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What It Is & How It Works

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Canonicalization is the process that search engines use to determine the main version of a page. That is the page that will be indexed and shown to users. The chosen version is canonical, and ranking signals like links will consolidate to that page. This process is sometimes referred to as standardization or normalization.

According to Google Webmaster Trends Analyst Gary Illyes, ~60% of the internet is duplicate content.

Canonicalization is complex and often misunderstood. I don’t think most of the duplicates are nefarious. It’s mostly going to be technical issues that cause them. We’ll look at this more in a bit. I’m going to talk about how the canonicalization process works as wellΒ as:

A lot of different signals go into the canonicalization process. These include:

  • Duplicates
  • Canonical link elements
  • Sitemap URLs
  • Internal links
  • Redirects

Google looks at all the different signals and weighs them to determine what the canonical version should be. That’s the version of the page they will index and what they usually show toΒ users.

A potential scenario when Google decides on the canonical based on internal links and the canonical URL.

A potential scenario when Google decides on the canonical based on internal links and the canonical URL.

Duplicates

With duplicate content, Google will pick a canonical version to index. All the eligible pages form a cluster of pages, and the signals that go to the pages in that cluster will consolidate at the chosen canonical. That canonical may even change overΒ time.

How duplicate signals consolidateHow duplicate signals consolidate

Some SEOs believe there is a duplicate content penalty, but that’s not true. Generally, you’re going to have one version or another indexed. It may not be the version you want to be indexed, but it will be indexed and rank just as well as any other version of the sameΒ page.

Here are some examples of what can cause duplicate pages and sometimes canonicalization issues:

  • HTTP and HTTPS variants (e.g., http://www.example.com and https://www.example.com)
  • Non-www and www variants (e.g., http://example.com and http://www.example.com)
  • URLs with and without trailing slashes (e.g., https://example.com/page/ and https://example.com/page)
  • URLs with and without capital letters (e.g., https://example.com/page/ and https://example.com/Page/)
  • Default versions of the page such as index pages (e.g., https://www.example.com/, https://www.example.com/index.htm, https://www.example.com/index.html, https://www.example.com/index.php, https://www.example.com/default.htm, etc.)
  • Alternate versions of pages. This could include mobile versions (e.g., example.com and m.example.com), AMP versions (e.g., example.com/page and amp.example.com/page), print versions (e.g., example.com/page and example.com /page/print), alternate versions meant for other countries but containing the same content (e.g., example.com/en-us/, example.com/en-gb/, example.com/en-au/), or versions in a dev or staging site (e.g., dev.example.com).
  • URL parameters (e.g., example.com?parameter=whatever). These may exist because of tracking codes, faceted navigation, sorting content, session IDs, etc. There are some instances where parameters may change the page’s content so that it’s not a duplicate.
  • Other pages showing the full content. Google may choose the wrong canonical when another page displays the content in full. This may include the main blog page, paginated pages, tag pages, category pages, or feedΒ pages.
  • Scraped or syndicated content. Content syndication best practices generally recommend having a canonical tag back to the original content or at least a link to the original content. That’s because the canonical chosen can be a completely different domain. They try to select the original source as the canonical, but in some cases, they choose the wrongΒ page.

Most of these aren’t usually issues. As I mentioned, Google will usually choose one version or another as the canonical. There are a few exceptions toΒ this.

  1. Sometimes with content syndication, the original source isn’t chosen as the canonical. This is a real problem. How would you feel if someone else started ranking for an article youΒ wrote?
  2. Hreflang does not solve duplication on international sites. Google will generally try to swap to show the correct version, but it’s not guaranteed, and this setup often breaks. When this happens, users see pages from the wrong country. It’s best to avoid having the same content on multiple pages for international websites.
  3. With some JavaScript sites (typically app shell models), the initial code for the pages can look like other pages or even the code from other websites. Sometimes these pages get canonicalized to other pages on the same or even different websites.

I believe part of the problem with both hreflang and the JavaScript content is that Google may be running the duplicate detection via crawl algorithms that detect duplication patterns, again after just seeing the code, and yet again after rendering theΒ pages.

Google’s render path marked up where I believe duplicate detection systems are run.Google’s render path marked up where I believe duplicate detection systems are run.

Google’s render path marked up where I believe duplicate detection systems areΒ run.

Google’s render path marked up where I believe duplicate detection systems areΒ run.

With the pages using hreflang, if they decide that the pages are duplicates without crawling them, they may not be able to swap them properly.

Before a page is even rendered, it may β€œlook” like another page based on the HTML content. Google may choose the canonical based on this initial version and may not prioritize it for rendering because it’s already deemed a duplicate page. This usually resolves itself after rendering, but it can take some time to clearΒ up.

Google has a couple of rules they generally follow when it comes to canonicalization of duplicates.

1. They prefer HTTPS pages over HTTPΒ pages

They will generally index the HTTPS version, but there are a few issues or conflicting signals that may cause them to choose the HTTP version instead, suchΒ as:

  • Having an invalid security certificate
  • HTTPS page links to HTTP resources on the page (excludes images)
  • HTTPS redirecting toΒ HTTP
  • HTTPS page having a rel=β€œcanonical” link element pointing to the HTTPΒ page

2. They prefer shorter URLs over longer URLs

This has been misconstrued over the years by SEOs to say that all your URLs should be shorter. But that’s not what was meant by the original statement. What Google said was that if you had, for instance, a clean short version of a URL and a longer version with parameters attached, they would generally choose the shorter version of the URL without the parameter as the canonical version.

Canonical link element

This is also commonly referred to as a canonical tag. It looks likeΒ this:

<link rel=”canonical” https://www.example.com />

The canonical tag is sometimes referred to as a hint because it’s just one canonicalization signal. Google ignores it if other signals are stronger.

If the canonical tag is respected, all signals like links will pass. However, if the canonical is ignored, no value is passed. The value isn’t lost; it stays with the original page or goes to whatever page Google chooses as the canonical.

A canonical link element can be implemented in two different ways. It can be in the <head> section or the HTTP header.

A fun anecdote. Google’s SEO Starter Guide used to be a PDF. They didn’t have a canonical tag set in the HTTP header, and people used to β€œsteal” the listing with their own duplicate version.

Sometimes the <head> section of a page will end before it should. This is usually caused by a tag in the <head> not closed out properly. When that happens, a canonical tag may be put into the <body> section instead. If that happens, your canonical tag won’t be respected.

Invalid canonical tag located in the<body></noscript><img class=

Invalid canonical tag located in the <body> section

Sitemap URLs

The URLs you include in your sitemap are also a canonicalization signal. Most of the time, you only want to include URLs of pages that you want to be indexed.

There are some exceptions to this because sitemap URLs also help with crawling. After a website migration, you should create a sitemap that still lists the old pages, even though they aren’t canonical. This will help the redirects be processed faster. You’ll want to delete this sitemap after most of the redirects have been picked up and processed.

Internal links

It matters how you link to pages. Internal links are another canonicalization signal.

Generally, you should link to the version of a page you want to be canonical and update the links to any URLs that may have changed. However, there are exceptions to this, such as with faceted navigation. In some cases like this, what is best for users may trump what is best forΒ SEO.

Redirects

There are several different types of redirects, and they’re all canonicalization signals. They pass PageRank and help determine which URL gets shown in Google’s index.

301s and 308s send signals forward to the new URL. 302s and some 307s send signals backwards to the redirected URL. If a 302 is left in place long enough or the URL it’s redirected to already exists, it may be treated as a 301 and send signals forward instead. It requires enough signals to flip the scale we saw earlier for canonicalization signals. As links build up, internal links are changed, sitemap URLs are updated, etc., more signals point to the new URL than the old URL, and the flip occurs.

At some point the scale flips for 302sAt some point the scale flips for 302s

At some point the scale flips forΒ 302s

A 307 has two different cases. In cases where it’s a temporary redirect, it will be treated the same as a 302 and attempt to consolidate backward. When web servers require clients to only use HTTPS connections (HSTS policy), Google won’t see the 307 because it’s cached in the browser. The initial hit (without cache) will have a server response code that’s likely a 301 or a 302. But your browser will show you a 307 for subsequent requests.

There are also other types of redirects like those implemented with JavaScript. These are also canonicalization signals and pass the full value just like other redirects as long as they can be seen and processed by Google. They’re fine to use in mostΒ cases.

How to check the canonical

Your main source of truth for what Google chose as the canonical will be the URL Inspection tool in Google Search Console. Enter the URL, and it will show what the declared canonical is and what Google chose as the canonical.

The declared and Google-selected canonical via Google Search ConsoleThe declared and Google-selected canonical via Google Search Console

If you don’t have access to Google Search Console, the recommended way to check the version of a page Google has indexed is to paste the URL into Google. The top result is usually the canonical.

Similarly, if you check the cached version of a page in Google and a different page is shown, Google has selected a different version of theΒ page.

Warning: Don’t use site: searches for checking canonicals. It shows what Google knows about, not necessarily what’s indexed or the selected canonical.

Within Site Audit, we show many issues related to canonicalization. Keep in mind that we’re flagging best practices in most cases. Because the canonical is a hint, Google and other search engines will have to choose which version of a page toΒ index.

Canonicalization issues in Ahrefs' Site AuditCanonicalization issues in Ahrefs' Site Audit

Even if your website has lots of issues related to canonicalization, search engines may be able to figure out what version should be indexed and where they should consolidate signals. It may not create any real problems forΒ them.

Fun fact. When running a Site Audit, we only count the canonical version of pages as crawl credits. Some other tools count every version of a page towards the credits. On many sites, this can eat multiple credits perΒ page!

There’s a lot that can go wrong with canonicalization. Let’s look at some common mistakes.

Mistake #1: Blocking the canonicalized URL via robots.txt

Blocking a URL in robots.txt prevents Google from crawling it, meaning that they cannot see any canonical tags on that page. That, in turn, prevents them from transferring any β€œlink equity” from the non-canonical to the canonical.

Unless you have a crawl budget issue, it’s probably better to let all the signals consolidate. Even if you’re going to block or noindex some versions, you still may want to check for versions with links that you should canonicalize instead. However, as Google tends to crawl non-canonical pages less over time, you may just want toΒ wait.

Mistake #2: Setting the canonicalized URL to β€˜noindex’

Never mix noindex and rel=canonical. They’re contradictory instructions.

As John Mueller states, Google will usually prioritize the canonical tag over the β€˜noindex’ tag.

Mistake #3: Setting a 4XX HTTP status code for the canonicalized URL

Setting a 4XX HTTP status code for a canonicalized URL has the same effect as using the β€˜noindex’ tag: Google will be unable to see the canonical tag and transfer β€œlink equity” to the canonical version.

Mistake #4: Canonicalizing all paginated pages to the rootΒ page

Paginated pages should not be canonicalized to the first paginated page in the series. Instead, self-referencing canonicals should be used on all paginated pages.

Why? As Google’s John Mueller stated on Reddit, this is improper use of the rel=canonical.

The main thing to avoid, since this post is about canonicalization, is to use the rel=canonical on page 2 pointing to page 1. Page 2 isn’t equivalent to page 1, so the rel=canonical like that would be incorrect.Β 

John MuellerJohn Mueller

We have a guide on pagination for SEO and best practices if you’re interested.

Mistake #5: Don’t use the URL removal tool in Google Search Console for canonicalization.

This can remove all versions of a URL, effectively deindexing your page from search.

Mistake #6: Not keeping canonicalization signals consistent.

As we talked about earlier, there are many different canonicalization signals.

Having different signals suggest different canonicals means that you will be relying on Google to select a canonical for you. The more consistent signals you show them with your preferred version, the more likely it is that version will be the chosen canonical.

Mistake #7: Not using canonical tags with hreflang

Hreflang tags specify the language and geographical targeting of a webpage.

Google states that when using hreflang, you should β€œspecify a canonical page in the same language, or the best possible substitute language if a canonical doesn’t exist for the same language.”

Mistake #8: Having multiple rel=canonical tags

Having multiple rel=canonical tags will usually cause Google to ignore them. In many cases, this happens because tags are inserted into a system at different points, such as by the CMS, the theme, and plugin(s). This is why many plugins have an overwrite option meant to ensure they are the only source for canonical tags.

Another area where this might be a problem is with canonicals added with JavaScript. If you have no canonical URL specified in the HTML response and then add a rel=canonical tag with JavaScript, it should be respected when Google renders the page. However, if you have a canonical specified in HTML and swap the preferred version with JavaScript, you send mixed signals to Google.

Mistake #9: Rel=canonical in the <body>

Rel=canonical should only appear in the <head> of a document. A canonical tag in the <body> section of a page will be ignored.

Where this can become a problem is with the parsing of a document. Even if the page’s source code has the rel=canonical tag in the correct place, many different things such as unclosed tags, JavaScript injected, or <iframes> in the <head> section can cause the <head> to end prematurely while rendering. In these cases, a canonical tag may be accidentally thrown into the <body> of a rendered page where it will not be respected.

Final thoughts

Many of the tools SEOs had for handling canonicalization have been taken away, such as the URL Parameters Tool and Preferred Domain setting in Google Search Console. However, there are still plenty of other signals to help Google choose a canonical.

If you have questions, message me on Twitter.

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4 Ways To Try The New Model From Mistral AI

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4 Ways To Try The New Model From Mistral AI

In a significant leap in large language model (LLM) development, Mistral AI announced the release of its newest model, Mixtral-8x7B.

What Is Mixtral-8x7B?

Mixtral-8x7B from Mistral AI is a Mixture of Experts (MoE) model designed to enhance how machines understand and generate text.

Imagine it as a team of specialized experts, each skilled in a different area, working together to handle various types of information and tasks.

A report published in June reportedly shed light on the intricacies of OpenAI’s GPT-4, highlighting that it employs a similar approach to MoE, utilizing 16 experts, each with around 111 billion parameters, and routes two experts per forward pass to optimize costs.

This approach allows the model to manage diverse and complex data efficiently, making it helpful in creating content, engaging in conversations, or translating languages.

Mixtral-8x7B Performance Metrics

Mistral AI’s new model, Mixtral-8x7B, represents a significant step forward from its previous model, Mistral-7B-v0.1.

It’s designed to understand better and create text, a key feature for anyone looking to use AI for writing or communication tasks.

This latest addition to the Mistral family promises to revolutionize the AI landscape with its enhanced performance metrics, as shared by OpenCompass.

Mixtral-8x7B: 4 Ways To Try The New Model From Mistral AI

What makes Mixtral-8x7B stand out is not just its improvement over Mistral AI’s previous version, but the way it measures up to models like Llama2-70B and Qwen-72B.

mixtral-8x7b performance metrics compared to llama 2 open source ai modelsmixtral-8x7b performance metrics compared to llama 2 open source ai models

It’s like having an assistant who can understand complex ideas and express them clearly.

One of the key strengths of the Mixtral-8x7B is its ability to handle specialized tasks.

For example, it performed exceptionally well in specific tests designed to evaluate AI models, indicating that it’s good at general text understanding and generation and excels in more niche areas.

This makes it a valuable tool for marketing professionals and SEO experts who need AI that can adapt to different content and technical requirements.

The Mixtral-8x7B’s ability to deal with complex math and coding problems also suggests it can be a helpful ally for those working in more technical aspects of SEO, where understanding and solving algorithmic challenges are crucial.

This new model could become a versatile and intelligent partner for a wide range of digital content and strategy needs.

How To Try Mixtral-8x7B: 4 Demos

You can experiment with Mistral AI’s new model, Mixtral-8x7B, to see how it responds to queries and how it performs compared to other open-source models and OpenAI’s GPT-4.

Please note that, like all generative AI content, platforms running this new model may produce inaccurate information or otherwise unintended results.

User feedback for new models like this one will help companies like Mistral AI improve future versions and models.

1. Perplexity Labs Playground

In Perplexity Labs, you can try Mixtral-8x7B along with Meta AI’s Llama 2, Mistral-7b, and Perplexity’s new online LLMs.

In this example, I ask about the model itself and notice that new instructions are added after the initial response to extend the generated content about my query.

mixtral-8x7b perplexity labs playgroundScreenshot from Perplexity, December 2023mixtral-8x7b perplexity labs playground

While the answer looks correct, it begins to repeat itself.

mixtral-8x7b errorsScreenshot from Perplexity Labs, December 2023mixtral-8x7b errors

The model did provide an over 600-word answer to the question, β€œWhat is SEO?”

Again, additional instructions appear as β€œheaders” to seemingly ensure a comprehensive answer.

what is seo by mixtral-8x7bScreenshot from Perplexity Labs, December 2023what is seo by mixtral-8x7b

2. Poe

Poe hosts bots for popular LLMs, including OpenAI’s GPT-4 and DALLΒ·E 3, Meta AI’s Llama 2 and Code Llama, Google’s PaLM 2, Anthropic’s Claude-instant and Claude 2, and StableDiffusionXL.

These bots cover a wide spectrum of capabilities, including text, image, and code generation.

The Mixtral-8x7B-Chat bot is operated by Fireworks AI.

poe bot for mixtral-8x7b firebaseScreenshot from Poe, December 2023poe bot for mixtral-8x7b firebase

It’s worth noting that the Fireworks page specifies it is an β€œunofficial implementation” that was fine-tuned for chat.

When asked what the best backlinks for SEO are, it provided a valid answer.

mixtral-8x7b poe best backlinks responseScreenshot from Poe, December 2023mixtral-8x7b poe best backlinks response

Compare this to the response offered by Google Bard.

Mixtral-8x7B: 4 Ways To Try The New Model From Mistral AIMixtral-8x7B: 4 Ways To Try The New Model From Mistral AI

Mixtral-8x7B: 4 Ways To Try The New Model From Mistral AIScreenshot from Google Bard, December 2023Mixtral-8x7B: 4 Ways To Try The New Model From Mistral AI

3. Vercel

Vercel offers a demo of Mixtral-8x7B that allows users to compare responses from popular Anthropic, Cohere, Meta AI, and OpenAI models.

vercel mixtral-8x7b demo compare gpt-4Screenshot from Vercel, December 2023vercel mixtral-8x7b demo compare gpt-4

It offers an interesting perspective on how each model interprets and responds to user questions.

mixtral-8x7b vs cohere on best resources for learning seoScreenshot from Vercel, December 2023mixtral-8x7b vs cohere on best resources for learning seo

Like many LLMs, it does occasionally hallucinate.

mixtral-8x7b hallucinationsScreenshot from Vercel, December 2023mixtral-8x7b hallucinations

4. Replicate

The mixtral-8x7b-32 demo on Replicate is based on this source code. It is also noted in the README that β€œInference is quite inefficient.”

Mixtral-8x7B: 4 Ways To Try The New Model From Mistral AIScreenshot from Replicate, December 2023Mixtral-8x7B: 4 Ways To Try The New Model From Mistral AI

In the example above, Mixtral-8x7B describes itself as a game.

Conclusion

Mistral AI’s latest release sets a new benchmark in the AI field, offering enhanced performance and versatility. But like many LLMs, it can provide inaccurate and unexpected answers.

As AI continues to evolve, models like the Mixtral-8x7B could become integral in shaping advanced AI tools for marketing and business.


Featured image: T. Schneider/Shutterstock



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OpenAI Investigates ‘Lazy’ GPT-4 Complaints On Google Reviews, X

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OpenAI Investigates 'Lazy' GPT-4 Complaints On Google Reviews, X

OpenAI, the company that launched ChatGPT a little over a year ago, has recently taken to social media to address concerns regarding the β€œlazy” performance of GPT-4 on social media and Google Reviews.

Screenshot from X, December 2023OpenAI Investigates ‘Lazy’ GPT-4 Complaints On Google Reviews, X

This move comes after growing user feedback online, which even includes a one-star review on the company’s Google Reviews.

OpenAI Gives Insight Into Training Chat Models, Performance Evaluations, And A/B Testing

OpenAI, through its @ChatGPTapp Twitter account, detailed the complexities involved in training chat models.

chatgpt openai a/b testingScreenshot from X, December 2023chatgpt openai a/b testing

The organization highlighted that the process is not a β€œclean industrial process” and that variations in training runs can lead to noticeable differences in the AI’s personality, creative style, and political bias.

Thorough AI model testing includes offline evaluation metrics and online A/B tests. The final decision to release a new model is based on a data-driven approach to improve the β€œreal” user experience.

OpenAI’s Google Review Score Affected By GPT-4 Performance, Billing Issues

This explanation comes after weeks of user feedback about GPT-4 becoming worse on social media networks like X.

Complaints also appeared in OpenAI’s community forums.

openai community forums gpt-4 user feedbackScreenshot from OpenAI, December 2023openai community forums gpt-4 user feedback

The experience led one user to leave a one-star rating for OpenAI via Google Reviews. Other complaints regarded accounts, billing, and the artificial nature of AI.

openai google reviews star rating Screenshot from Google Reviews, December 2023openai google reviews star rating

A recent user on Product Hunt gave OpenAI a rating that also appears to be related to GPT-4 worsening.

openai reviewsScreenshot from Product Hunt, December 2023openai reviews

GPT-4 isn’t the only issue that local reviewers complain about. On Yelp, OpenAI has a one-star rating for ChatGPT 3.5 performance.

The complaint:

yelp openai chatgpt reviewScreenshot from Yelp, December 2023yelp openai chatgpt review

In related OpenAI news, the review with the most likes aligns with recent rumors about a volatile workplace, alleging that OpenAI is a β€œCutthroat environment. Not friendly. Toxic workers.”

google review for openai toxic workersScreenshot from Google Reviews, December 2023google review for openai toxic workers

The reviews voted the most helpful on Glassdoor about OpenAI suggested that employee frustration and product development issues stem from the company’s shift in focus on profits.

openai employee review on glassdooropenai employee review on glassdoor

openai employee reviewsScreenshots from Glassdoor, December 2023openai employee reviews

This incident provides a unique outlook on how customer and employee experiences can impact any business through local reviews and business ratings platforms.

openai inc google business profile local serps google reviewsScreenshot from Google, December 2023openai inc google business profile local serps google reviews

Google SGE Highlights Positive Google Reviews

In addition to occasional complaints, Google reviewers acknowledged the revolutionary impact of OpenAI’s technology on various fields.

The most positive review mentions about the company appear in Google SGE (Search Generative Experience).

Google SGE response on OpenAIScreenshot from Google SGE, December 2023Google SGE response on OpenAI

Conclusion

OpenAI’s recent insights into training chat models and response to public feedback about GPT-4 performance illustrate AI technology’s dynamic and evolving nature and its impact on those who depend on the AI platform.

Especially the people who just received an invitation to join ChatGPT Plus after being waitlisted while OpenAI paused new subscriptions and upgrades. Or those developing GPTs for the upcoming GPT Store launch.

As AI advances, professionals in these fields must remain agile, informed, and responsive to technological developments and the public’s reception of these advancements.


Featured image: Tada Images/Shutterstock



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ChatGPT Plus Upgrades Paused; Waitlisted Users Receive Invites

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ChatGPT Plus Upgrades Paused; Waitlisted Users Receive Invites

ChatGPT Plus subscriptions and upgrades remain paused after a surge in demand for new features created outages.

Some users who signed up for the waitlist have received invites to join ChatGPT Plus.

Screenshot from Gmail, December 2023ChatGPT Plus Upgrades Paused; Waitlisted Users Receive Invites

This has resulted in a few shares of the link that is accessible for everyone. For now.

RELATED: GPT Store Set To Launch In 2024 After β€˜Unexpected’ Delays

In addition to the invites, signs that more people are getting access to GPTs include an introductory screen popping up on free ChatGPT accounts.

ChatGPT Plus Upgrades Paused; Waitlisted Users Receive InvitesScreenshot from ChatGPT, December 2023ChatGPT Plus Upgrades Paused; Waitlisted Users Receive Invites

Unfortunately, they still aren’t accessible without a Plus subscription.

chatgpt plus subscriptions upgrades paused waitlistScreenshot from ChatGPT, December 2023chatgpt plus subscriptions upgrades paused waitlist

You can sign up for the waitlist by clicking on the option to upgrade in the left sidebar of ChatGPT on a desktop browser.

ChatGPT Plus Upgrades Paused; Waitlisted Users Receive InvitesScreenshot from ChatGPT, December 2023ChatGPT Plus Upgrades Paused; Waitlisted Users Receive Invites

OpenAI also suggests ChatGPT Enterprise for those who need more capabilities, as outlined in the pricing plans below.

ChatGPT Plus Upgrades Paused; Waitlisted Users Receive InvitesScreenshot from OpenAI, December 2023ChatGPT Plus Upgrades Paused; Waitlisted Users Receive Invites

Why Are ChatGPT Plus Subscriptions Paused?

According to a post on X by OpenAI’s CEO Sam Altman, the recent surge in usage following the DevDay developers conference has led to capacity challenges, resulting in the decision to pause ChatGPT Plus signups.

The decision to pause new ChatGPT signups follows a week where OpenAI services – including ChatGPT and the API – experienced a series of outages related to high-demand and DDoS attacks.

Demand for ChatGPT Plus resulted in eBay listings supposedly offering one or more months of the premium subscription.

When Will ChatGPT Plus Subscriptions Resume?

So far, we don’t have any official word on when ChatGPT Plus subscriptions will resume. We know the GPT Store is set to open early next year after recent boardroom drama led to β€œunexpected delays.”

Therefore, we hope that OpenAI will onboard waitlisted users in time to try out all of the GPTs created by OpenAI and community builders.

What Are GPTs?

GPTs allow users to create one or more personalized ChatGPT experiences based on a specific set of instructions, knowledge files, and actions.

Search marketers with ChatGPT Plus can try GPTs for helpful content assessment and learning SEO.

There are also GPTs for analyzing Google Search Console data.

And GPTs that will let you chat with analytics data from 20 platforms, including Google Ads, GA4, and Facebook.

Google search has indexed hundreds of public GPTs. According to an alleged list of GPT statistics in a GitHub repository, DALL-E, the top GPT from OpenAI, has received 5,620,981 visits since its launch last month. Included in the top 20 GPTs is Canva, with 291,349 views.

Β 

Weighing The Benefits Of The Pause

Ideally, this means that developers working on building GPTs and using the API should encounter fewer issues (like being unable to save GPT drafts).

But it could also mean a temporary decrease in new users of GPTs since they are only available to Plus subscribers – including the ones I tested for learning about ranking factors and gaining insights on E-E-A-T from Google’s Search Quality Rater Guidelines.

custom gpts for seoScreenshot from ChatGPT, November 2023custom gpts for seo

Featured image: Robert Way/Shutterstock



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