The database entry glowed on the terminal, but the coordinates were too sharp—down to the fifth decimal. That was a problem. That was risk.
PII anonymization radius is the distance around a point within which the exact personal location is blurred or replaced to protect privacy. It works by introducing controlled inaccuracy into location or other sensitive data, making it impossible to link back to the individual. The anonymization radius determines how far the obfuscation spreads. Too small, and private details can still be inferred. Too large, and the data loses analytical value.
Choosing the right PII anonymization radius depends on legal requirements, threat models, and the minimum resolution you need for analytics or product functionality. Many data protection frameworks—such as GDPR and CCPA—do not define a specific radius. Instead, they require that re-identification is not “reasonably likely.” This puts the burden on you to calculate a radius that ensures compliance while preserving data utility.
Implementations often use techniques like coordinate jittering, spatial aggregation, or rounding to grid cells. Jittering adds random noise within a set radius. Aggregation groups multiple records into a shared center point, also defined by the radius. Both approaches reduce the precision of location data while retaining patterns at higher scales.