How a model describes you, diffed against what you declared
Every claim on the left is something this site declares in structured data. Every highlight on the right is the model reproducing it, or contradicting it, or silently leaving it out. The gap between those two columns is the entire argument for entity SEO.
Entity drift · canonical claims vs model output
Canonical claims · declared in schema
What the model says
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The uncomfortable part is not that a model gets something wrong. It is that the wrong answer is fluent, confident, and derived from whatever thin signal happened to be available. Structured data is how you stop leaving that to chance.
You cannot optimise what you never measured
Rank tracking assumes a ranked list. Retrieval systems produce a description instead, and a description can be subtly, persistently wrong in ways no rank tracker will ever surface.
Drift is directional
Models fill gaps with the most statistically plausible neighbour. A Boston consultancy with thin data quietly becomes a generic Boston agency. The error is always toward the average.
Declared beats inferred
An explicit, resolvable claim with a stable identifier is far cheaper for a retrieval system to trust than a claim it has to reconstruct from prose across several pages.
The fix is boring
Consistent identifiers, sameAs edges to profiles that already have authority, and one canonical statement of each fact. Not prompt tricks.