Google SERPs Without Favicons Is A Glitch via @sejournal, @martinibuster

Last week, reports claimed Google was testing mobile search results without favicons or colors, eliminating any advantage conferred by a well optimized favicon. However, a Google representative confirmed this was not a test.

Favicons In Search Results

The word favicon is short for “favorite icons,” an image meant to be shown in browser tabs, in bookmarks and in Google search results. Google recently recommended that publishers use favicons that are at least 32×32 pixels in size.

Google shows favicons in search results, which makes it a subtle way for ranked websites to attract attention and traffic. For that reason it would be a blow for many websites should Google remove the favicons because it would further erode search visibility.

Favicons Missing?

Lily Ray tweeted a screenshot showing that the favicons were missing in search results.

Google testing organic results with NO favicons or colors. 👎🏽 pic.twitter.com/zhcdnQ04bv

— Lily Ray 😏 (@lilyraynyc) November 8, 2024

The screenshot clearly shows that the favicons are missing from the search results. However the reason for that happening turned out to be something else entirely.

Googler Rajan Patel, VP of Engineering at Google, tweeted a response that explained that this was not the way the search results should be displaying. He explained that this kind of search result is meant for low end devices that can’t support rich results.

He tweeted:

This isn’t intended. @lilyraynyc Did you have JavaScript disabled on the device? What kind of device was it? The experience you’re showing is what we show for lower end devices that can’t support the richness of the search result page.”

Lily Ray responded:

“JS is not disabled. iPhone iOS 18.1 on an iPhone 15 pro. I was either using the Chrome app or Google app to search, can’t remember which.”

Rajan Patel speculated that it may have been a misconfigured experiment.

Glitches At Google

It turns out to be an example of Google glitching. Something that wasn’t explored is the whether the Internet connection or latency may have played a role in causing Google to react to the SERP request as if it was being made from a low quality device.  In any case, it’s an example of how complex serving search results can be.

Featured Image by Shutterstock/tomertu

Digital Marketers See Schema Structured Data Shifting Beyond SEO via @sejournal, @martinibuster

An interesting discussion emerged on Twitter inspired by an article written by Jono Alderson. The article proposes thinking about Schema.org structured data markup as a way for emerging AI technologies to better understand and surface published Internet content.

Schema.org Structured Data Markup

The content on a website is called unstructured data because there is no formal organized structure to it that labels each part of the content in a machine readable way. Structured data on the other hand is the exact same content but organized with labels that identify images, authors, and content so that a machine can immediately understand it.

Schema.org structured data markup is generally seen by publishers and the SEO community as something to use in order to make a web page eligible for rich results features in Google. That way of thinking is manifested in the many SEO and Schema.org WordPress plugins that are limited to outputting structured data that Google may use for surfacing rich results.

New AI technologies that can use structured data are here, requiring search marketers to consider a new approach to how structured data is deployed. What Jono encouraged in the article is to think of structured data as a way to create a “data-first foundation” that is ready for the near future.

The article proposes thinking of Schema.org markup as a way to communicate what a web page is about and how it relates to everything else on the website. Jono writes:

“But don’t shy away from building a connected graph of broader, “descriptive”” schema just because Google’s not showing an immediate return. These “descriptive” types and relationships might end up being the lifeline between your content and the AI models of the future.”

Jono tweeted about his article on X (formerly Twitter) and Martha van Berkel, founder of SchemaApp, agreed with Jono’s article that the role of Schema structured data markup is shifting.

She tweeted:

“I agree with you that the role of schema markup is changing. Building a knowledge graph to manage how your website/content is understood with schema, and then asking it questions will be more important than optimizing for Rich Results or for Google.”

Ammon Johns tweeted:

“The biggest issue with Schema is that it is largely just self-declaration, no different in essence to META content, and we know how reliable Google decided that stuff was. So Google will use it, but they are unlikely to fully trust it.”

Ammon is right of course that structured data can’t be blindly trusted. One way to solve that problem is to use a smaller index of high quality websites the wa Perplexity AI does.

Gagan Ghotra tweeted how they sometimes would like to expand their use of structured data but are limited by what the SEO and structured data tools offer.

Read Jono Alderson’s X discussion here.

Read Jono’s article:

What if Schema.org is just… Labels?

Featured Image by Shutterstock/PureSolution

Google Rolls Out November 2024 Core Algorithm Update via @sejournal, @MattGSouthern

Google has released its latest broad core algorithm update for November 2024. This update continues Google’s refinement of search systems to enhance the quality of results.

On X, Google states:

“Today we released the November 2024 core update. We’ll add it to our ranking release history page in the near future and update when the rollout is complete.”

Today we released the November 2024 core update. We’ll add it to our ranking release history page in the near future and update when the rollout is complete. For more on core updates: https://t.co/43pVoYH8k7

— Google Search Central (@googlesearchc) November 11, 2024

Core Updates Explained

These algorithmic changes, which Google implements several times annually, are designed to improve the overall search experience by reassessing how content is evaluated and ranked.

Unlike targeted updates, core updates affect search results globally across all regions and languages.

What You Should Know

According to Google’s documentation, most websites may not notice significant changes from core updates.

However, some sites might experience notable shifts in search rankings and traffic.

Google recommends that site owners who observe ranking changes should:

• Wait until the update is completed before analyzing the impact
• Compare traffic data from before and after the update in Search Console
• Pay special attention to pages experiencing major position drops (particularly those falling more than 20+ positions)
• Evaluate content quality using Google’s self-assessment guidelines
• Focus on sustainable improvements rather than quick fixes

Recovery & Response

For sites affected by the update, Google emphasizes that recovery may take time—potentially several months—as its systems learn and validate improvements.

Specific changes aren’t guaranteed to result in ranking recoveries. Google emphasizes that search results are dynamic due to evolving user expectations and continuous web content updates.

Site owners can monitor the rollout’s completion status through Google’s Search Status Dashboard.

As with previous core updates, Google is expected to announce when the rollout, which typically takes about two weeks, has finished.

Looking Ahead

This marks Google’s final confirmed core update for 2024, following previous algorithmic changes throughout the year.

We will closely assess the impact as the update rolls out across Google’s search results.

Featured Image: Salarko/Shutterstock

New Internet Rules Will Block AI Training Bots via @sejournal, @martinibuster

New standards are being developed to extend the Robots Exclusion Protocol and Meta Robots tags, allowing them to block all AI crawlers from using publicly available web content for training purposes. The proposal, drafted by Krishna Madhavan, Principal Product Manager at Microsoft AI, and Fabrice Canel, Principal Product Manager at Microsoft Bing, will make it easy to block all mainstream AI Training crawlers with one simple rule.

Virtually all legitimate crawlers obey the Robots.txt and Meta Robots tags which makes this proposal a dream come true for publishers who don’t want their content used for AI training purposes.

Internet Engineering Task Force (IETF)

The Internet Engineering Task Force (IETF) is an international Internet standards making group founded in 1986 that coordinates the development and codification of standards that everyone can voluntarily agree one. For example, the Robots Exclusion Protocol was independently created in 1994 and in 2019 Google proposed that the IETF adopt it as an official standards with agreed upon definitions. In 2022 the IETF published an official Robots Exclusion Protocol that defines what it is and extends the original protocol.

Robots.Txt For Blocking AI Robots

The draft proposal seeks to create additional rules that will extend the Robots Exclusion Protocol (Robots.txt) to extend to AI Training Robots. This will bring about some order and give publishers choice in what robots are allowed to crawl their websites.

Adherance to the Robots.txt protocol is voluntary but all legitimate crawlers tend to obey it.

The draft explains the purpose of the new Robots.txt rules:

“While the Robots Exclusion Protocol enables service owners to control how, if at all, automated clients known as crawlers may access the URIs on their services as defined by [RFC8288], the protocol doesn’t provide controls on how the data returned by their service may be used in training generative AI foundation models.

Application developers are requested to honor these tags. The tags are not a form of access authorization however.”

An important quality of the new robots.txt rules and the meta robots HTML elements is that they don’t require naming specific crawlers. One rule covers all bots that are crawling for AI training data and that voluntarily agree to follow these protocols, which is something that all legitimate bots do. This will simplify bot blocking for publishers.

The following are the proposed Robots.txt rules:

• DisallowAITraining – instructs the parser to not use the data for AI training language model.
• AllowAITraining -instructs the parser that the data can be used for AI training language model.

The following are the proposed meta robots directives:

Provides Greater Control

AI companies have been unsuccessfully sued in court for using publicly available data. AI companies have asserted that it’s fair use to crawl publicly available websites, just as search engines have done for decades.

These new protocols give web publishers control over crawlers whose purpose is for consuming training data, bringing those crawlers into alignment with search crawlers.

Read the proposal at the IETF:

Robots Exclusion Protocol Extension to manage AI content use

Featured Image by Shutterstock/ViDI Studio