Your television does not necessarily belong to the person holding the phone beside it.
Advertising systems sometimes have to make that guess anyway.
Cross-device matching tries to connect activity from several internet-connected devices to the same person or household.
When the match is right, separate histories become one story.
When it is wrong, somebody else’s behavior can become part of yours.
Devices can be linked directly or inferred
The Federal Trade Commission’s staff report on cross-device tracking describes two broad approaches.
Deterministic matching uses stronger direct evidence, such as the same person logging into one account across multiple devices.
Probabilistic matching estimates relationships using signals that may include IP addresses, device information, location, browsing patterns, or other observations. See Cross-Device Tracking: An FTC Staff Report.
Both approaches can be useful.
They do not have the same error profile.
A shared login is evidence that the same account appeared on two devices.
A shared household network is evidence that two devices used the same connection.
Those statements are different.
Households are hostile environments for neat attribution
Imagine four people in one home.
They share:
- a television,
- a game console,
- home Wi-Fi,
- a family tablet,
- streaming accounts,
- and occasionally each other’s laptops.
One household member researches motorcycles.
Another shops for maternity clothes.
A teenager watches hours of gaming videos on the living-room TV.
A parent uses the same tablet to research retirement accounts.
A matching system that collapses those devices too aggressively can produce a fictional super-person who is simultaneously pregnant, retiring, buying a motorcycle, and speedrunning Elden Ring.
The database may be internally consistent.
The human it describes may not exist.
Shared IP addresses are not identities
A household router makes many devices appear to the outside world through one public IP address.
Workplaces, schools, libraries, hotels, apartment networks, mobile carriers, and VPNs can create even larger shared environments.
That makes network proximity useful as a signal but dangerous as a conclusion.
LiveRamp’s current identity-resolution documentation explicitly recognizes that shared device touchpoints can map to more than one persistent identity. See LiveRamp’s RampID identity-resolution documentation.
That is an important admission built into the machinery itself: one technical identifier does not always equal one human.
Attribution errors propagate
Once two devices are joined, later systems may inherit the connection.
Advertising measurement can credit the wrong device. Audience segments can absorb another person’s interests. Recommendations can become strange. A household-level campaign can be mistaken for person-level evidence.
This is not an argument that cross-device matching never works.
It is an argument that the resolution level matters.
Person.
Household.
Device.
Account.
Those are different objects.
The Surveillance Economy becomes unreliable when its databases quietly slide between them as though they were the same thing.