens all the time in these commercial transactions, what the Internet supplies is a multivariate datamining opportunity to discriminate in ever more precise ways that may largely escape legal scrutiny.
Part 3 of this series looks at the role of Google in the subprime mortgage debacle and its aftermath, as well as the broader antitrust implications of the company's dominant role as an intermediary for behavioral targeting of consumers by advertisers.