Surveys show significant public concern regarding information privacy. To better understand how consumer concerns vary by type of personal data, the authors created a typology of information types based on perceived associated risks. In a national consumer survey, 52 information types were analyzed along four perceived risk categories (physical, psychological, monetary, and social), consumers' overall sensitivity regarding the information, and their willingness to provide it. This resulted in six highly distinctive clusters—Basic Demographics, Personal Preferences, Contact Information, Community Interaction, Financial Information, and Secure Identifiers—organized around similarities in perceived risk profile. Additionally, consumer segmentation analysis shows rank order of cluster risk perceptions to be stable, even when perceived magnitude and overall risk propensities change by segment. This research advances the conversation from an outdated PII/non‐PII framework to a more meaningful, consumer‐based understanding of the perceived risks associated with different types of personal information.