Arrow AI
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AI visibility / Accuracy

Is your AI visibility tool tracking the right company?

A mention should count only after it has been matched to the intended business. Short names, shared names, product names and rebrands can create false matches. Establish a brand identity record, inspect the surrounding answer and cited domain, and keep uncertain matches out of confirmed totals until reviewed.

Arrow / Decision brief03
AccuracyDifferent signals. Different meanings.
ReadinessDefine the scope
MentionKeep the context
CitationInspect the record
RecommendationKnow the limits

Evaluation framework · illustrative workflow

01 / Compare the evidence

What to inspect before you decide.

Accuracy / what to inspect
AmbiguityVerificationReporting treatment
01Shared company nameMatch the offer, location and linked domain.Confirm only when context identifies the intended company.
02Product versus companyDefine which product mentions belong in the company report.Keep product and corporate metrics distinguishable.
03Old brand nameSave aliases and the effective rebrand date.Label historical names rather than silently rewriting old answers.
04Unclear contextInspect the full response and source passage.Mark uncertain pending review.

02 / Worked example

The “Arrow” problem

Illustrative example · no client result

An answer containing “arrow” may describe a symbol, another company or Arrow AI. The word alone is insufficient. A reference to Arrow AI’s GEO offer with the correct domain is stronger identity evidence; a vague name without supporting context should remain unresolved. This is a matching example, not a captured AI answer.

03 / Put it into practice

A useful next step, with an owner.

  1. 01

    Create the identity record

    Record the canonical name, official domain, key products, verified aliases and common false matches.

  2. 02

    Review the match

    Read the sentence in context and follow available source links. Keep the original answer unchanged.

  3. 03

    Audit corrections

    Log why a match was accepted, rejected or left uncertain so totals can be reviewed later.

04 / Where Arrow fits

Evaluate us by
the same standard.

When evaluating Arrow, bring your domain, products and known naming collisions. Ask how identity checks and uncertain matches will appear in your agreed reporting workflow.

Inspect Arrow’s published scope Published by Arrow AI about its own field and offer.

05 / Common questions

The details behind the decision.

Should every exact-name match count?

No. An exact name can still refer to a different business. Context and official domains help resolve the identity.

What about misspellings?

Keep verified variants in an explicit alias list and review ambiguous matches. Broad fuzzy matching can create false positives.

Does a linked domain always settle the match?

It is useful evidence, but inspect the surrounding claim and whether the link actually supports it.

How should we handle a rebrand?

Preserve historical records with the name observed at the time and document the relationship between the old and current names.

Can we count a product mention as a company recommendation?

Only under an explicitly defined rule, and the report should still distinguish product mentions from company-level recommendations.

Sources & scope

This is an editorial evaluation guide, not a completed experiment or an independent ranking of vendors. Product details should be checked against the current offer.

Arrow GEO: scope and measurement method Current Arrow GEO plans

Related buyer questions

What evidence should an AI visibility platform let you inspect? When is manual AI visibility tracking enough? Explore all 10 questions

From a question to a plan

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