22.3.16

Your Online Attention, Bought in an Instant (3)

By NATASHA SINGER

YOU can be sold in seconds.
No, wait: make that milliseconds.
The odds are that access to you — or at least the online you — is being bought and sold in less than the blink of an eye. On the Web, powerful algorithms are sizing you up, based on myriad data points: what you Google, the sites you visit, the ads you click. Then, in real time, the chance to show you an ad is auctioned to the highest bidder.
Not that you’d know it. These days in the hyperkinetic world of digital advertising, all of this happens automatically, and imperceptibly, to most consumers.
Ever wonder why that same ad for a car or a couch keeps popping up on your screen? Nearly always, the answer is real-time bidding, an electronic trading system that sells ad space on the Web pages people visit at the very moment they are visiting them. Think of these systems as a sort of Nasdaq stock market, only trading in audiences for online ads. Millions of bids flood in every second. And those bids — essentially what your eyeballs are worth to advertisers — could determine whether you see an ad for, say, a new Lexus or a used Ford, for sneakers or a popcorn maker.
One big player in this space is the Rubicon Project. Never heard of it? Consider this: Rubicon, based in Los Angeles, has actually eclipsed Google in one crucial area — the percentage of Internet users in the United States reached by display ads sold through its platform, according to comScore, a digital analytics company.
Rubicon is among a handful of technology companies that have quietly developed automated ad sales systems for Web site operators. The bidders are marketers seeking to identify their best prospects and pitch them before they move to the next Web page. It is a form of high-frequency trading — that souped-up business of algorithm-loving Wall Streeters. But in this case, the prize is the attention of ordinary people. And it all depends on data-mining to instantly evaluate the audiences available to see those online display ads, the ones that appear on Web sites next to or around content.
In industry parlance, each digital ad space is an impression. The value of an impression depends on several factors, like the size of the ad, the type of person who is available to see it and that person’s location.
“The first impression seen by a high-value person on the opening page of a major newspaper first thing in the morning has a different value than a user from China who is 12 and has been on the Web all day long playing games,” says Frank Addante, the founder and chief executive of Rubicon.
Yet for most of us, real-time bidding is invisible. About 97 percent of American Internet users interact with Rubicon’s system every month, Mr. Addante says, and most of them aren’t aware of it.
That worries some federal regulators and consumer advocates, who say that such electronic trading systems could unfairly stratify consumers, covertly offering better pricing to certain people while relegating others to inferior treatment. A computer-generated class system is one risk, they say, of an ad-driven Internet powered by surveillance.
“As you profile more and more people, you’ll start to segregate people into ‘the people you can get money out of’ and ‘the people you can’t get money out of,’ ” says Dan Auerbach, a staff technologist at the Electronic Frontier Foundation, a digital civil rights group in San Francisco, who formerly worked in digital ad data-mining. “That is one of the dangers we should be worried about.”
Of course, ad agencies and brands can tailor ads to Web users without real-time bidding. They can also buy ads without aiming them at narrow audience groups. But for marketers, the marriage of ad- and audience-buying is one of the benefits of real-time bidding.
Not so long ago, they simply bought ad spaces based on a site’s general demographics and then showed every visitor the same ad, a practice called “spray and pray.” Now marketers can aim just at their ideal customers — like football fans who earn more than $100,000 a year, or mothers in Denver in the market for an S.U.V. — showing them tailored ads at the exact moment they are available on a specific Web page.
“We are not buying content as a proxy for audience,” says Paul Alfieri, the vice president for marketing at Turn, a data management companyand automated buy-side platform for marketers based in Redwood City, Calif. “We are just buying who the audience is.”
Still, for many consumer advocates, real-time bidding resembles nothing so much as a cattle auction.
“Online consumers are being bought and sold like chattel,” says Jeffrey Chester, the executive director of the Center for Digital Democracy, a consumer group in Washington that has filed a complaint about real-time bidding with the Federal Trade Commission. “It’s dehumanizing.”
FRANK ADDANTE is 36 years old and given to wearing black shirts with a white Rubicon logo on the front. Rubicon is the fifth company he has started or helped to found.
In 1996, in his dorm room at the Illinois Institute of Technology, he developed and introduced a search engine. He later helped found L90, a digital ad technology company that went public and was later acquired by DoubleClick. His fourth enterprise, StrongMail Systems, provides e-mail delivery infrastructure to large companies.
While working in ad technology, Mr. Addante says, he became puzzled by the manual ad sales processes that many Web sites were using. Just a few years ago, he recalled, many sites still executed their online ad deals through the cumbersome back-and-forth of meetings, phone calls, e-mails and even faxes. The fragmented market made it hard for ad agencies and brands.
“That market was very inefficient,” Mr. Addante said in an interview in Rubicon’s Manhattan office, “much like the early days of manual stock trading."



Rubicon’s customers now include ABC, eBay, CareerBuilder, Glam Media, Time Inc., the Drudge Report and Zynga. Its competitors include major players like PubMatic and Google’s DoubleClick ad exchange.
But Rubicon is not just a sales platform for Web site operators. It’s an analytics system that uses consumer data to help sites figure out how much their visitors are worth to advertisers.
Most sites, Mr. Addante explains, compile data about their own visitors through member registration or by placing bits of computer code called cookies on people’s browsers to collect information about their online activities. To those first-party profiles, Rubicon typically adds details from third-party data aggregators, like BlueKai or eXelate, such as users’ sex and age, interests, estimated income range and past purchases. Finally, Rubicon applies its own analytics to estimate the fair market value of site visitors and the ad spaces they are available to see.
The whole process typically takes less than 30 milliseconds.
“All these calculations have to happen before the Web page loads,” Mr. Addante says. “In our system, inventory is perishable.”
The competition for pricing accuracy has made companies involved in real-time bidding among the Internet’s most aggressive consumer trackers. Among the trackers setting the most cookies on the top 1,000 Web sites in the United States, for example, BlueKai was first, with 2,562 cookies, while Rubicon came in second, with 2,470, according toresearch conducted last month by the Berkeley Center for Law and Technology.
Consumer advocates say real-time bidding companies are acquiring and commoditizing all of that consumer data with little benefit to consumers themselves — and much digital snooping.
Mr. Addante and other industry executives disagree, saying consumers benefit by receiving ads and offers specifically relevant to them. Their systems do not invade privacy, they say, because they use numerical customer codes — not real names or other identifying details — to collect “anonymous” information about people’s online activities.
For many consumers, however, that Web and search history may seem personal, especially if they visit financial or health sites. Some computer scientists argue that the customer codes assigned to online users are unique ID’s, allowing companies to compile portraits about millions of people — without needing to know their names. Moreover, a few researchers have reported that many sites leak personal information, like names and addresses, to third-party trackers operating on their sites.
That means that rather than being anonymous, those customer code numbers are pseudonymous at best, some computer researchers say.
“It’s like a Social Security number, a number that businesses can use to recognize you on your future visits,” says Rob van Eijk, a computer science researcher at Leiden University in the Netherlands, where he is studying real-time bidding. Yet, he adds, consumers generally remain in the dark as to how automated trading systems rank and shunt them. “Envision a Kafkaesque future,” he said, “where decisions are being made about you and you don’t know what the criteria are based on.”
TICK. Tick. Tick. Tick.
The horizontal ticker at the bottom of Turn’s buy-side trading dashboard registers the groups of users available now to see ads — and lists the bids that Turn’s system recommends for access to them.
The ad spaces, or impressions, sell in lots of 1,000. The price depends on variables like the size and type of ad space, the type of user, and whether the user is in an urban or rural location.
One moment, Turn’s system recommends that an insurance customer bid up to $35.70 per lot being sold by Facebook Exchange, a Facebook service that auctions ad space on the social networking site, and $1.35 per lot being offered by AppNexus, another sell-side platform. That means Turn has identified Facebook’s lots as “premium inventory,” says Mr. Alfieri, Turn’s vice president for marketing, while AppNexus is selling ads on sites where little is known about the users available to see them.
Real-time dashboards like Turn’s, he says, have modernized the online ad trade in the same way that Bloomberg terminals revolutionized Wall Street trading. Ad agencies and brands can now check the intraday prices for various impressions. Many ad agencies have even created in-house “trading desks” to monitor and adjust their bids.
But Turn’s dashboard is more than a real-time ticker. It’s an analytics system that enables clients like insurers or car companies to identify common details among their best customer segments and then bid to show ads to people who resemble those best customers. The machine learning process gets better at pinpointing ideal audiences over the course of an ad campaign.
For example, Turn recently ran an ad campaign for a sneaker company that initially chose to buy a wide variety of impressions nationwide. But as Turn’s system analyzed the early sets of results, it began to separate audiences into the kinds of people who clicked on those sneaker ads, or later searched for the shoes on their own, and those who did not. Identifying common details among those people required the system to comb through its databank of nearly a billion user profiles for each transaction.
(Like Rubicon, Turn uses consumer data from third-party data aggregators for its analyses, Mr. Alfieri said, adding that the company has hired outside software services to strip names and other details from the profiles before Turn receives them).
The results of the sneaker campaign were surprising, says Bill Demas, the chief executive of Turn.
“It turned out that Republicans in certain districts of Texas basically did not exercise. We were able to adjust the campaign to try to aim more at Democrats,” Mr. Demas says. Without analyzing those user profiles, he says, “who would think that party affiliation would be an influence in advertising campaigns?”
In some ways, the consumer segmentation process is not as newfangled as it may seem. For decades in the bricks-and-mortar world, direct marketers have hired third-party data resellers to help them decide which customers should get catalogs or special offers in the mail. Real-time bidding is just a faster, smarter, more automated process for brands to find prospects likely to be the best fit for their products, says Joe Zawadzki, C.E.O. of MediaMath, a buy-side trading platform and data management company in Manhattan.
“How much is a rich person worth? To Mercedes, a lot. To a used Pinto dealer, not a lot,” he says. “It’s a different set of impressions for every marketer. That’s where the magic happens.”
But privacy advocates argue that real-time bidding is more problematic than direct mail because it often involves dozens of business-to-business companies — whose names most consumers have never heard of — collecting information and making instant decisions about them. The concern, advocates say, is that the very same automated bidding system that can distinguish coffee drinkers from, say, tea drinkers, and set different prices to show them ads, is also capable of distinguishing shopaholics or people in debt and potentially auctioning them to high-interest payday lenders.
“The reality looks like ‘we know a person is a sucker and they spend a lot of money on dumb things,’  ” says Mr. Auerbach of the Electronic Frontier Foundation. “Advertisers will spend more money to target them, and they aren’t savvy enough to know what is happening to them.”
AS real-time bidding gains traction, the consumer data-mining that fuels it is escalating. Yet that surge in surveillance may present a serious risk for online businesses.
The volume of data collection on the Web has surged 400 percent, from an average of 10 collections a page in 2011 to 50 a page this year, according to a study published last June by Krux, a company that helps businesses protect and monetize their consumer data. The report attributed the explosive growth to the ad industry’s shift to real-time bidding.
Krux also warned Web site operators about what it called “rogue data collection.” When publishers allow third parties, like real-time bidding platforms or information resellers, to collect data on their site, the report said, those partners often bring in other data miners whose practices the sites themselves cannot control. Those middlemen may use a site’s proprietary data to help competitors, the report said.
“Publishers who leak data leak revenue,” the report warned. “They face threats from middlemen who steal data and use it to create directly competitive audience-based offerings.”
Those threats may increase as real-time bidding moves more aggressively into mobile sites and apps, entities that may collect valuable information about users’ real-time locations and geographic patterns.
In May, Rubicon acquired Mobsmith, a start-up specializing in mobile ad technology. A few months later, the company announced that it wasintegrating real-time bidding for mobile ads into its system. Mr. Addante says he expects the industry to adopt real-time bidding for mobile ads faster than it had for desktop display ads. He also predicts that consumers will find tailored mobile ads for, say, a cafe or taxi in their vicinity, more pertinent than many Web ads tailored to them.
“I think mobile ads become more of an information provider than what is happening in display advertising where it has become a nuisance,” he says.
Yet the prospect of ubiquitous real-time bidding — online, on mobile devices and eventually on Web-enabled televisions — also hastens our transition to a totally traceable society. What we read and how we spend our spare time used to be private. Now those activities are becoming windows through which marketers scrutinize, appraise and vie to influence us for a price. Soon there may be no personal spaces left for our private thoughts.
“Real-time bidding creates the possibility for companies to tag you wherever you are going, without you knowing or having the ability to influence it,” says Mr. van Eijk, the computer scientist. “It is becoming a huge imbalance for the ordinary user because, in the end, the ordinary user is the product.”


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Mapping, and Sharing, the Consumer Genome (1)

IT knows who you are. It knows where you live. It knows what you do.
It peers deeper into American life than the F.B.I. or the I.R.S., or those prying digital eyes at Facebook and Google. If you are an American adult, the odds are that it knows things like your age, race, sex, weight, height, marital status, education level, politics, buying habits, household health worries, vacation dreams — and on and on.
Right now in Conway, Ark., north of Little Rock, more than 23,000 computer servers are collecting, collating and analyzing consumer data for a company that, unlike Silicon Valley’s marquee names, rarely makes headlines. It’s called the Acxiom Corporation, and it’s the quiet giant of a multibillion-dollar industry known as database marketing.
Few consumers have ever heard of Acxiom. But analysts say it has amassed the world’s largest commercial database on consumers — and that it wants to know much, much more. Its servers process more than 50 trillion data “transactions” a year. Company executives have said its database contains information about 500 million active consumers worldwide, with about 1,500 data points per person. That includes a majority of adults in the United States.
Such large-scale data mining and analytics — based on information available in public records, consumer surveys and the like — are perfectly legal. Acxiom’s customers have included big banks like Wells Fargo and HSBC, investment services like E*Trade, automakers like Toyota and Ford, department stores like Macy’s — just about any major company looking for insight into its customers.
For Acxiom, based in Little Rock, the setup is lucrative. It posted profit of $77.26 million in its latest fiscal year, on sales of $1.13 billion.
But such profits carry a cost for consumers. Federal authorities say current laws may not be equipped to handle the rapid expansion of an industry whose players often collect and sell sensitive financial and health information yet are nearly invisible to the public. In essence, it’s as if the ore of our data-driven lives were being mined, refined and sold to the highest bidder, usually without our knowledge — by companies that most people rarely even know exist.
Julie Brill, a member of the Federal Trade Commission, says she would like data brokers in general to tell the public about the data they collect, how they collect it, whom they share it with and how it is used. “If someone is listed as diabetic or pregnant, what is happening with this information? Where is the information going?” she asks. “We need to figure out what the rules should be as a society.”
Although Acxiom employs a chief privacy officer, Jennifer Barrett Glasgow, she and other executives declined requests to be interviewed for this article, said Ines Rodriguez Gutzmer, director of corporate communications.
In March,  however, Ms. Barrett Glasgow  endorsed increased industry openness. “It’s not an unreasonable request to have more transparency among data brokers,” she said in an interview with The New York Times.  In marketing materials, Acxiom promotes itself as “a global thought leader in addressing consumer privacy issues and earning the public trust.”
But, in interviews, security experts and consumer advocates paint a portrait of a company with practices that privilege corporate clients’ interests over those of consumers and contradict the company’s stance on transparency. Acxiom’s marketing materials, for example, promote a special security system for clients and associates to encrypt the data they send. Yet cybersecurity experts who examined Acxiom’s Web site for The Times found basic security lapses on an online form for consumers seeking access to their own profiles. (Acxiom says it has fixed the broken link that caused the problem.)
In a fast-changing digital economy, Acxiom is developing even more advanced techniques to mine and refine data. It has recruited talent from Microsoft, Google, Amazon.com and Myspace and is using a powerful, multiplatform approach to predicting consumer behavior that could raise its standing among investors and clients.
Of course, digital marketers already customize pitches to users, based on their past activities. Just think of “cookies,” bits of computer code placed on browsers to keep track of online activity. But Acxiom, analysts say, is pursuing far more comprehensive techniques in an effort to influence consumer decisions. It is integrating what it knows about our offline, online and even mobile selves, creating in-depth behavior portraits in pixilated detail. Its executives have called this approach a “360-degree view” on consumers.
“There’s a lot of players in the digital space trying the same thing,” saysMark Zgutowicz, a Piper Jaffray analyst. “But Acxiom’s advantage is they have a database of offline information that they have been collecting for 40 years and can leverage that expertise in the digital world.”
Yet some prominent privacy advocates worry that such techniques could lead to a new era of consumer profiling.
Jeffrey Chester, executive director of the Center for Digital Democracy, a nonprofit group in Washington, says: “It is Big Brother in Arkansas.”
SCOTT HUGHES, an up-and-coming small-business owner and Facebook denizen, is Acxiom’s ideal consumer. Indeed, it created him.
Mr. Hughes is a fictional character who appeared in an Acxiom investor presentation in 2010. A frequent shopper, he was designed to show the power of Acxiom’s multichannel approach.
In the presentation, he logs on to Facebook and sees that his friend Ella has just become a fan of Bryce Computers, an imaginary electronics retailer and Acxiom client. Ella’s update prompts Mr. Hughes to check out Bryce’s fan page and do some digital window-shopping for a fast inkjet printer.
Such browsing seems innocuous — hardly data mining. But it cues an Acxiom system designed to recognize consumers, remember their actions, classify their behaviors and influence them with tailored marketing.
Correctly typecast, Mr. Hughes buys the printer.
But the multichannel system of Acxiom and its online partners is just revving up. Later, it sends him coupons for ink and paper, to be redeemed via his cellphone, and a personalized snail-mail postcard suggesting that he donate his old printer to a nearby school.
Analysts say companies design these sophisticated ecosystems to prompt consumers to volunteer enough personal data — like their names, e-mail addresses and mobile numbers — so that marketers can offer them customized appeals any time, anywhere.
Still, there is a fine line between customization and stalking. While many people welcome the convenience of personalized offers, others may see the surveillance engines behind them as intrusive or even manipulative.
“If you look at it in cold terms, it seems like they are really out to trick the customer,” says Dave Frankland, the research director for customer intelligence at Forrester Research. “But they are actually in the business of helping marketers make sure that the right people are getting offers they are interested in and therefore establish a relationship with the company.”
DECADES before the Internet as we know it, a businessman named Charles Ward planted the seeds of Acxiom. It was 1969, and Mr. Ward started a data processing company in Conway called Demographics Inc., in part to help the Democratic Party reach voters. In a time when Madison Avenue was deploying one-size-fits-all national ad campaigns, Demographics and its lone computer used public phone books to compile lists for direct mailing of campaign material.
Today, Acxiom maintains its own database on about 190 million individuals and 126 million households in the United States. Separately, it manages customer databases for or works with 47 of the Fortune 100 companies. It also worked with the government after the September 2001 terrorist attacks, providing information about 11 of the 19 hijackers.
To beef up its digital services, Acxiom recently mounted an aggressive hiring campaign. Last July, it named Scott E. Howe, a former corporate vice president for Microsoft’s advertising business group, as C.E.O. Last month, it hired Phil Mui, formerly group product manager for Google Analytics, as its chief product and engineering officer.
In interviews, Mr. Howe has laid out a vision of Acxiom as a new-millennium “data refinery” rather than a data miner. That description posits Acxiom as a nimble provider of customer analytics services, able to compete with Facebook and Google, rather than as a stealth engine of consumer espionage.
Still, the more that information brokers mine powerful consumer data, the more they become attractive targets for hackers — and draw scrutiny from consumer advocates.
This year, Advertising Age ranked Epsilon, another database marketing firm, as the biggest advertising agency in the United States, with Acxiom second. Most people know Epsilon, if they know it at all, because it experienced a major security breach last year, exposing the e-mail addresses of millions of customers of Citibank, JPMorgan Chase, Target, Walgreens and others. In 2003, Acxiom had its own security breaches.
But privacy advocates say they are more troubled by data brokers’ ranking systems, which classify some people as high-value prospects, to be offered marketing deals and discounts regularly, while dismissing others as low-value — known in industry slang as “waste.”
Exclusion from a vacation offer may not matter much, says Pam Dixon, the executive director of the World Privacy Forum, a nonprofit group in San Diego, but if marketing algorithms judge certain people as not worthy of receiving promotions for higher education or health services, they could have a serious impact.
“Over time, that can really turn into a mountain of pathways not offered, not seen and not known about,” Ms. Dixon says.
Until now, database marketers operated largely out of the public eye. Unlike consumer reporting agencies that sell sensitive financial information about people for credit or employment purposes, database marketers aren’t required by law to show consumers their own reports and allow them to correct errors. That may be about to change. This year, the F.T.C. published a report calling for greater transparency among data brokers and asking Congress to give consumers the right to access information these firms hold about them.
ACXIOM’S Consumer Data Products Catalog offers hundreds of details — called “elements” — that corporate clients can buy about individuals or households, to augment their own marketing databases. Companies can buy data to pinpoint households that are concerned, say, about allergies, diabetes or “senior needs.” Also for sale is information on sizes of home loans and household incomes.
Clients generally buy this data because they want to hold on to their best customers or find new ones — or both.
A bank that wants to sell its best customers additional services, for example, might buy details about those customers’ social media, Web and mobile habits to identify more efficient ways to market to them. Or, says Mr. Frankland at Forrester, a sporting goods chain whose best customers are 25- to 34-year-old men living near mountains or beaches could buy a list of a million other people with the same characteristics. The retailer could hire Acxiom, he says, to manage a campaign aimed at that new group, testing how factors like consumers’ locations or sports preferences affect responses.
But the catalog also offers delicate information that has set off alarm bells among some privacy advocates, who worry about the potential for misuse by third parties that could take aim at vulnerable groups. Such information includes consumers’ interests — derived, the catalog says, “from actual purchases and self-reported surveys” — like “Christian families,” “Dieting/Weight Loss,” “Gaming-Casino,” “Money Seekers” and “Smoking/Tobacco.” Acxiom also sells data about an individual’s race, ethnicity and country of origin. “Our Race model,” the catalog says, “provides information on the major racial category: Caucasians, Hispanics, African-Americans, or Asians.” Competing companies sell similar data.
Acxiom’s data about race or ethnicity is “used for engaging those communities for marketing purposes,” said Ms. Barrett Glasgow, the privacy officer, in an e-mail response to questions.
There may be a legitimate commercial need for some businesses, like ethnic restaurants, to know the race or ethnicity of consumers, says Joel R. Reidenberg, a privacy expert and a professor at the Fordham Law School.
“At the same time, this is ethnic profiling,” he says. “The people on this list, they are being sold based on their ethnic stereotypes. There is a very strong citizen’s right to have a veto over the commodification of their profile.”
He says the sale of such data is troubling because race coding may be incorrect. And even if a data broker has correct information, a person may not want to be marketed to based on race.
“DO you really know your customers?” Acxiom asks in marketing materials for its shopper recognition system, a program that uses ZIP codes to help retailers confirm consumers’ identities — without asking their permission.
“Simply asking for name and address information poses many challenges: transcription errors, increased checkout time and, worse yet, losing customers who feel that you’re invading their privacy,” Acxiom’s fact sheet explains. In its system, a store clerk need only “capture the shopper’s name from a check or third-party credit card at the point of sale and then ask for the shopper’s ZIP code or telephone number.” With that data Acxiom can identify shoppers within a 10 percent margin of error, it says, enabling stores to reward their best customers with special offers. Other companies offer similar services.
“This is a direct way of circumventing people’s concerns about privacy,” says Mr. Chester of the Center for Digital Democracy.
Ms. Barrett Glasgow of Acxiom says that its program is a “standard practice” among retailers, but that the company encourages its clients to report consumers who wish to opt out.
Acxiom has positioned itself as an industry leader in data privacy, but some of its practices seem to undermine that image. It created the position of chief privacy officer in 1991, well ahead of its rivals. It even offers an online request form, promoted as an easy way for consumers to access information Acxiom collects about them.
But the process turned out to be not so user-friendly for a reporter for The Times.
In early May, the reporter decided to request her record from Acxiom, as any consumer might. Before submitting a Social Security number and other personal information, however, she asked for advice from a cybersecurity expert at The Times. The expert examined Acxiom’s Web site and immediately noticed that the online form did not employ a standard encryption protocol — called https — used by sites like Amazon and American Express. When the expert tested the form, using software that captures data sent over the Web, he could clearly see that the sample Social Security number he had submitted had not been encrypted. At that point, the reporter was advised not to request her file, given the risk that the process might expose her personal information.
Later in May, Ashkan Soltani, an independent security researcher and former technologist in identity protection at the F.T.C., also examined Acxiom’s site and came to the same conclusion. “Parts of the site for corporate clients are encrypted,” he says. “But for consumers, who this information is about and who stand the most to lose from data collection, they don’t provide security.”
Ms. Barrett Glasgow says that the form has always been encrypted with https but that on May 11, its security monitoring system detected a “broken redirect link” that allowed unencrypted access. Since then, she says, Acxiom has fixed the link and determined that no unauthorized person had gained access to information sent using the form.
On May 25, the reporter submitted an online request to Acxiom for her file, along with a personal check, sent by Express Mail, for the $5 processing fee. Three weeks later, no response had arrived.
Regulators at the F.T.C. declined to comment on the practices of individual companies. But Jon Leibowitz, the commission chairman, said consumers should have the right to see and correct personal details about them collected and sold by data aggregators.
After all, he said, “they are the unseen cyberazzi who collect information on all of us.”
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Secret E-Scores Chart Consumers’ Buying Power (2)

By NATASHA SINGER
AMERICANS are obsessed with their scores. Credit scores, G.P.A.’s, SAT’s, blood pressure and cholesterol levels — you name it.
So here’s a new score to obsess about: the e-score, an online calculation that is assuming an increasingly important, and controversial, role in e-commerce.
These digital scores, known broadly as consumer valuation or buying-power scores, measure our potential value as customers. What’s your e-score? You’ll probably never know. That’s because they are largely invisible to the public. But they are highly valuable to companies that want — or in some cases, don’t want — to have you as their customer.
Online consumer scores are calculated by a handful of start-ups, as well as a few financial services stalwarts, that specialize in the flourishing field of predictive consumer analytics. It is a Google-esque business, one fueled by almost unimaginable amounts of data and powered by complex computer algorithms. The result is a private, digital ranking of American society unlike anything that has come before.
It’s true that credit scores, based on personal credit reports, have been around for decades. And direct marketing companies have long ranked consumers by their socioeconomic status. But e-scores go further. They can take into account facts like occupation, salary and home value to spending on luxury goods or pet food, and do it all with algorithms that their creators say accurately predict spending.
A growing number of companies, including banks, credit and debit card providers, insurers and online educational institutions are using these scores to choose whom to woo on the Web. These scores can determine whether someone is pitched a platinum credit card or a plain one, a full-service cable plan or none at all. They can determine whether a customer is routed promptly to an attentive service agent or relegated to an overflow call center.
Federal regulators and consumer advocates worry that these scores could eventually put some consumers at a disadvantage, particularly those under financial stress. In effect, they say, the scores could create a new subprime class: people who are bypassed by companies online without even knowing it. Financial institutions, in particular, might avoid people with low scores, reducing those people’s access to home loans, credit cards and insurance.
It might seem strange that one innovator in this sphere has blossomed here in St. Cloud, a world away from the hothouse of Silicon Valley. It is called eBureau, and it develops eScores — its name for custom scoring algorithms — to predict whether someone is likely to become a customer or a money-loser. Gordy Meyer, the founder and chief executive, says his system needs less than a second to size up a consumer and to transmit his or her score to an eBureau client.
“It’s like gambling,” Mr. Meyer says. “It’s a game of odds, when to double down and when to pass.”
Every month, eBureau scores about 20 million American adults on behalf of clients like banks, payday lenders and insurers, looking to buy the names of prospective customers. An eBureau spinoff called TruSignal, also located here, scores about 110 million consumers monthly for advertisers seeking select audiences for online ads. Mr. Meyer says eBureau’s clients use the scores to answer basic business questions about their potential audience.
“Are they legitimate?” Mr. Meyer asks. “Are they worth pursuing? Are they worth spending money on?” The scores, he adds, are generated without using federally regulated consumer data and are not used to make credit decisions about consumers. (Using regulated credit data for marketing purposes could run afoul of federal law.)
Such assurances aside, consumer value scores have begun to trouble some federal regulators. One of their worries is that these scores, which have spread quietly through American business, measure individuals against one another, using yardsticks that are essentially secret. Another is that the scores could pigeonhole people, limit their financial choices and channel some into predatory loans, they say.
“The scoring is a tool to enable financial institutions to make decisions about financing based on unconventional methods,” says David Vladeck, the director of the bureau of consumer protection at the Federal Trade Commission. “We are troubled by these practices.”
Federal law governs the use of old-fashioned credit scores. Companies must have a legally permissible purpose before checking consumers’ credit reports and must alert them if they are denied credit or insurance based on information in those reports. But the law does not extend to the new valuation scores because they are derived from nontraditional data and promoted for marketing.
Ed Mierzwinski, consumer program director at the United States Public Interest Research Group in Washington, worries that federal laws haven’t kept pace with change in the digital age.
“There’s a nontransparent, opaque scoring system that collects information about you to generate a score — and what your score is results in the offers you get on the Internet,” he says. “In most cases, you don’t know who is collecting the information, you don’t know what predictions they have made about you, or the potential for being denied choice or paying too much.”
ON the ground floor of eBureau’s headquarters are the company’s prized assets: several hundred computer processors that analyze billions of details about consumers every month. EBureau has built a glass enclosure on a raised platform to showcase the machines. From the dimly lit viewing hall, tiny green and blue lights flicker behind glass.
Mr. Meyer at a LeadsCon conference. He says eBureau’s system needs less than a second to size up a consumer and transmit his or her eScore. Tina Fineberg for The New York Times
Like many facets of eBureau, the idea of putting the processors on a pedestal came from Mr. Meyer, 51, whose relaxed uniform of jeans and cotton shirts belies the methodological decider underneath.

“Traditional ways to evaluate credit didn’t exist on half of them,” he recalls. “So Fingerhut had to come up with a way to decide who they mailed catalogs to and who they ultimately approved orders to.”
Back then, he says, Fingerhut evaluated creditworthiness based in part on how people filled out order forms. Those who used pens were seen as safer bets than those who used pencils. People who used a middle initial were considered better credit risks than those who didn’t. After an analysis by Mr. Meyer, he says, the company also began scoring first-time customers based on whether their phones were connected and their phone numbers legitimate. (Those whose phones did not work were considered at high risk of defaulting on payments.)
Using these different scoring techniques, Mr. Meyer says, Fingerhut could efficiently tailor its catalogs and offers to different customers; decide whether to approve or decline certain product orders; or choose which customer debts to collect on or write off.
“Without Fingerhut,” Mr. Meyer says, “I would never be in this business.”(Fingerhut is now an online and catalog retailer.)
In the 1990s, Mr. Meyer decided to use his expertise in spotting patterns of fraud to start RiskWise, an analytics enterprise of his own. After selling it, and two other companies, to LexisNexis in 2000 for about $89 million, he founded another start-up: a predictive analytics company that would become eBureau.
EVERY business needs customers. But how do you find them, and how do you know they will be good ones? In 2006, Mr. Meyer began to answer that question by carving a niche for himself in a nascent online industry called “lead generation.”
Lead generators are companies that set up consumer-friendly Web sites with the goal of funneling potential customers to businesses ranging from financial institutions to wedding photographers. It is a multibillion-dollar industry in the United States, says Jay Weintraub, chief executiveof LeadsCon, a conference for Web sites that specializes in online customer acquisition.
Lead-generation sites like Bankrate.com, for example, offer rate calculators and other tools that prompt people to fill out forms with their names and contact information. The sites then transmit those consumers’ information to mortgage brokers, credit card issuers, car insurers and the like, offering access to these prospective customers, or leads, in return for a finder’s fee. The price varies. Lead generators may charge $8 for an insurance prospect; $35 for a finance lead; or $75 for a mortgage prospect, Mr. Meyer says.
But, he says, some companies were buying more than 100,000 leads a month without being able to distinguish one from another. They couldn’t sort potentially profitable customers from window-shoppers and fakes.
“Are people who are filling out the forms telling the truth? Because Yogi Bear and Fred Flintstone don’t buy a lot of stuff,” Mr. Meyer says. “Companies needed to figure out whether these leads were quality or not.”
Big national and international brands, Mr. Meyer knew, already employed data analytics to rate consumers. To distinguish his firm, he developed eBureau to offer customized scoring systems to midsize companies.
Here’s how eScores work:
A client submits a data set containing names of tens of thousands of sales leads it has already bought, along with the names of leads who went on to become customers. EBureau then adds several thousand details — like age, income, occupation, property value, length of residence and retail history — from its databases to each customer profile. From those raw data points, the system extrapolates up to 50,000 additional variables per person. Then it scours all that data for the rare common factors among the existing customer base. The resulting algorithm scores prospective customers based on their resemblance to previous customers.
EScores might range from 0 to 99, with 99 indicating a consumer who is a likely return on investment and 0 indicating an unprofitable one. But in some industries, “knowing the bottom is more important than knowing the top,” Mr. Meyer says. In online education, for instance, scores help schools winnow prospective students who are not worth the investment of expensive course catalogs or attentive follow-up calls — like people who use fake names or adopt the identities of relatives.
“If we can find 25 percent who have zero chance of enrolling, we can say ‘don’t waste your money on them,’ ” he says.
EBureau charges clients 3 to 75 cents a score, depending on the industry and the volume of leads.
Such scores increase the accuracy and speed with which companies can identify potential customers, says Mr. Weintraub of the LeadsCon conference.
“Scores tell you ‘this person might actually qualify, so let’s focus on them,’ ” he says. “This way you are not focusing on people who really can’t qualify.”
MOST people never see their value scores. But some services openly discuss how their measurements work. A case study on the eBureau site, for example, describes how the company ranked prospective customers for a national prepaid debit card issuer, assigning each a score of 0 to 998. People who scored above 950 were considered likely to become highly profitable customers, generating revenue over six months of an estimated $213 per card. Those who scored less than 550 were predicted to be unprofitable clients, with estimated revenue of $74 or less. With e-Bureau’s system, the card issuer could identify and court the high scorers while avoiding low scorers.
TargusInfo, a subsidiary of Neustar that is an eBureau competitor, is even more explicit about how a multinational credit card issuer used its scores.
According to a case study on its site, TargusInfo instantly scores prospective customers who call the card company’s call centers, selecting the kind of card to offer even before an agent picks up the phone. The scores also alert agents to high-value prospects, people “who are more likely to apply, be approved, request supplemental cards or spend more in their first year,” the case study says. While high-value callers are immediately routed to dedicated agents, it says, “less-qualified callers no longer waste the valuable time of the card issuer’s dedicated agents and are routed to an outsourced overflow call center.”
Becky Burr, chief privacy officer of Neustar, sees TargusInfo’s scoring system as a modern incarnation of marketing services to help companies find and communicate with their audiences.
“They want to allocate their marketing money efficiently, and consumers want messages that are relevant,” she says. The scores, she adds, should be seen as predictions about groups of consumers, not judgments on individuals.
For companies, this kind of scoring clearly increases the speed and reduces the cost of acquiring customers. But consumers are paying a heavy price for that increased corporate efficiency, public interests advocates say.
The digital scores create a two-tiered system that invisibly prioritizes some online users for credit and insurance offers while denying the same opportunities to others, says Mr. Mierzwinski of the Public Interest Research Group. The decades-old federal law that protects consumers from unfair credit practices, he says, has not kept pace with online innovation.
The Fair Credit Reporting Act requires that consumer reporting agencies, the companies that compile credit data, show people their credit reports and allow them to correct errors. Companies that use the reports must notify consumers if they take adverse action based on information in those reports. But digital marketers, Mr. Mierzwinski says, are able to work around the rules by using alternative financial data to calculate consumer scores. In an article scheduled to be published next spring in the Suffolk University Law Review, Mr. Mierzwinski and a co-author argue that new digital techniques like scoring let sales agents rapidly convert online prospects to customers, blurring the line between marketing and actual credit offers.
“The relationship between marketing and making a distinct offer of credit to a consumer is becoming blurred given contemporary digital marketing practices,” Mr. Mierzwinski and his co-author, Jeffrey Chester of theCenter for Digital Democracy, write in the article. Federal regulators, they add, “should ensure consumers know whether and how they have been secretly scored or rated by the digital financial marketers, especially those labeled as less profitable or desirable.”
Mr. Meyer and other eBureau executives disagree, saying the concerns are misplaced.
EBureau, Mr. Meyer says, went to great lengths to build a system with both regulatory requirements and consumer privacy in mind. The company, he says, has put firewalls in place to separate databases containing federally regulated data, like credit or debt information used for purposes like risk management, from databases about consumers used to generate scores for marketing purposes.
He adds that eBureau’s clients use the scores only to narrow their field of prospective customers — not for the purposes of approving people for credit, loans or insurance. Moreover, he says, the company does not sell consumer data to others, nor does it retain the scores it transmits to clients.
“We are an evaluator,” Mr. Meyer says. “We are trying to stay away from being intrusive to the consumer.”
AT a LeadsCon conference in Midtown Manhattan last month, eBureau was among those making its sales pitch. Its exhibition booth depicted a multiethnic group of fictional consumers and their hypothetical scores.
Score boxes superimposed over a young African-American male read variously: “eScore: 811, high lifetime value potential” and “eScore: 524, underbanked, but safe credit risk.” Another caption floating over the crowd read: “eScore: 906, route to best call center agent NOW!”
It’s just another sign of the rise of what might be called the Scored Society. Google ranks our search results by our location and search history. Facebook scores us based on our online activities. Klout scores usby how many followers we have on Twitter, among other things.
And now e-scores rank our potential value to companies.
But the spread of consumer rankings raises deep questions of fairness, says Frank Pasquale, a professor at Seton Hall University School of Law, who is writing a book about scoring technologies. The scores may help companies, he says. But over time, they may send some consumers into a downward spiral, locking them into a world of digital disadvantage.
“I’m troubled by the idea that some people will essentially be seeing ads for subprime loans, vocational schools and payday loans,” Professor Pasquale says, “while others might be seeing ads for regular banks and colleges, and not know why.”
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