Question 29
Domain 2: Privacy Risk ManagementA retailer wants to combine loyalty history, browsing behavior, and in-store video analytics to predict highly personal life events. Which change most reduces privacy risk while preserving marketing measurement?
Correct answer: C
Explanation
Cohort-level measurement limits processing to aggregated groups, which reduces the chance of identifying a person or inferring sensitive traits from combined loyalty, browsing, and video data. Avoiding individualized sensitive inferences follows the privacy principle of data minimization and purpose limitation, preserving marketing measurement without building personal profiles about life events.
Why each option is right or wrong
A. Move the combined dataset to a more expensive analytics platform.
B. Keep the same detailed profiles but shorten password length to speed access.
C. Use cohort-level measurement and avoid creating individualized sensitive inferences from the combined data.
Under GDPR Article 5(1)(c) and (b), processing must be limited to what is adequate, relevant, and necessary for the stated purpose, and not repurposed into broader profiling. Combining loyalty, browsing, and video data to infer life events would create highly intrusive profiling, whereas cohort-level measurement keeps the analysis aggregated and avoids identifying a natural person or generating special-category-style inferences about an individual.
D. Expand the model with social media scraping so predictions are more accurate.