Case: Capital One’s Online Profiles
Listen to the Audio
In 2010, Capital One Financial Corporation began using specialsoftware to createinstantaneous profiles of visitors to itswebsite. Constructed from information such as recent purchases, webbrowsing history, and geographic location, these profiles were usedmainly to determine which credit card offers to display on avisitor’s computer screen.136
Customer Profiles
In the case of one customer, Carrie Isaac, Capital One’s websiteused “cookies” left by other websites, her Internet Protocol (IP)address, and other technical information transmitted by hercomputer to conclude that she was a member of the “White PicketFences” group, a profile for customers who are thought to bemiddle-class parents who live in a metropolitan suburb and havereliable creditworthiness. Capital One used sophisticatedalgorithms to determine correctly that she was female and a youngparent and that she earned approximately $50,000 annually, hadattended, and shopped at discount department stores. On the basisof this information, Capital One’s software displayed a credit carddesigned for people of average creditworthiness with no annual feeand an initial monthly interest rate of zero percent, increasing to19.8 percent thereafter. Overall, Capital One’s inferences aboutMs. Isaac’s identity were accurate.
The same appeared to be true of another potential customer, PaulBoulifard. Capital One’s website focused on Mr. Boulifard’sresidence in Nashville, Tennessee, and his interest in travel. Itdisplayed the “VentureOne Rewards” credit card to him, which allowsthe accumulation of points that can be used to purchase airlinetickets. The images surrounding this card included a beach sceneand the slogan “Still Searching? Get double miles withVenture.”
In the case of Karyn Morton, however, Capital One’s software wasless accurate. Ms. Morton was profiled as a member of the “CityRoots” segment. Capital One accurately determined that she was ahomeowner living in Detroit, a member of the National Associationfor the Advancement of Colored People (NAACP), and a regular readerof major newspapers. It inaccurately inferred that Ms. Morton wasretired without children, had little education, and was living on amodest income of $28,000. She actually earned three times thatamount, was 33 years old, and held a law degree. Capital Oneoffered Ms. Morton two credit card options, one for individualswith average credit scores and an interest rate of 24.9 percent andone for customers with excellent credit scores and an interest rateof 13.9 percent.
Use of Profiles
Capital One emphasized at the time that it did not use theinformation gathered in a visitor’s online profile to determine whoactually received certain lines of credit. It used only theconcrete information voluntarily offered by a customer on a creditapplication for such purposes. Capital One, therefore, did notviolate the Equal Opportunity Credit Act, a federal law thatprohibits banks and other lenders from targeting or restrictingfinancial services based on race, ethnicity, national origin, orresidency.137 Capital One claimed that it simply made an “educatedguess” about what it thought customers would want and featuredproducts based on those inferred preferences.138
Capital One’s efforts at product placement were not unique.Other online retailers have used similar methods in setting onlineprices.
In 2012, Orbitz, theonline travel site that provides low-priced deals on car rentals,hotel rooms, and airfares, offered the same products to differentcustomers at different prices.
Customers who useddesktop computers with an Apple operating system paid 30 percentmore for hotel rooms compared with customers who booked the samerooms using computers with a Microsoft operating system.139
The office supplygiant Staples has sold products at different prices depending upona customer’s proximity to competitors’ stores. A recentinvestigation found that theStaples.com website displayed differentprices to different people by “estimating” their location based ontheir computer’s IP address. Staples considered the distance from acompetitor’s store, such as OfficeMax or Office Depot, and if astore was located within 20 miles, then a discounted price wasshown.
Profiling Technology
Capital One arguably refined a common practice. Marketingdecisions involving product placement and pricing have long beenguided by the concept of “segmentation.” The marketplace iscomposed of groups of customers—or segments—with differentexperiences, demographic traits, and preferences. The rise ofinformation technology and e-commerce has enabled marketers tomodify the manner in which they sell products based on theirknowledge of the segment to which a potential customer belongs.Segments provide a useful, if imperfect, guide to quickly predict acustomer’s likely purchases.
Capital One’s software was engineered by a little-knownsupplier, [x+1], Inc. Neither this fact nor the exact methodsemployed by the profiling software were disclosed to visitors onthe website. Capital One did disclose that it collected and usedvisitors’ IP addresses, browser and operating system information,“cookies” placed by other websites, navigation preferences, socialmedia activity, and geographic data. These disclosures, however,were placed within the “privacy” section of Capital One’s website,located at the bottom of the user’s screen in small font. This istypical in the online commercial environment. Internet users arerarely cognizant of how they are being profiled, and privacydisclosures are not easy to find without some effort.141 Users alsoexpect their online activity to take place in a market thatprovides impersonal, even anonymous, interaction. This expectationis apparently important to Internet users. Marketing studies142indicate that consumers typically find product and pricecustomization problematic when there is a lack of transparencyregarding the customization efforts. When consumers expectstandardized sales experiences, customized experiences areconsidered unfair, but if there is an expectation that productoffers or prices will differ between consumers, then variations areperceived as less problematic.143
Capital One’s algorithms were focused exclusively on theinformation that could be gleaned from visitors’ computers at themoment that they started using Capital One’s website. More advancedtechnology exists, however, which can combine the up-front dataprovided by a visitor’s computer, web browser and IP address withlarger sources of data that contain historical records of Internettransactions, in-person retail purchases, and e-mail addresses.144This technology could conceivably enable customer profiling thatcombines online with offline behavior. It also holds the prospectof eliminating anonymity in Internet transactions. As more data,such as ZIP codes, telephone numbers, birth dates, e-mailaddresses, and online social activities, are accessed and used byonline advertisers, the accuracy with which companies can place acustomer within a segment, or even construct a concrete identityprofile, is increased. This capability would expand and refine theability of companies like Capital One to customize experiences foreach consumer.
Question: What is the problem of this case. Does Capital One'shave any issued that use customer online profile to clarify theirrequirement? Can you point out of each problems of this case?
