Glossary
Identity resolution
Deciding that separate records — a click, a session, an order, an email — belong to the same person. Everything downstream inherits whatever this gets wrong.
Also called: identity stitching, profile unification
You have a click from Tuesday, an anonymous browsing session from Thursday, an order on Friday, and a support ticket next week. Identity resolution is the process of deciding which of those are the same person.
It matters because every number built on top of it inherits its errors. Split one customer into three and your repeat-purchase rate collapses, your acquisition costs look better than they are, and your retention reporting is fiction. Merge three people into one and you have a different set of wrong numbers plus a privacy problem.
Two approaches, and the distinction is not cosmetic.
Deterministic matching uses something exact: a login, a hashed email, an order reference, a click ID carried through the funnel. When it matches, it is right. It simply fails to match a great deal of the time, because most visitors never identify themselves.
Probabilistic matching infers the link from signals that merely tend to co-occur — device characteristics, network, timing, behaviour. It has far better coverage and it is sometimes wrong, in ways that are difficult to detect after the fact because the output looks identical to a correct match.
The judgement call is which error you would rather have. Under-matching gives you fragmented, conservative numbers. Over-matching gives you clean-looking numbers that are quietly wrong, and it can attach one person’s behaviour to another’s profile — which is a privacy incident, not a data quality issue.
For measurement, prefer deterministic and accept the gaps. For anything that changes what an individual sees, be very sure before you merge.
Do not confuse with
Close enough to get mixed up, different enough that the mix-up costs something.
- Click ID A unique identifier an ad platform appends to the landing page URL when someone clicks an ad, so a later conversion can be tied back to that exact click.
- Data clean room A controlled environment where two parties analyse their combined data without either seeing the other's raw records. Aggregate answers come out; row-level data does not.
- First-party data Information you collected directly from your own customers through your own properties. Distinct from data bought or obtained through an intermediary.
- Match rate The share of records you sent that a platform could tie to a known person. The single number that tells you whether an identity setup is working, and the first one to check when results look thin.
- Session A group of one visitor's activity treated as a single visit. The grouping is a rule each tool applies, not an event, which is why two tools rarely agree on the count.