Short answer: an author identity benchmark must measure whether eligible articles have real authors, stable profiles, and consistent markup. They don't have to invent an authority score. Google recommends identifying authors for Article structured data and allows author.url' orsameAs' for identity clarification. In local services, the benchmark should separate the editorial author from the location or organization they are writing about.

Population

Define the corpus up front: articles, guides and editorial resources where author identity is relevant. Excludes service pages, contact pages and other surfaces where the individual byline would be artificial.

Keep list of URLs and snapshot date.

Baselines

For each eligible item save:

  • byline;
  • type of author: Person or Organization;
  • URL author;
  • status code of the profile;
  • names from structured data;
  • sameAs, if any;
  • the date of the last revision of the profile;
  • the existence of a reviewer, if the workflow uses it.

Metric 1: byline coverage

Numerator: Eligible articles with legitimate and visible authorship. Denominator: total eligible items.

Don't increase the percentage by artificially signing pages that don't need an author.

Metric 2: profile coverage

Numerator: bylines that link to a valid profile. Denominator: bylines for people where the profile is required according to the editorial model.

The author organization may have a different structure.

Metric 3: identity consistency

Compare byline, author page and Article markup. It only normalizes cosmetic differences.

If the name in the scheme is another person, the finding is material.

Metric 4: URL integrity

It measures broken profiles, redirect chains and canonical mismatch. These issues are easily automated and retestable.

Metric 5: expertise relevance

On a sample, check that the profile explains the experience relevant to the published topics. Use a rubric, not impressions.

It doesn't ask for spectacular credentials. Just look for the real connection between the person and the content.

Metric 6: locality claims

If the profile says the author is an "expert in city X", check the basis of the claim. Don't create different local expertise for each geographic page.

This metric is important for sites that multiply local pages.

Metric 7: reviewer attribution

For technical or professional reviewed content, check that the reviewer is displayed separately from the author.

Don't put reviewer in `author' just to have more Person entities.

Metric 8: profile freshness

Keep last_reviewed for profiles. An author can change role, location or company.

Don't automatically change articles' dateModified when you update your bio.

Metric 9: orphan profiles

Profiles without articles can be legacy, migration error or automatically created pages. Sort before deleting.

Metric 10: article-profile reciprocity

The article must be reachable to the profile, and the profile must list or discover related articles. This helps the reader verify attribution.

Observation window

Run the benchmark after CMS migration, team changes or periodically, for example quarterly. Keep the same population where possible.

If the editorial model changes, version the benchmark.

False-attribution risks

An article can rank better after correcting the author profile, but in the same period it can be rewritten or receive backlinks. Do not assign author identity ranking without separate experiment.

Likewise, an AI citation does not prove that the author's profile was the cause.

Agreement between evaluators

Expertise relevance is an interpretable metric. Take a sample and ask two raters to apply the rubric. If the disagreement is high, clarify the standard.

How do you report

It shows byline coverage, profile integrity, mismatch count, freshness and reviewer coverage separately. Do not create an "author authority 91/100".

For each finding it keeps URL, type, severity, owner and closing criteria.

Acceptance criteria

The benchmark is reproducible when corpus, rubrics, denominators and data are versioned, and findings can be reproduced from concrete URLs.

How do you compare two periods

If the number of authors or articles changes a lot between quarters, report absolute rates and volumes. An increase in coverage may come from the withdrawal of old articles, not from process improvement.

It also maintains a stable cohort of URLs for longitudinal comparison. Thus you can separate the effect of corpus migration from the quality of identity signals.

How do you treat former authors

An author who has left the organization may remain the legitimate author of a historical article. The profile can indicate the updated role or former contributor status without rewriting the assignment. If the article receives a major revision from another person, explicitly document the change in editorial ownership.

This is more correct than automatically replacing the name just for consistency.

Stop condition

Move the benchmark into monitoring when byline coverage, profile integrity and identity consistency remain stable and new findings are rare and of low severity. Resume the full audit after migration, large team changes or editorial model redesign.

Minimum change threshold

Does not open a new finding for any bio or role title variation. Prioritize mismatches that change the identity, ownership of the article, or the reader's ability to verify the author. Purely cosmetic differences may remain documented without immediate remediation.

Claim ledger

  • FACT/EVIDENCE: Google recommends identifying authors in Article structured data and allows URL/sameAs for clarification.
  • PRACTITIONER GUIDANCE: the benchmark must measure consistency, integrity and editorial ownership.
  • INFERENCE: stable profiles reduce assignment ambiguity.
  • NOT PROVEN: a universal author authority score used by Search or AI systems.

Conclusion

Author identity in local services can be measured without invented scores. A good benchmark shows where bylines are missing, where profiles are broken, and where the author is artificially portrayed as a local expert. These findings can be repaired and retested.

Sources reviewed

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