{"id":12843,"date":"2022-02-13T18:52:37","date_gmt":"2022-02-13T18:52:37","guid":{"rendered":"https:\/\/mailinvest.blog\/index.php\/2022\/02\/13\/is-googles-mum-a-search-ranking-factor\/"},"modified":"2022-02-13T18:52:37","modified_gmt":"2022-02-13T18:52:37","slug":"is-googles-mum-a-search-ranking-factor","status":"publish","type":"post","link":"https:\/\/mailinvest.blog\/index.php\/2022\/02\/13\/is-googles-mum-a-search-ranking-factor\/","title":{"rendered":"Is Google\u2019s MUM A Search Ranking Factor?"},"content":{"rendered":"

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At Google I\/O earlier last year, Google announced that it\u2019s exploring a new technology called MUM (Multitask Unified Model) internally to help its ranking systems better understand language.<\/p>\n

Dubbed \u201ca new AI milestone for understanding information,\u201d MUM is designed to make it easier for Google to answer complex needs in search.<\/p>\n

Google promised MUM is 1,000 times<\/a> more powerful than its NLP transfer learning predecessor, BERT.<\/p>\n

It uses a model called T5<\/a>, 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.<\/p>\n

According to Google, MUM can be applied to document summarization, question answering, and classification tasks such as sentiment analysis.<\/p>\n

Clearly, MUM is a major priority inside the Googleplex \u2013 and something that important to the search team had better on the SEO industry\u2019s radar, as well.<\/p>\n

But is it a ranking factor in Google\u2019s search algorithms?\n<\/p>\n

The Claim: MUM As A Ranking Factor<\/h2>\n

Many who read the news about MUM when it was first revealed<\/a> naturally wondered how it might impact search rankings (especially their own).<\/p>\n

Google makes thousands of updates to its ranking algorithms each year and while the vast majority go unnoticed, some are impactful.<\/p>\n

BERT is one such example.<\/p>\n

Rolled out worldwide in 2019<\/a>, it was hailed the most important update in five years by Google itself.<\/p>\n

And sure enough, BERT impacted about 10%<\/a> of search queries.<\/p>\n

RankBrain<\/a>, rolled out in the spring of 2015, is another example of an algorithmic update that had a substantial impact on the SERPs.<\/p>\n

Now that Google is talking about MUM, it\u2019s clear that SEO professionals and the clients they serve should take note.<\/p>\n

Roger Montti recently wrote about a patent<\/a> he believes could provide more insight into MUM\u2019s inner workings.<\/p>\n

That makes for an interesting read if you want to take a peek at what may be under the hood.<\/p>\n

For now, let\u2019s just consider whether MUM is a ranking factor.<\/p>\n

The Evidence For MUM As A Ranking Factor<\/h2>\n

When RankBrain rolled out, it wasn\u2019t announced until some six months afterward. And most updates aren\u2019t announced or confirmed at all.<\/p>\n

However, Google has gotten better at sharing impactful updates before they happen.<\/p>\n

For example, BERT was first announced<\/a> in November 2018, rolled out for English-language queries in October 2019<\/a>, and rolled out worldwide later that year, in December<\/a>.<\/p>\n

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

Google has already said MUM is coming and it\u2019s going to be a big deal.<\/p>\n

But could MUM be responsible for a rankings drop many sites experienced in the spring and summer of 2021?<\/p>\n

The Evidence Against MUM As A Ranking Factor<\/h2>\n

In his May 2021 introduction to MUM, Pandu Nayak, Google Fellow and Vice President of Search, made it clear<\/a> that technology isn\u2019t in play. Not yet, anyway:<\/p>\n

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\u201cToday\u2019s search engines aren\u2019t quite sophisticated enough to answer the way an expert would. But with a new technology called Multitask Unified Model, or MUM, we\u2019re getting closer to helping you with these types of complex needs. So in the future<\/strong>, you\u2019ll need fewer searches to get things done.\u201d<\/p>\n<\/blockquote>\n

The timeline given then as to when MUM-powered features and updates would go live was \u201cin the coming months and years.\u201d<\/p>\n

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

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Yes, as with BERT, I\u2019m sure we\u2019ll let every know. We won\u2019t be mum on MUM.<\/p>\n

\u2014 Danny Sullivan (@dannysullivan) May 20, 2021<\/a><\/p>\n<\/blockquote>\n

More recently, Nayak explained how Google is using AI in Search<\/a> and wrote,<\/p>\n

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\u201cWhile we\u2019re still in the early days of tapping into MUM\u2019s potential, we\u2019ve already used it to improve searches for COVID-19 vaccine information, and we\u2019ll offer more intuitive ways to search using a combination of both text and images in Google Lens in the coming months.<\/p>\n

These are very specialized applications \u2014 so MUM is not currently used to help rank and improve the quality of search results<\/strong> like RankBrain, neural matching and BERT systems do.\u201d<\/p>\n<\/blockquote>\n

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.<\/p>\n

MUM As A Ranking Factor: Our Verdict<\/h2>\n

\"Is<\/p>\n

Bottom line: Google doesn\u2019t use MUM as a search ranking signal. It\u2019s a language AI model built on Google\u2019s open source neural network architecture, Transformer.<\/p>\n

Google will train MUM as it did BERT on large datasets<\/a>, then fine-tune it for specific applications on smaller datasets. This is what it\u2019s testing with MUM\u2019s use for improving vaccine search results.<\/p>\n

Google has mentioned specific ways in which it may be used in the (near) future, including:<\/p>\n

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

    How will you optimize for MUM?<\/p>\n

    That remains to be seen.<\/p>\n

    What is for sure: Google search\u2019s intelligence is growing by leaps and bounds.<\/p>\n

    As Google\u2019s 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).<\/p>\n

    With an NLP technology 1000x more powerful than RankBrain on the horizon, optimizing for human experience is more important than ever.<\/p>\n

    If you want to get ahead of MUM, focus on what the content you\u2019re creating means<\/a> for the people whose needs it is intended to meet.<\/p>\n

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

    Featured Image: Paulo Bobita\/Search Engine Journal<\/em><\/p>\n<\/div>\n