Target's Algorithm to Calculate Customer's Pregnancy Likelihood

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Target's Algorithm to Calculate Customer's Pregnancy Likelihood
Short Title Target Knew About a Teen Girl Pregnancy Before Her Father
Location United States
Date February 2016

Solove Harm Surveillance, Aggregation, Secondary Use, Exclusion, Disclosure
Information Behavioral, Contact, Identifying, Medical and Health, Transactional, Family, Ownership
Threat Actors Target

Affected Target customers
High Risk Groups Children, Females, Pregnant Women
Tangible Harms Changed Behavior, Ostracism

Target's algorithm has enough data and is trained enough to calculate how likely is one to be pregnant.


Target collects all information about its customer's that it can get, including their buying behavior, payment data, home address etc. Surveillance It then stores a history of everything the customer bought and any demographic information Target has collected from them or bought from other sources.Aggregation

Combining as much data as possible Target's algorithm then analyzes it and tries finding extra information about the individuals. One of the examples of such information can be whether the individual is pregnant or not. Secondary Use

Target sent coupons for baby items to customers according to their pregnancy scores. One case like that included a father finding out about his teen daughter being pregnant, because Target started sending such coupons to their home address.Disclosure

The teenager had no way of knowing that Target would know her secret. Exclusion

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