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Is Google’s MUM A Search Ranking Factor?

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Is Google’s MUM A Search Ranking Factor?

At Google I/O earlier last year, Google announced that it’s exploring a new technology called MUM (Multitask Unified Model) internally to help its ranking systems better understand language.

Dubbed “a new AI milestone for understanding information,” MUM is designed to make it easier for Google to answer complex needs in search.

Google promised MUM is 1,000 times more powerful than its NLP transfer learning predecessor, BERT.

It uses a model called T5, the Text-To-Text Transfer Transformer, to reframe NLP tasks into a unified text-to-text format and develop a more comprehensive understanding of knowledge and information.

According to Google, MUM can be applied to document summarization, question answering, and classification tasks such as sentiment analysis.

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Clearly, MUM is a major priority inside the Googleplex – and something that important to the search team had better on the SEO industry’s radar, as well.

But is it a ranking factor in Google’s search algorithms?

The Claim: MUM As A Ranking Factor

Many who read the news about MUM when it was first revealed naturally wondered how it might impact search rankings (especially their own).

Google makes thousands of updates to its ranking algorithms each year and while the vast majority go unnoticed, some are impactful.

BERT is one such example.

Rolled out worldwide in 2019, it was hailed the most important update in five years by Google itself.

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And sure enough, BERT impacted about 10% of search queries.

RankBrain, rolled out in the spring of 2015, is another example of an algorithmic update that had a substantial impact on the SERPs.

Now that Google is talking about MUM, it’s clear that SEO professionals and the clients they serve should take note.

Roger Montti recently wrote about a patent he believes could provide more insight into MUM’s inner workings.

That makes for an interesting read if you want to take a peek at what may be under the hood.

For now, let’s just consider whether MUM is a ranking factor.

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The Evidence For MUM As A Ranking Factor

When RankBrain rolled out, it wasn’t announced until some six months afterward. And most updates aren’t announced or confirmed at all.

However, Google has gotten better at sharing impactful updates before they happen.

For example, BERT was first announced in November 2018, rolled out for English-language queries in October 2019, and rolled out worldwide later that year, in December.

We had even more time to prepare for the Page Experience signal and Core Web Vitals, which were announced over a year ahead of the eventual rollout in June 2021.

Google has already said MUM is coming and it’s going to be a big deal.

But could MUM be responsible for a rankings drop many sites experienced in the spring and summer of 2021?

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The Evidence Against MUM As A Ranking Factor

In his May 2021 introduction to MUM, Pandu Nayak, Google Fellow and Vice President of Search, made it clear that technology isn’t in play. Not yet, anyway:

“Today’s search engines aren’t quite sophisticated enough to answer the way an expert would. But with a new technology called Multitask Unified Model, or MUM, we’re getting closer to helping you with these types of complex needs. So in the future, you’ll need fewer searches to get things done.”

The timeline given then as to when MUM-powered features and updates would go live was “in the coming months and years.”

When asked whether the industry would get a heads up when MUM goes live in search, Google Search Liaison Danny Sullivan said yes.

More recently, Nayak explained how Google is using AI in Search and wrote,

“While we’re still in the early days of tapping into MUM’s potential, we’ve already used it to improve searches for COVID-19 vaccine information, and we’ll offer more intuitive ways to search using a combination of both text and images in Google Lens in the coming months.

These are very specialized applications — so MUM is not currently used to help rank and improve the quality of search results like RankBrain, neural matching and BERT systems do.”

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He also added that any future applications of MUM will be subjected to a rigorous evaluation process including paying special attention to the responsible usage of AI.

MUM As A Ranking Factor: Our Verdict

Bottom line: Google doesn’t use MUM as a search ranking signal. It’s a language AI model built on Google’s open source neural network architecture, Transformer.

Google will train MUM as it did BERT on large datasets, then fine-tune it for specific applications on smaller datasets. This is what it’s testing with MUM’s use for improving vaccine search results.

Google has mentioned specific ways in which it may be used in the (near) future, including:

  • Surfacing insights based on its deep knowledge of the world.
  • Surfacing helpful subtopics for deeper exploration.
  • Breaking down language barriers by transferring knowledge across languages.
  • Simultaneously understanding information from different formats like webpages, pictures and more.

How will you optimize for MUM?

That remains to be seen.

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What is for sure: Google search’s intelligence is growing by leaps and bounds.

As Google’s search algorithms become more sophisticated and better able to determine the intent and nuance of language, attempts at trickery and manipulation will be less and less effective (and likely easier to detect).

With an NLP technology 1000x more powerful than RankBrain on the horizon, optimizing for human experience is more important than ever.

If you want to get ahead of MUM, focus on what the content you’re creating means for the people whose needs it is intended to meet.

The machines are inching ever closer to fully and completely experiencing that content as your intended reader/viewer does.


Featured Image: Paulo Bobita/Search Engine Journal

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brightonSEO Live Blog

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brightonSEO Live Blog

Hello everyone. It’s April again, so I’m back in Brighton for another two days of sun, sea, and SEO!

Being the introvert I am, my idea of fun isn’t hanging around our booth all day explaining we’ve run out of t-shirts (seriously, you need to be fast if you want swag!). So I decided to do something useful and live-blog the event instead.

Follow below for talk takeaways and (very) mildly humorous commentary. 

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Google Further Postpones Third-Party Cookie Deprecation In Chrome

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Close-up of a document with a grid and a red stamp that reads "delayed" over the word "status" due to Chrome's deprecation of third-party cookies.

Google has again delayed its plan to phase out third-party cookies in the Chrome web browser. The latest postponement comes after ongoing challenges in reconciling feedback from industry stakeholders and regulators.

The announcement was made in Google and the UK’s Competition and Markets Authority (CMA) joint quarterly report on the Privacy Sandbox initiative, scheduled for release on April 26.

Chrome’s Third-Party Cookie Phaseout Pushed To 2025

Google states it “will not complete third-party cookie deprecation during the second half of Q4” this year as planned.

Instead, the tech giant aims to begin deprecating third-party cookies in Chrome “starting early next year,” assuming an agreement can be reached with the CMA and the UK’s Information Commissioner’s Office (ICO).

The statement reads:

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“We recognize that there are ongoing challenges related to reconciling divergent feedback from the industry, regulators and developers, and will continue to engage closely with the entire ecosystem. It’s also critical that the CMA has sufficient time to review all evidence, including results from industry tests, which the CMA has asked market participants to provide by the end of June.”

Continued Engagement With Regulators

Google reiterated its commitment to “engaging closely with the CMA and ICO” throughout the process and hopes to conclude discussions this year.

This marks the third delay to Google’s plan to deprecate third-party cookies, initially aiming for a Q3 2023 phaseout before pushing it back to late 2024.

The postponements reflect the challenges in transitioning away from cross-site user tracking while balancing privacy and advertiser interests.

Transition Period & Impact

In January, Chrome began restricting third-party cookie access for 1% of users globally. This percentage was expected to gradually increase until 100% of users were covered by Q3 2024.

However, the latest delay gives websites and services more time to migrate away from third-party cookie dependencies through Google’s limited “deprecation trials” program.

The trials offer temporary cookie access extensions until December 27, 2024, for non-advertising use cases that can demonstrate direct user impact and functional breakage.

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While easing the transition, the trials have strict eligibility rules. Advertising-related services are ineligible, and origins matching known ad-related domains are rejected.

Google states the program aims to address functional issues rather than relieve general data collection inconveniences.

Publisher & Advertiser Implications

The repeated delays highlight the potential disruption for digital publishers and advertisers relying on third-party cookie tracking.

Industry groups have raised concerns that restricting cross-site tracking could push websites toward more opaque privacy-invasive practices.

However, privacy advocates view the phaseout as crucial in preventing covert user profiling across the web.

With the latest postponement, all parties have more time to prepare for the eventual loss of third-party cookies and adopt Google’s proposed Privacy Sandbox APIs as replacements.

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Featured Image: Novikov Aleksey/Shutterstock

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How To Write ChatGPT Prompts To Get The Best Results

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How To Write ChatGPT Prompts To Get The Best Results

ChatGPT is a game changer in the field of SEO. This powerful language model can generate human-like content, making it an invaluable tool for SEO professionals.

However, the prompts you provide largely determine the quality of the output.

To unlock the full potential of ChatGPT and create content that resonates with your audience and search engines, writing effective prompts is crucial.

In this comprehensive guide, we’ll explore the art of writing prompts for ChatGPT, covering everything from basic techniques to advanced strategies for layering prompts and generating high-quality, SEO-friendly content.

Writing Prompts For ChatGPT

What Is A ChatGPT Prompt?

A ChatGPT prompt is an instruction or discussion topic a user provides for the ChatGPT AI model to respond to.

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The prompt can be a question, statement, or any other stimulus to spark creativity, reflection, or engagement.

Users can use the prompt to generate ideas, share their thoughts, or start a conversation.

ChatGPT prompts are designed to be open-ended and can be customized based on the user’s preferences and interests.

How To Write Prompts For ChatGPT

Start by giving ChatGPT a writing prompt, such as, “Write a short story about a person who discovers they have a superpower.”

ChatGPT will then generate a response based on your prompt. Depending on the prompt’s complexity and the level of detail you requested, the answer may be a few sentences or several paragraphs long.

Use the ChatGPT-generated response as a starting point for your writing. You can take the ideas and concepts presented in the answer and expand upon them, adding your own unique spin to the story.

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If you want to generate additional ideas, try asking ChatGPT follow-up questions related to your original prompt.

For example, you could ask, “What challenges might the person face in exploring their newfound superpower?” Or, “How might the person’s relationships with others be affected by their superpower?”

Remember that ChatGPT’s answers are generated by artificial intelligence and may not always be perfect or exactly what you want.

However, they can still be a great source of inspiration and help you start writing.

Must-Have GPTs Assistant

I recommend installing the WebBrowser Assistant created by the OpenAI Team. This tool allows you to add relevant Bing results to your ChatGPT prompts.

This assistant adds the first web results to your ChatGPT prompts for more accurate and up-to-date conversations.

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It is very easy to install in only two clicks. (Click on Start Chat.)

Screenshot from ChatGPT, April 2024

For example, if I ask, “Who is Vincent Terrasi?,” ChatGPT has no answer.

With WebBrower Assistant, the assistant creates a new prompt with the first Bing results, and now ChatGPT knows who Vincent Terrasi is.

Enabling reverse prompt engineeringScreenshot from ChatGPT, March 2023

You can test other GPT assistants available in the GPTs search engine if you want to use Google results.

Master Reverse Prompt Engineering

ChatGPT can be an excellent tool for reverse engineering prompts because it generates natural and engaging responses to any given input.

By analyzing the prompts generated by ChatGPT, it is possible to gain insight into the model’s underlying thought processes and decision-making strategies.

One key benefit of using ChatGPT to reverse engineer prompts is that the model is highly transparent in its decision-making.

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This means that the reasoning and logic behind each response can be traced, making it easier to understand how the model arrives at its conclusions.

Once you’ve done this a few times for different types of content, you’ll gain insight into crafting more effective prompts.

Prepare Your ChatGPT For Generating Prompts

First, activate the reverse prompt engineering.

  • Type the following prompt: “Enable Reverse Prompt Engineering? By Reverse Prompt Engineering I mean creating a prompt from a given text.”
Enabling reverse prompt engineeringScreenshot from ChatGPT, March 2023

ChatGPT is now ready to generate your prompt. You can test the product description in a new chatbot session and evaluate the generated prompt.

  • Type: “Create a very technical reverse prompt engineering template for a product description about iPhone 11.”
Reverse Prompt engineering via WebChatGPTScreenshot from ChatGPT, March 2023

The result is amazing. You can test with a full text that you want to reproduce. Here is an example of a prompt for selling a Kindle on Amazon.

  • Type: “Reverse Prompt engineer the following {product), capture the writing style and the length of the text :
    product =”
Reverse prompt engineering: Amazon productScreenshot from ChatGPT, March 2023

I tested it on an SEJ blog post. Enjoy the analysis – it is excellent.

  • Type: “Reverse Prompt engineer the following {text}, capture the tone and writing style of the {text} to include in the prompt :
    text = all text coming from https://www.searchenginejournal.com/google-bard-training-data/478941/”
Reverse prompt engineering an SEJ blog postScreenshot from ChatGPT, March 2023

But be careful not to use ChatGPT to generate your texts. It is just a personal assistant.

Go Deeper

Prompts and examples for SEO:

  • Keyword research and content ideas prompt: “Provide a list of 20 long-tail keyword ideas related to ‘local SEO strategies’ along with brief content topic descriptions for each keyword.”
  • Optimizing content for featured snippets prompt: “Write a 40-50 word paragraph optimized for the query ‘what is the featured snippet in Google search’ that could potentially earn the featured snippet.”
  • Creating meta descriptions prompt: “Draft a compelling meta description for the following blog post title: ’10 Technical SEO Factors You Can’t Ignore in 2024′.”

Important Considerations:

  • Always Fact-Check: While ChatGPT can be a helpful tool, it’s crucial to remember that it may generate inaccurate or fabricated information. Always verify any facts, statistics, or quotes generated by ChatGPT before incorporating them into your content.
  • Maintain Control and Creativity: Use ChatGPT as a tool to assist your writing, not replace it. Don’t rely on it to do your thinking or create content from scratch. Your unique perspective and creativity are essential for producing high-quality, engaging content.
  • Iteration is Key: Refine and revise the outputs generated by ChatGPT to ensure they align with your voice, style, and intended message.

Additional Prompts for Rewording and SEO:
– Rewrite this sentence to be more concise and impactful.
– Suggest alternative phrasing for this section to improve clarity.
– Identify opportunities to incorporate relevant internal and external links.
– Analyze the keyword density and suggest improvements for better SEO.

Remember, while ChatGPT can be a valuable tool, it’s essential to use it responsibly and maintain control over your content creation process.

Experiment And Refine Your Prompting Techniques

Writing effective prompts for ChatGPT is an essential skill for any SEO professional who wants to harness the power of AI-generated content.

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Hopefully, the insights and examples shared in this article can inspire you and help guide you to crafting stronger prompts that yield high-quality content.

Remember to experiment with layering prompts, iterating on the output, and continually refining your prompting techniques.

This will help you stay ahead of the curve in the ever-changing world of SEO.

More resources: 


Featured Image: Tapati Rinchumrus/Shutterstock

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