University of Missouri School of Law Scholarship Repository Faculty Publications 2014 Secret Consumer Scores and Segmentations: Separating Consumer 'Haves' from 'Have-Nots' Amy J. Schmitz University of Missouri School of Law,
[email protected] Follow this and additional works at: http://scholarship.law.missouri.edu/facpubs Part of the Law and Society Commons, and the Legal Remedies Commons Recommended Citation Amy J. Schmitz, Secret Consumer Scores and Segmentations: Separating "Haves" from "Have-Nots", 2014 Mich. St. L. Rev. 1411 (2014) This Article is brought to you for free and open access by University of Missouri School of Law Scholarship Repository. It has been accepted for inclusion in Faculty Publications by an authorized administrator of University of Missouri School of Law Scholarship Repository. SECRET CONSUMER SCORES AND SEGMENTATIONS: SEPARATING "HAVES" FROM "HAVE-NOTS" Amy J Schmitz* 2014 MICH. ST. L. REV. 1411 ABSTRACT "Big Data" is big business. Data brokers profit by tracking consumers' information and behavior both on- and offline and using this collected data to assign consumers evaluative scores and classify consumers into segments. Companies then use these consumer scores and segmentationsfor marketing and to determine what deals, offers, and remedies they provide to different individuals. These valuations and classifications are based on not only consumers 'financial histories and relevant interests, but also their race, gender, ZIP Code, social status, education,familial ties, and a wide range of additional data. Nonetheless, consumers are largely unaware of these scores and segmentations, and generally have no way to challenge their veracity because they usually fall outside the purview of the Fair Credit Reporting Act (FCRA).