Structured Data That AI Search Engines Actually Read

Acquisitions deserve particular care. An acquired brand carries its own accumulated record, and both merging it into yours and keeping it separate are defensible choices. What fails is doing neither, leaving two partly overlapping records that each dilute the other, which is the most common outcome because nobody owns the decision.

A quick way to find contradictions is to write out your key facts on one sheet, taken from your structured data, then check that sheet against your about page, your main directory listing and your marketplace account. Doing it manually feels crude and it surfaces the conflicts that validators never flag, because a validator checks syntax rather than whether your founding year matches the one you published elsewhere.

Verify the Fix Without Fooling Yourself Re-ask the same four questions quarterly rather than weekly, from a fresh signed out session. Identity work has slow feedback because scattered sources have to be re-crawled before the picture updates, and checking too often produces noise that looks like failure.

Assertions with nothing behind them are weaker than silence, because they introduce a detail that fails verification. The pattern that works is reciprocal: your site names the profile, the profile links to your site, and some independent source associates the two without either of you being involved.

The Mistake That Undoes Everything Markup is a claim, not evidence. Structured data asserting that you own a profile only helps when that profile exists and points back at you. Markup naming an author only helps when the author can be found elsewhere.

Pair your name with your sector and location consistently, rather than letting it appear alone. Correct third party listings that conflate you with the other business. Where the confusion is entrenched, consider whether a consistent descriptive phrase used alongside the name in all coverage is worth adopting.

Ask What Happens in Month One A proposal that opens with content production has skipped the diagnosis. There is no way to know what to write before you know which questions matter, which assistants answer them badly and which sources they draw on.

One final practical check costs nothing. Ask for a client reference in a category structurally similar to yours rather than a famous name, and when you speak to them ask what the agency got wrong rather than what went well. References are chosen to be positive, so the useful information is in how candidly they describe the difficult parts.

Assume the pitch is good. Everyone's pitch is good, and the vocabulary in this field is easy enough that a competent salesperson can hold a convincing conversation without anyone behind them who can do the work.

Read the answers for confidence rather than accuracy at first. Hedged language, generic descriptions that would fit any competitor, and refusals to state a basic fact all indicate an incomplete record rather than a hostile one.

An entity gap is a specific and diagnosable condition. The system has encountered your company, holds some facts about it, and lacks the confidence to say anything definite. The symptom is hedging: ai search optimization vague descriptions, a refusal to recommend, or your details attached to a different business with a similar name.

Be wary of pricing tied to a proprietary visibility score, since the vendor controls both the number and the prompt set that produces it. Be equally wary of performance pricing tied to mentions, which sounds aligned and creates pressure to game the measurement rather than improve the business.

Where you do name people, make the association reciprocal. Your site names the profile, the profile links back, and ideally some independent source associates the two without either of you arranging it.

Run a commercial prompt in almost any category and look at what gets cited. Review platforms, roundups and comparison sites appear first and most often, and the brands being discussed appear well down the list if at all.

The answer you want describes a baseline: a prompt set built from how your customers actually speak, run across the assistants that matter, with raw answers and cited sources recorded. Everything after that should be justified by reference to what the baseline showed.

Results Split by Intent, With Run Counts Not one number. Mention rate reported as a fraction with the run count visible, broken out by prompt tier, so buying intent is never blended with definitional questions.

One thing worth measuring separately is how recent your reviews are relative to your competitors on the same platform. Volume comparisons are the usual instinct and recency is the more informative one, because a profile with steady recent activity describes a business as it operates now while a larger historic total describes one that used to be busy.

You are unlikely to read all of it, and its presence changes the incentives entirely. An agency that knows the raw evidence ships with the report writes a different summary than one that knows it will not be checked.