Connect with us

NEWS

Google: Structured Data is an Extremely Light Signal

Published

on

Google’s John Mueller offered insightful comments in a Twitter conversation about structured data and how Google uses it. His comment touched on the importance of structured data as a Google signal.

Twitter Discussion on Structured Data

The Twitter discussion grew out of a seeming contradiction in a statement made in a recent article, Google Doesn’t Read Unsupported Structured Data.

There was no contradiction and the details are besides the point. Mueller clarified the seeming contradiction and then went on to discuss how Google uses structured data.

What followed are the tweets that matter.

Extra Structured Data

Google’s Mueller began by clarifying what kind of structured data (SD) was considered as extra. In this case, he called attention to structured data types and information that is obvious.

The first issue was about using the WebPage structured data type instead of a more specific data type:

“The thing is a lot of “extra” SD is super obvious. “This is a webpage”, well, that’s shocking, seeing we’re crawling webpages.

Lots of other SD is already clear from the page text (Is it a Ford car or a Ford president? No need for SD unless you’re really creative in writing).”

The WebPage structured data type is considered to be very general and according to Mueller, it’s “super obvious.”

Schema.org says this about the WebPage structured data type:

“Every web page is implicitly assumed to be declared to be of type WebPage…”

That seems to mean that you don’t need to use structured data to tell Google that a webpage is a webpage, it’s implied.

So that actually frees you up to use a more specific structured data type.

This is actually a fairly common error. Probably because almost everything you can document with a more specific structured data type can be declared in the more general WebPage structured data.

Structured data for Google can be split into two kinds:

  1. Rich Results Structured Data
  2. Non-rich Results Structured Data

Rich results structured data can qualify for a search results listing that is enhanced, i.e. a rich result. Non-rich results do not qualify.

But it’s probably best to be more specific. For example, these are rich results structured data types that can be used on a webpage:

  • Article
  • NewsArticle
  • HowTo

So if you’re already using a specific structured data like Article, there is no reason to use the WebPage structured data because it’s superfluous.

There are other structured data types that are non-rich results structured data that won’t show rich results but are more specifically about webpages:

  • AboutPage
  • CheckoutPage
  • CollectionPage

While those exist, they won’t qualify for any kind of rich results. But that doesn’t mean you can’t use the AboutPage structured data to communicate to a search engine what that page is about, although it’s highly likely Google can already tell from the content that it’s an “about page.”

Communicating what a page is about is generally a good idea and if you feel it might help to make something clear, then go ahead and use it.

But if the structured data type is not listed on Google’s developer pages as one that could qualify for a rich result, don’t expect to see that kind of result from it, set your expectations lower.

A rich result is like those featured snippets that show at the top of the page or stars shown in the search results for reviews.

Structured data types that are not listed in Google’s developer pages are highly likely to not quality for a rich result. Those are non-rich results structured data.

Non-rich Results Structured Data

John Mueller next discussed non-rich results structured data and said that it can be helpful but in a limited way.

He used the acronym RR to refer to Rich Results and SD to refer to Structured Data.

This is what he tweeted:

“What about the non-RR SD that’s not absolutely clear from the page? It can be helpful, but it’s also limited in the extra value it provides.”

Structured Data Signal

He finished the above tweet with a statement that seems to say that structured data is a light signal.

Mueller’s tweet:

“How do you rank something purely from SD hints? It’s an extremely light signal. If you’re worried, make the content more obvious.”

So… structured data is an extremely light signal? By signal, did he mean a ranking signal? Or a signal related to what the content was about?

John Mueller didn’t elaborate on those details.

Structured Data and Rich Results Types

Mueller reaffirmed the value of structured data, particularly where it might be difficult to accurately understand specific details.

John tweeted:

“I do see long-term value in SD for RR types where parsing the page is hard. Event dates? Venue phone numbers? Ratings & scale? Article date? It’s possible, but hard + unique per page/site, and embarrassing when we highlight it incorrectly.”

Structured data is useful for communicating information where it’s critical to get it right, like phone numbers, ratings and dates.

But Mueller also said that structured data is “extremely light” as a signal, a statement that might need clarification as to what kind of signal he was referring to.

Searchenginejournal.com

NEWS

What can ChatGPT do?

Published

on

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.

Continue Reading

NEWS

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

Published

on

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.”

Advertisement

Continue Reading Below

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.

Advertisement

Continue Reading Below

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

[embedded content]

Searchenginejournal.com

Continue Reading

NEWS

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

Published

on

survey-says:-amazon,-google-more-trusted-with-your-personal-data-than-apple-is-–-phonearena
 

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.”

Continue Reading

Trending

en_USEnglish