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Google Lighthouse 8.3.0 Update via @sejournal, @martinibuster

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Lighthouse, the technology that powers audits in Chrome Dev Tools and PageSpeed Insights updated to version 8.3.0. The new version features bug fixes and incremental improvements but it also takes the first step toward measuring what happens after a web page loads. This new direction is called Project Fraggle Rock.

The updated version of Lighthouse is live on PageSpeed Insights. It is scheduled to be released in Chrome Dev Tools in Chrome 94 on September 21, 2021.

Google Lighthouse

Google Lighthouse is an open source tool created by Google that tests web pages for web performance bottlenecks, accessibility issues and identify SEO opportunities.

Because the tool is open source, the underlying code that powers Lighthouse can be found in numerous third party tools, some of which extend Lighthouse by adding different capabilities and more helpful data visualizations.

That means that any changes to Lighthouse will inevitably make it into third party tools as well.

Lighthouse can be used as part of the Chrome Dev Tools suite of tools that is native in every Chrome-based browser.

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Lighthouse 8.3.0 is coming Chrome 94, which is due to be released on September 21, 2021.

PageSpeed Insights Updates to Lighthouse 8.3.0

PageSpeed Insights is a web page performance measurement tool that is also produced by Google. Google Lighthouse powers PageSpeed Insights.

The difference between PageSpeed Insights and the Lighthouse tool is that PageSpeed insights only shows the web page performance metrics and is strictly focused on that metric.

PageSpeed Insights does not show the rest of the data that Lighthouse presents which includes accessibility and SEO.

Related: A Technical SEO Guide to Lighthouse Performance Metrics

What’s New in Lighthouse 8.3.0

There are no big shifts in how Core Web Vitals are measured. But version 8.3.0 represents a little step toward bigger things in the future and also includes bug fixes.

Lighthouse Fraggle Rock Project

Lighthouse 8.3.0 takes a small step toward moving beyond analyzing a single web page and expanding to also analyzing user flows.

The future of Lighthouse is analyzing flows from when a user takes an action like clicking a button and what happens next.

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Lighthouse currently measures things like how long it takes for a web page to become interactive.

The new running on flows direction will measure what happens after the page loads.

This project is whimsically called Fraggle Rock, which is the name of a 1980’s Children’s show that featured a lighthouse referred to as the Fraggle Rock Lighthouse.

The current description of the Fraggle Rock project is officially summarized:

“Fraggle Rock (Lighthouse scripted scenarios) allows a developer to get a Lighthouse report beyond an initial page load. This is valuable as it provides developers with insight into performance & best practices for complex user flows like sign-up, add-to-cart, time-to-tweet, etc.”

The official GitHub page for the new feature describes four scenarios:

  1. “Run snapshot-style audits on a page after interaction, i.e. I’ve clicked a menu option and now rerun the accessibility category
  2. Run timespan-style audits on a page during any arbitrary interaction
  3. Run Lighthouse on a traditional page navigation from an existing page
  4. Run Lighthouse on a single page app navigation”

There are eight (tentative) phases for bringing running flows to Lighthouse.

The Lighthouse team is currently in Phase zero, which is the planning phase.

Phase 0 – Research & Design

  • Create an inventory of all audits cataloging their implicit requirements (e.g. snapshot v. timespan v. load) Complete
  • Create design doc and project plan Complete”

Phases 1 – 8 are not complete so it’s clear that the Lighthouse team is at the beginning of an important update that will dramatically change this tool.

Related: How to Perform an In-Depth Technical SEO Audit

Lighthouse 8.3.0 Bug Fixes

Lighthouse 8.3.0 also features bug fixes and small improvements, some of which were suggestions from the developer community that were frustrated with issues they discovered.

For example, one of the fixes was to address the “resource size calculation of cached images.”

One of the developers commented:

“The original reason we wanted to disable cache was because when calculating resource size, the gatherer takes transferSize into account, which is 0 for cached images. Images coming from cache are therefore ignored by this gatherer. This seems to be unwanted behavior as it shouldn’t matter whether an image is cached or not to optimize it.

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Turning off cache fixed the issue but added on average 10 seconds to our lighthouse runs. I’m wondering if the aforementioned code isn’t actually unintentionally discarding cached images.”

Lighthouse SEO Category Reworded

The SEO category of Lighthouse was reworded in order to emphasize Core Web Vitals (CWV).

The new wording also removes the explicit reference to improving search results ranking and replaces that reference with the words “search engine optimization advice” which is more neutral in terms of promises of rocking the top of the search engine results pages.

The official GitHub page for this change states:

“Updates our SEO category description to tone down its comprehensiveness and remind the user about CWV.”

Previous Lighthouse SEO description:

“These checks ensure that your page is optimized for search engine results ranking.

There are additional factors Lighthouse does not check that may affect your search ranking.”

The new Lighthouse SEO description now reads like this:

“These checks ensure that your page is following basic search engine optimization advice.

There are many additional factors Lighthouse does not score here that may affect your search ranking, including performance on Core Web Vitals. Learn more.”

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Lighthouse 8.3.0 Summary of Changes

It’s realistic that the Lighthouse team reworded the SEO section to more accurately define SEO as optimization for search engines and pull back any association with ranking better.

Clearly the most interesting part of Lighthouse 8.3.0 announcement is the Fraggle Rock project, which will be covered in more detail soon.

Citation

Lighthouse 8.3.0 Release Notes

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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

[embedded content]

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

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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.”

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