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Core Web Vitals Might Include Noindexed Pages via @martinibuster

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Webmaster Trends Analyst John Mueller answered questions about Core Web Vitals and how the scores are calculated. He also discussed the possibility of noindexed pages being be used as part of the Core Web Vitals calculation in the new ranking signal that is coming soon.

Core Web Vitals

The Core Web Vitals are user experience metrics. They are a group of metrics that Google chose to represent how well a web page downloads and presents a good user experience for site visitors.

There are three Core Web Vitals metrics:

  1. Largest Contentful Paint (LCP)
    How fast a web page is perceived to load
  2. First Input Delay (FID)
    How soon a visitor can interact with a web page
  3. Cumulative Layout Shift (CLS)
    How stable web page elements (like buttons, text and images) are while the page is downloading, without shifting about.

Those three metrics are scheduled to become ranking factors sometime in 2021. That is why many publishers and SEOs are concerned about how Google calculates the core web vitals score because, as a ranking factor, there is a possibility that it may impact rankings in certain scenarios.

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Screenshot of Google’s John Mueller Discussing Noindexed Pages and Core Web Vitals

Screenshot of John Mueller discussing core web vitalsScreenshot of Google’s John Mueller discussing why noindexed pages might be used to calculate Core Web Vitals scoreScreenshot of John Mueller discussing core web vitals

Lab Data and Field Data

Knowing what lab data and field data are is key to understanding John Mueller’s answer.

Lab data, in reference to web vitals scores is an estimate of the score. The lab data scores are generated in a simulated environment.

The goal with lab data is to give a publisher an idea of what could be problematic.

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Field Data is a score based on actual site visitors under real-world conditions.

It’s the field data that Google will be using to calculate the associated ranking signal score.

Publishers concerned about their ability to rank are concerned with how field data is calculated.

  • Does Google use actual page score?
  • Does Google use an average of several pages to calculate the core web vitals score?

Noindex and Core Web Vitals

Noindex is a signal that a publisher can use to tell Google not to include a web page in Google’s search results.

According to Google’s official documentation:

“You can prevent a page from appearing in Google Search by including a noindex meta tag in the page’s HTML code, or by returning a noindex header in the HTTP request.

When Googlebot next crawls that page and sees the tag or header, Googlebot will drop that page entirely from Google Search results, regardless of whether other sites link to it.”

The question asked of Google’s John Mueller was whether a noindexed page will be used to calculate the web vitals score.

What made this question important was that the publisher was blocking these pages because they were very slow and the publisher did not want those pages used as part of the calculation of the core web vitals score.

This is the first question:

“With regards to core web vitals, field data is going to be the one to pay attention to, correct (in terms of ranking signals)?”

John Mueller’s response:

“Yes, yes, it’s the field data.”

Google May Aggregate Pages for Core Web Vitals

In the follow up question Mueller reveals how Google may in some cases calculate the core web vitals score as an average of multiple pages.

This is the question:

“When this becomes a ranking signal… is it going to be page level or domain level?”

Mueller answered:

“…What happens with the field data is we don’t have data points for every page.

So we, for the most part, we need to have kind of groupings of individual pages.

And depending on the amount of data that we have, that can be a grouping of the whole website (kind of the domain).

…I think in the Chrome User Experience Report they use the origin which would be the subdomain and the protocol there.

So that would be kind of the overarching kind of grouping.

And if we have more data for individual parts of a website then we’ll try to use that.

And I believe that’s something you also see in search console where we’ll show like one URL and say… there’s so many other pages that are associated with that. And that’s kind of the grouping that we would use there.”

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Mueller is clear that the core web vitals score may not always be calculated on a page by page basis.

Will Slow Pages Affect Overall CWV Score?

The person asking the follow up question then related that they have a set of pages that are slow and are no-indexed and asked if those pages can impact the core web vitals score.

“We gave this set of pages that they are slow. And these we have a noindex on them… they are very slow. And that’s why we don’t want it to be accounted for.”

Mueller responded:

“I don’t know for sure how we would do things with a noindex there. But it’s not something you can easily determine ahead of time.

Like, will we see this as one website or will we see it as different groupings there.

Sometimes with the Chrome User Experience Report data you can see like, Does Google have data points for those noindex pages? Does Google have data points for the other pages there?

And then you can kind of figure out like okay, it can recognize that there is separate kinds of pages and can treat them individually.

And if that’s the case, then I don’t see a problem with that.

If it’s a smaller website where we just don’t have a lot of signals for the website then those noindex pages could be playing a role there as well.

So I’m not 100% sure but my understanding is that in the Chrome User Experience Report data we do include all kinds of pages that users access.

So there’s no specific kind of, will this page be indexed like this or not check that happens there because the indexability is sometimes quite complex with regards to canonicals and all of that.

So it’s not trivial to determine… on the Chrome side if this page will be indexed or not.

It might be the case that if a page has a clear noindex then even in Chrome we would be able to recognize that. But I’m not 100% sure if we actually do that.

I would also check the Chrome User Experience Report data. I think you can download data into BigQuery and you can play with that a little bit and figure out how is that happening for other sites, for similar sites that kind of fall in the same category as the site that you’re working on.”

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Pages that Users Access

While Mueller hedged by saying that he wasn’t 100% certain if Google used noindexed pages, he did affirm that the Chrome User Experience Report included all kinds of pages (which in this context presumably includes noindexed pages).

The reason they are included is because, according to Mueller:

“…we do include all kinds of pages that users access.”

The logic behind using noindexed pages can be that because users can access a page then it is going to be measured. The reason is because a user will experience the noindexed pages, regardless if those web pages are blocked to Google.

Though Mueller wasn’t 100% certain, until there is further clarification, it may be prudent to assume that noindexed pages will be measured as part of the core web vitals ranking score.

Citation

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NEWS

What can ChatGPT do?

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ChatGPT Explained

ChatGPT is a large language model developed by OpenAI that is trained on a massive amount of text data. It is capable of generating human-like text and has been used in a variety of applications, such as chatbots, language translation, and text summarization.

One of the key features of ChatGPT is its ability to generate text that is similar to human writing. This is achieved through the use of a transformer architecture, which allows the model to understand the context and relationships between words in a sentence. The transformer architecture is a type of neural network that is designed to process sequential data, such as natural language.

Another important aspect of ChatGPT is its ability to generate text that is contextually relevant. This means that the model is able to understand the context of a conversation and generate responses that are appropriate to the conversation. This is accomplished by the use of a technique called “masked language modeling,” which allows the model to predict the next word in a sentence based on the context of the previous words.

One of the most popular applications of ChatGPT is in the creation of chatbots. Chatbots are computer programs that simulate human conversation and can be used in customer service, sales, and other applications. ChatGPT is particularly well-suited for this task because of its ability to generate human-like text and understand context.

Another application of ChatGPT is language translation. By training the model on a large amount of text data in multiple languages, it can be used to translate text from one language to another. The model is able to understand the meaning of the text and generate a translation that is grammatically correct and semantically equivalent.

In addition to chatbots and language translation, ChatGPT can also be used for text summarization. This is the process of taking a large amount of text and condensing it into a shorter, more concise version. ChatGPT is able to understand the main ideas of the text and generate a summary that captures the most important information.

Despite its many capabilities and applications, ChatGPT is not without its limitations. One of the main challenges with using language models like ChatGPT is the risk of generating text that is biased or offensive. This can occur when the model is trained on text data that contains biases or stereotypes. To address this, OpenAI has implemented a number of techniques to reduce bias in the training data and in the model itself.

In conclusion, ChatGPT is a powerful language model that is capable of generating human-like text and understanding context. It has a wide range of applications, including chatbots, language translation, and text summarization. While there are limitations to its use, ongoing research and development is aimed at improving the model’s performance and reducing the risk of bias.

** The above article has been written 100% by ChatGPT. This is an example of what can be done with AI. This was done to show the advanced text that can be written by an automated AI.

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Google December Product Reviews Update Affects More Than English Language Sites? via @sejournal, @martinibuster

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Google’s Product Reviews update was announced to be rolling out to the English language. No mention was made as to if or when it would roll out to other languages. Mueller answered a question as to whether it is rolling out to other languages.

Google December 2021 Product Reviews Update

On December 1, 2021, Google announced on Twitter that a Product Review update would be rolling out that would focus on English language web pages.

The focus of the update was for improving the quality of reviews shown in Google search, specifically targeting review sites.

A Googler tweeted a description of the kinds of sites that would be targeted for demotion in the search rankings:

“Mainly relevant to sites that post articles reviewing products.

Think of sites like “best TVs under $200″.com.

Goal is to improve the quality and usefulness of reviews we show users.”

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Google also published a blog post with more guidance on the product review update that introduced two new best practices that Google’s algorithm would be looking for.

The first best practice was a requirement of evidence that a product was actually handled and reviewed.

The second best practice was to provide links to more than one place that a user could purchase the product.

The Twitter announcement stated that it was rolling out to English language websites. The blog post did not mention what languages it was rolling out to nor did the blog post specify that the product review update was limited to the English language.

Google’s Mueller Thinking About Product Reviews Update

Screenshot of Google's John Mueller trying to recall if December Product Review Update affects more than the English language

Screenshot of Google's John Mueller trying to recall if December Product Review Update affects more than the English language

Product Review Update Targets More Languages?

The person asking the question was rightly under the impression that the product review update only affected English language search results.

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But he asserted that he was seeing search volatility in the German language that appears to be related to Google’s December 2021 Product Review Update.

This is his question:

“I was seeing some movements in German search as well.

So I was wondering if there could also be an effect on websites in other languages by this product reviews update… because we had lots of movement and volatility in the last weeks.

…My question is, is it possible that the product reviews update affects other sites as well?”

John Mueller answered:

“I don’t know… like other languages?

My assumption was this was global and and across all languages.

But I don’t know what we announced in the blog post specifically.

But usually we try to push the engineering team to make a decision on that so that we can document it properly in the blog post.

I don’t know if that happened with the product reviews update. I don’t recall the complete blog post.

But it’s… from my point of view it seems like something that we could be doing in multiple languages and wouldn’t be tied to English.

And even if it were English initially, it feels like something that is relevant across the board, and we should try to find ways to roll that out to other languages over time as well.

So I’m not particularly surprised that you see changes in Germany.

But I also don’t know what we actually announced with regards to the locations and languages that are involved.”

Does Product Reviews Update Affect More Languages?

While the tweeted announcement specified that the product reviews update was limited to the English language the official blog post did not mention any such limitations.

Google’s John Mueller offered his opinion that the product reviews update is something that Google could do in multiple languages.

One must wonder if the tweet was meant to communicate that the update was rolling out first in English and subsequently to other languages.

It’s unclear if the product reviews update was rolled out globally to more languages. Hopefully Google will clarify this soon.

Citations

Google Blog Post About Product Reviews Update

Product reviews update and your site

Google’s New Product Reviews Guidelines

Write high quality product reviews

John Mueller Discusses If Product Reviews Update Is Global

Watch Mueller answer the question at the 14:00 Minute Mark

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Survey says: Amazon, Google more trusted with your personal data than Apple is

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MacRumors reveals that more people feel better with their personal data in the hands of Amazon and Google than Apple’s. Companies that the public really doesn’t trust when it comes to their personal data include Facebook, TikTok, and Instagram.

The survey asked over 1,000 internet users in the U.S. how much they trusted certain companies such as Facebook, TikTok, Instagram, WhatsApp, YouTube, Google, Microsoft, Apple, and Amazon to handle their user data and browsing activity responsibly.

Amazon and Google are considered by survey respondents to be more trustworthy than Apple

Those surveyed were asked whether they trusted these firms with their personal data “a great deal,” “a good amount,” “not much,” or “not at all.” Respondents could also answer that they had no opinion about a particular company. 18% of those polled said that they trust Apple “a great deal” which topped the 14% received by Google and Amazon.

However, 39% said that they trust Amazon  by “a good amount” with Google picking up 34% of the votes in that same category. Only 26% of those answering said that they trust Apple by “a good amount.” The first two responses, “a great deal” and “a good amount,” are considered positive replies for a company. “Not much” and “not at all” are considered negative responses.

By adding up the scores in the positive categories,

Apple tallied a score of 44% (18% said it trusted Apple with its personal data “a great deal” while 26% said it trusted Apple “a good amount”). But that placed the tech giant third after Amazon’s 53% and Google’s 48%. After Apple, Microsoft finished fourth with 43%, YouTube (which is owned by Google) was fifth with 35%, and Facebook was sixth at 20%.

Rounding out the remainder of the nine firms in the survey, Instagram placed seventh with a positive score of 19%, WhatsApp was eighth with a score of 15%, and TikTok was last at 12%.

Looking at the scoring for the two negative responses (“not much,” or “not at all”), Facebook had a combined negative score of 72% making it the least trusted company in the survey. TikTok was next at 63% with Instagram following at 60%. WhatsApp and YouTube were both in the middle of the pact at 53% followed next by Google and Microsoft at 47% and 42% respectively. Apple and Amazon each had the lowest combined negative scores at 40% each.

74% of those surveyed called targeted online ads invasive

The survey also found that a whopping 82% of respondents found targeted online ads annoying and 74% called them invasive. Just 27% found such ads helpful. This response doesn’t exactly track the 62% of iOS users who have used Apple’s App Tracking Transparency feature to opt-out of being tracked while browsing websites and using apps. The tracking allows third-party firms to send users targeted ads online which is something that they cannot do to users who have opted out.

The 38% of iOS users who decided not to opt out of being tracked might have done so because they find it convenient to receive targeted ads about a certain product that they looked up online. But is ATT actually doing anything?

Marketing strategy consultant Eric Seufert said last summer, “Anyone opting out of tracking right now is basically having the same level of data collected as they were before. Apple hasn’t actually deterred the behavior that they have called out as being so reprehensible, so they are kind of complicit in it happening.”

The Financial Times says that iPhone users are being lumped together by certain behaviors instead of unique ID numbers in order to send targeted ads. Facebook chief operating officer Sheryl Sandberg says that the company is working to rebuild its ad infrastructure “using more aggregate or anonymized data.”

Aggregated data is a collection of individual data that is used to create high-level data. Anonymized data is data that removes any information that can be used to identify the people in a group.

When consumers were asked how often do they think that their phones or other tech devices are listening in to them in ways that they didn’t agree to, 72% answered “very often” or “somewhat often.” 28% responded by saying “rarely” or “never.”

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