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Google’s John Mueller: Never Blindly Follow Big Sites’ SEO

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googles john mueller never blindly follow big sites seo via mattgsouthern

Google’s John Mueller recently advised against blindly following what big sites do when it comes to SEO.

This topic was addressed in a Reddit thread in which a person asks whether they should listen to Google’s advice or follow what big sites are doing. In particular, this question referred to canonical tags for pagination.

The original poster of the Reddit thread points out how Google recommends canonical pages should point a canonical tag at themselves. While big sites, on the other hand, point their canonical tag toward the first page in a series.

John Mueller’s Response

Mueller begins his response by advising against following what big sites are doing with SEO because many get it wrong. Sometimes big sites succeed in search rankings despite getting things wrong, but other sites might note fare as well.

As the thread was published in the r/TechSEO sub-Reddit, Mueller notes that technical SEO follows a logical process and there’s often a right and wrong way to do things.

”Luckily, a lot of technical SEO is not a matter of blind trust or hope, it’s not a magical black box where you have to believe, there’s no “Person X said Y, therefore Y must always be true.” It’s something that’s very deterministic, and you can logically find the answer, just as you can often test it out for your case. You can do it right, or you can do it wrong (though to be fair, search engines will try to help when you do it wrong, because lots of sites get it wrong).”

In addressing the original question, Mueller says the use of canonical tags depends on which pages you want indexed. Using a self-referencing canonical on every page helps ensure that all pages of a series get indexed on their own.

On the other hand, if every page in a series has a canonical tag pointing to page one then Google will likely index only the first page in the series.

Mueller points out that there are advantages and disadvantages to using a self-referencing canonical on each page:

“The advantage of a per-page canonical is that you’re sure all links to all items will be found. The disadvantage is that there’s potentially a lot more to crawl, and it’ll be a bit harder for us to understand how to rank the paginated pages (eg, if they’re “running shoes” category pages, which page is the right one to show for a [running shoes] search?).”

For what it’s worth, several other users in the Reddit thread recommend using self-referencing canonical in a paginated series.

Searchenginejournal

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Google Warns About Misuse of Its Indexing API

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Google Warns About Misuse of Its Indexing API

Google has updated its Indexing API documentation with a clear warning about spam detection and the possible consequences of misuse.

Warning Against API Misuse The new message in the guide says:

“All submissions through the Indexing API are checked for spam. Any misuse, like using multiple accounts or going over the usage limits, could lead to access being taken away.”

This warning is aimed at people trying to abuse the system by exceeding the API’s limits or breaking Google’s rules.

What Is the Indexing API? The Indexing API allows websites to tell Google when job posting or livestream video pages are added or removed. It helps websites with fast-changing content get their pages crawled and indexed quickly.

But it seems some users have been trying to abuse this by using multiple accounts to get more access.

Impact of the Update Google is now closely watching how people use the Indexing API. If someone breaks the rules, they might lose access to the tool, which could make it harder for them to keep their search results updated for time-sensitive content.

How To Stay Compliant To use the Indexing API properly, follow these rules:

  • Don’t go over the usage limits, and if you need more, ask Google instead of using multiple accounts.
  • Use the API only for job postings or livestream videos, and make sure your data is correct.
  • Follow all of Google’s API guidelines and spam policies.
  • Use sitemaps along with the API, not as a replacement.

Remember, the Indexing API isn’t a shortcut to faster indexing. Follow the rules to keep your access.

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GOOGLE

This Week in Search News: Simple and Easy-to-Read Update

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This Week in Search News: Simple and Easy-to-Read Update

Here’s what happened in the world of Google and search engines this week:

1. Google’s June 2024 Spam Update

Google finished rolling out its June 2024 spam update over a period of seven days. This update aims to reduce spammy content in search results.

2. Changes to Google Search Interface

Google has removed the continuous scroll feature for search results. Instead, it’s back to the old system of pages.

3. New Features and Tests

  • Link Cards: Google is testing link cards at the top of AI-generated overviews.
  • Health Overviews: There are more AI-generated health overviews showing up in search results.
  • Local Panels: Google is testing AI overviews in local information panels.

4. Search Rankings and Quality

  • Improving Rankings: Google said it can improve its search ranking system but will only do so on a large scale.
  • Measuring Quality: Google’s Elizabeth Tucker shared how they measure search quality.

5. Advice for Content Creators

  • Brand Names in Reviews: Google advises not to avoid mentioning brand names in review content.
  • Fixing 404 Pages: Google explained when it’s important to fix 404 error pages.

6. New Search Features in Google Chrome

Google Chrome for mobile devices has added several new search features to enhance user experience.

7. New Tests and Features in Google Search

  • Credit Card Widget: Google is testing a new widget for credit card information in search results.
  • Sliding Search Results: When making a new search query, the results might slide to the right.

8. Bing’s New Feature

Bing is now using AI to write “People Also Ask” questions in search results.

9. Local Search Ranking Factors

Menu items and popular times might be factors that influence local search rankings on Google.

10. Google Ads Updates

  • Query Matching and Brand Controls: Google Ads updated its query matching and brand controls, and advertisers are happy with these changes.
  • Lead Credits: Google will automate lead credits for Local Service Ads. Google says this is a good change, but some advertisers are worried.
  • tROAS Insights Box: Google Ads is testing a new insights box for tROAS (Target Return on Ad Spend) in Performance Max and Standard Shopping campaigns.
  • WordPress Tag Code: There is a new conversion code for Google Ads on WordPress sites.

These updates highlight how Google and other search engines are continuously evolving to improve user experience and provide better advertising tools.

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Exploring the Evolution of Language Translation: A Comparative Analysis of AI Chatbots and Google Translate

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A Comparative Analysis of AI Chatbots and Google Translate

According to an article on PCMag, while Google Translate makes translating sentences into over 100 languages easy, regular users acknowledge that there’s still room for improvement.

In theory, large language models (LLMs) such as ChatGPT are expected to bring about a new era in language translation. These models consume vast amounts of text-based training data and real-time feedback from users worldwide, enabling them to quickly learn to generate coherent, human-like sentences in a wide range of languages.

However, despite the anticipation that ChatGPT would revolutionize translation, previous experiences have shown that such expectations are often inaccurate, posing challenges for translation accuracy. To put these claims to the test, PCMag conducted a blind test, asking fluent speakers of eight non-English languages to evaluate the translation results from various AI services.

The test compared ChatGPT (both the free and paid versions) to Google Translate, as well as to other competing chatbots such as Microsoft Copilot and Google Gemini. The evaluation involved comparing the translation quality for two test paragraphs across different languages, including Polish, French, Korean, Spanish, Arabic, Tagalog, and Amharic.

In the first test conducted in June 2023, participants consistently favored AI chatbots over Google Translate. ChatGPT, Google Bard (now Gemini), and Microsoft Bing outperformed Google Translate, with ChatGPT receiving the highest praise. ChatGPT demonstrated superior performance in converting colloquialisms, while Google Translate often provided literal translations that lacked cultural nuance.

For instance, ChatGPT accurately translated colloquial expressions like “blow off steam,” whereas Google Translate produced more literal translations that failed to resonate across cultures. Participants appreciated ChatGPT’s ability to maintain consistent levels of formality and its consideration of gender options in translations.

The success of AI chatbots like ChatGPT can be attributed to reinforcement learning with human feedback (RLHF), which allows these models to learn from human preferences and produce culturally appropriate translations, particularly for non-native speakers. However, it’s essential to note that while AI chatbots outperformed Google Translate, they still had limitations and occasional inaccuracies.

In a subsequent test, PCMag evaluated different versions of ChatGPT, including the free and paid versions, as well as language-specific AI agents from OpenAI’s GPTStore. The paid version of ChatGPT, known as ChatGPT Plus, consistently delivered the best translations across various languages. However, Google Translate also showed improvement, performing surprisingly well compared to previous tests.

Overall, while ChatGPT Plus emerged as the preferred choice for translation, Google Translate demonstrated notable improvement, challenging the notion that AI chatbots are always superior to traditional translation tools.


Source: https://www.pcmag.com/articles/google-translate-vs-chatgpt-which-is-the-best-language-translator

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