Does the REL=AUTHOR tag still enhance your visibility as an author?

What is REL=AUTHOR exactly?

The REL=AUTHOR tag is an HTML attribute that links a content page to an author profile, usually via a link to a bio page or an external profile. Historically, Google recommended this practice to clearly identify the creator of content and potentially surface this information in search results.

In practice, it looked like: <a href="/author/first-name-last-name" rel="author">By First Name Last Name</a>. The idea was that Google would crawl this link, associate the content with the author, and sometimes display their photo in the SERPs to enhance trust and click-through rates.

Why does Google still promote this tag?

Google dropped the display of authorship in organic results years ago but continues to promote REL=AUTHOR in its official documentation. The most likely hypothesis: the engine still uses these attribution signals internally to assess the expertise, authority, and trustworthiness (E-E-A-T) of content creators.

This logic fits with the rise of content authorship as a quality criterion. Google wants to understand who speaks, about what, and with what legitimacy. Thus, REL=AUTHOR would be one signal among others to build an author graph and evaluate their publication history.

What are the differences with schema.org author?

REL=AUTHOR is a simple HTML tag, while schema.org/author is a structured markup that provides much richer information: name, bio, social media links, affiliated organization. The two are not competitors but rather complementary.

In practice, schema.org is now priority for savvy SEOs. It offers more flexibility, is better documented, and fits into a broader structured data logic. However, REL=AUTHOR can still serve as an additional signal if you already have an author profile system in place.

• REL=AUTHOR links a page to an author profile via a simple HTML link
• Google used this tag to display authorship in SERPs, a feature that has been removed
• The engine is likely still using these links internally to assess authors' E-E-A-T
• Schema.org/author offers a richer and better-documented alternative
• The two approaches can coexist without technical conflict

Is this statement consistent with observed practices?

Let’s be honest: REL=AUTHOR is a relic. Google ended visible authorship markup in June 2014 after finding that its impact on CTR was marginal and that its implementation posed too many quality issues. Since then, the tag has not appeared in any major official recommendations, except in some dusty documents.

In the field, SEOs who have tested adding or removing REL=AUTHOR report zero measurable impact on rankings or visibility. Modern SEO audit tools don’t even flag it as a ranking factor. [To be verified]: Google claims to use it to identify authors, but no public study confirms that it actually influences results.

What nuances should be applied to this recommendation?

If you are on a YMYL (Your Money Your Life) site or a news medium, author attribution is critical for E-E-A-T. In such cases, prioritize using schema.org/author with complete information (name, bio, photo, affiliations). REL=AUTHOR can be added as an additional signal, but it won’t get the job done alone.

For standard blogs or e-commerce sites, the effort required to implement REL=AUTHOR probably isn’t worth it. Google already detects author signatures through textual content, bylines, and structured data. Prioritize schema.org and well-optimized author pages first before fiddling with obsolete HTML attributes.

In what cases does this rule not apply?

If your content is inherently anonymous (product pages, technical specs, transactional landing pages), forcing authorship attribution makes no sense. Google does not penalize the absence of authors on non-editorial pages. The same goes for service pages like T&Cs or legal notices.

Another limitation: REL=AUTHOR only works if you have a system of structured author profiles. If your author URLs are 404s or blank pages, the signal becomes counterproductive. Google interprets this as a lack of editorial coherence, which can harm your overall E-E-A-T.

What should I do to optimize authorship?

The first step: create dedicated author pages with a clean URL (/author/first-name-last-name). Each page should contain a detailed bio, a professional photo, and links to the content published by that author. This is the foundation of a solid authorship strategy.

Next, implement schema.org/Person on these pages with properties name, url, sameAs (social media links), affiliation (organization), and jobTitle. On content pages, use schema.org/Article with the author property pointing to the structured profile. REL=AUTHOR can be added in parallel on the bylines, but it’s not the priority.

What mistakes should be avoided during implementation?

Do not create link loops between the content page and the author profile without added value. Google may interpret this as internal keyword stuffing. Make sure that each author profile contains real content, not just a list of links.

Avoid also attributing content to authors who have no legitimacy on the subject. If your marketing intern signs a technical article on cardiology, Google will detect this through semantic analysis and a lack of coherence with the rest of the profile. Authenticity matters more than quantity.

How can I check if my implementation works?

Use the Google Rich Results Test to validate your structured data for authors. Ensure that the properties name, url, and image are coming through correctly. For REL=AUTHOR, simply inspect the source code: the link should point to an indexable and relevant page.

Also, keep an eye on the featured snippets and people also ask related to your authors. If Google starts associating specific queries with an author’s name from your site, it’s a good sign. This indicates that the engine is building an expertise graph around your creators.

• Create dedicated author pages with bio, photo, and list of publications
• Implement schema.org/Person on profiles and schema.org/Article on content
• Add REL=AUTHOR to bylines as a supplement (optional)
• Check the coherence between author and subject matter (E-E-A-T)
• Test the implementation with the Google Rich Results Test tool
• Avoid ghost authors or those inconsistent with the content