GeckoCheck

For publishers, editorial leaders and audience development teams

Your reporting adds the value. Know when AI cites it.

AI answers can summarize a topic before a reader reaches your publication. Track where your work is cited, which competing sources appear and where your original expertise is not being surfaced, without reducing editorial value to a citation count.

See Content
  • ChatGPT
  • Google AI Overview
  • Gemini
  • Claude
  • Perplexity
  • Copilot
  • Google AI Mode
  • Grok
  • Meta AI
  • Mistral

The original source and its citation

Illustrative review
The original review

Independent testing

What really picks up pet hair?

Original tests.
A documented method.
Results with limitations.

Inside the AI answer
“In independent testing…”
1
Source reference

Does it cite your original work?

Attribution is one signal. A citation is not a visit.

Illustrative example, not live customer data.

The questions

Questions where original work should matter.

Look at the reader needs your journalism, testing and expertise address. The goal is to understand source visibility, not to reshape every story around an AI prompt.

Which product performed best in testing?

A clear verdict should remain connected to the testing conditions and scope.

What evidence supports this conclusion?

Make original data, source documents and reported evidence easy to identify.

Who is the expert behind the advice?

Relevant expertise and transparent authorship help readers assess the work.

What changed since the last update?

Explain substantive changes rather than simply replacing the date.

How do the alternatives compare?

Consistent comparison criteria make trade-offs easier to understand.

Is this an independent recommendation?

Disclose commercial relationships and distinguish reporting from promotion.

The facts

Keep the evidence attached to the conclusion.

Make the work behind the article visible: who produced it, what was tested or reported and which limitations apply.

  • Original reporting
  • Testing methodology
  • Author expertise
  • Publication and update dates
  • Source documents
  • Comparison criteria
  • Clear limitations
  • Commercial disclosures

Follow the attribution trail

From original work to the answer that references it.

Review where attribution survives and where context gets lost. Citation visibility and referral traffic are different measures.

  1. 01

    Original work

    Locate the reporting, test results or source documents that make the article distinct.

  2. 02

    Published evidence

    Check that method, author, dates and limitations remain close to the conclusion.

  3. 03

    Observed answer

    Inspect the cited URL and whether the summary accurately represents the work.

Illustrative attribution review. A citation is not a licensing assessment, proof of model training or a guarantee of audience growth.

An editorially grounded review

Use citation data without chasing every answer.

Start with a coverage area where your publication has genuine expertise and a set of articles your team already considers important.

  1. Map the reader questions

    Choose the questions your reporting or testing helps answer. Compare your cited presence with the publications serving the same reader need.

  2. Review the article as a reference

    Check that methodology, authorship, evidence and update context are easy to find. Preserve the nuance and limitations behind any concise answer.

  3. Refresh with an editorial reason

    Prioritize factual updates and missing context, not cosmetic changes. Track citation patterns alongside the audience and commercial measures your team already uses.

A citation does not guarantee a referral, subscription or licensing outcome. AI visibility is one signal alongside reader trust, engagement and the value of original work.

Make original work easier to recognize

Find where your publication is part of the answer.

Bring a coverage area and a few important articles. Explore your citation presence, competing sources and opportunities for clearer attribution.

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