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SEO 22 min read May 16, 2022

Interview with Mert Erkal: What is Google MUM, and how does it affect SEO

google mum impact on seo
Author of aricle about MUM
Blog Editor at Serpstat
In 2021, Google announced a Multitask Unified Model (MUM) update. This is the most extensive system update since BERT, which will break down search barriers and improve search results based on artificial intelligence.

Although the update isn't released, it has generated much interest. To understand the topic better, we spoke to Mert Erkal.
Mert Erkal
Founder at
Mert is an experienced marketer and SEO specialist with more than ten years background. He is the founder of, one of the leading agencies on the Turkish market. Mert also holds SEOs Diner Club community with the latest news in the SEO field.

What is Google's MUM update?

Because of the imperfection of the search engines, Internet users face multiple searches, geographical and language barriers.

Google MUM is an algorithm based on artificial intelligence that will solve more difficult search problems: finding answers to complex questions by searching in different languages and media formats.

New mechanics will save users from performing multiple searches to compare and gain deeper insights. It can understand and find solutions based not only on textual content but also on interpreting images, videos, and podcasts in ways that were not possible before.
MUM is a multi-modal algorithm designed to answer complex queries by simultaneously evaluating the information on the multilingual text, images, video, and audio.

The algorithm is quite complex, so that will be implemented in several steps. Pandu Nayak presented this way of MUM development:

  • Short-term development: Knowledge transfer between languages. The first example of using MUM was in the case of improving searches about vaccination. The new algorithm has identified more than 800 variants of Covid-19 vaccine names in 50 languages.
  • Medium-term development: Multi-modal search with text, image, and video. It means an interface for simultaneous query processing with photos and text.
  • Long-term development: Understanding complex questions and offering greater depth of relevant knowledge. Content engagement: Google spokespersons insist that MUM will not turn Google into a question-answering system.
      — Mert Erkal, International SEO Expert, Founder at
      One of the main distinguishing features of MUM is multitasking. The model learns 75 languages and multiple tasks simultaneously. This allows it to gain a fuller understanding of information and the world at scale, according to a Google blog.

      For a better understanding, Google suggests the following example:
      Suppose you have already climbed Mount Adams. Now you want to hike Mount Fuji next fall and you need to know how preparing for this hike will be different from preparing for the previous climb. To find the answer to this question on Google, you need to split the search process into several steps: you have to search for the altitude of each mountain, the average temperature in autumn, the difficulty of the hiking trails, the right equipment, etc. But MUM technology should reduce the number of searches.
      As MUM is a multimodal technology, it can also understand images and video in addition to text.
      Imagine taking a picture of your hiking boots and asking, "Can I use them to climb Mount Fuji?" The MUM will be able to understand the purpose of your request, tell you whether your shoes are suitable for this climb and point you to a list of recommended equipment for climbing Mount Fuji.
      The MUM update means that searches will produce information containing valuable and related content and search for such sources more deeply than any other search engine update.

      What will change with MUM?

      In essence, MUM is just another tool to understand user thinking better. Moving away from blue links, the search engine is more and more like a recommendation system.

      In particular, there are four significant changes planned:
      - things to know;
      - zoom topic;
      - visual search upgrade;
      - video search update.
      A Complete Visual Guide of Google SERP Features in 2022: What Keywords to Use And How to Get Featured

      Things to know

      Now a similar feature called "People Also Ask" is available to us. It can be helpful for new content ideas and optimizing the structure of articles. Using Serpstat, you can easily find results from the "People also ask" block in Google. In the SERP crawling result, you can receive data with an additional block in which there will be a list of questions.
      serp crawling people also ask
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      Even though "Things to know" looks like "People also ask", it's much more in-depth.

      Google analyses how people typically explore a topic query. Based on this, it identifies the aspects that people are likely to look at first.

      This way, Google will anticipate the linked topics and show surface content instead of waiting for users to jump between the queries.

      Zoom topiс

      To help users explore ideas more deeply, Google gives the ability to zoom in and out of topics using new features to refine and broaden searches. The searchers will be able to go in-depth into a topic or go back to a more general one.
      Acrylic painting zoom topic
      Acrylic painting zoom topic. Image: Google
      Google gives the following example. Suppose you are searching for "acrylic painting."

      A new feature will help you learn more about specific techniques or suggest painting lessons. You can also expand your search and see other related topics. For example, painting techniques and famous artists.

      Visual search upgrade

      This update is already available on Google search. It makes it easier to find visual inspiration with a new results page that you can browse.
      visual search update
      Note: that the feature is only available for searches where the user is looking for inspiration.

      Video search update

      Based on Google's in-depth understanding of the information in the video, MUM can now show related topics that are not explicitly mentioned in the video.

      With MUM, Google will be able to process audio and video like text. The algorithm will identify what's in the video and how it relates to other topics.
      video search update
      Video search update. Image: Google

      Why is it important for SEO specialists?

      MUM is one of Google's steps towards a purely semantic search engine that continuously improves the context of search queries and content. In this way, content relevance and content conversions match the understanding of search intent.

      It's a fast, far-reaching, and thorough update compared to any previous search engine update. The introduction of MUM is changing the industry on par with Panda and Penguin.

      The processing of natural language and a large number of additional sources for data mining will significantly speed up a semantic search based on Hummingbird and Knowledge Graph.

      Therefore, SEO specialists need to keep a close eye on the development of the technology and its potential impact.
      SEOs may have to look at search data this year. You should notice the changes in search engine results quickly and take action.

      We see that the concept of User Intent plays a decisive role in Google results. Google can change the page titles and descriptions that appear in the search results when necessary to achieve this.
      — Mert Erkal, International SEO Expert, Founder at

      Don't quit with classic SEO

      In 2019, Pandu Nayak, Google Fellow and Vice President of Search, wrote in his blog that the search engine doesn't correctly understand queries was "one of the reasons why people often use the keyword-ese." BERT was the first step in changing the search engine from matching keywords to interpreting the context of words in a sentence.

      MUM will continue this tendency and will undoubtedly affect the game in the SEO market.

      However, one feature of complex algorithms is that they require a lot of processing power. MUM allows you to analyze pages in more detail, but covering all the network pages is still mission impossible. Thus, Google is likely to use a simpler algorithm to pre-select pages based on relevance, quality, and authority.
      Technical SEO will remain important, but with MUM, technical improvements, structured data, etc., implementations will lose their importance. Much more important will be the quality of content, the reputation and credibility of the site, and meeting user expectations.
      — Mert Erkal, International SEO Expert, Founder at
      As before, you must ensure the relevance of the subject matter, the authority of backlinks, and the quality of user experience. Likely, MUM will not pay attention to pages that don't meet these basic requirements.
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      Focus on the content's practical benefits for the user

      MUM is a very user-friendly algorithm. It overcomes language barriers to give us the widest search engine experience. By removing search barriers, Google will focus on reducing the time we spend searching for the correct answers to bring out what we need.

      In this context, content usefulness will play a significant role.
      In 2022, I think that the concept of producing quality content that best meets user expectations will be adopted instead of the idea of "SEO-friendly content." With the increasing importance of BERT and MUM algorithms, many SEO professionals will focus on the quality of the content and whether it meets the reader's expectations instead of producing SEO friendliness.
        — Mert Erkal, International SEO Expert, Founder at
        In addition, Google wants to accompany the user throughout their journey with answers to questions. Therefore, it becomes more important to create as many contact points with content as possible in the search process.

        Let's imagine you're creating content for a dance school. A newcomer to the topic will likely ask, "Can you learn dance from scratch?" Then they'll ask: "How long does it take to learn?". The user will only come to the direct search for a school after realizing that the topic is complicated enough. A company should provide answers along the way.

        SEO specialists should consider different media formats

        As we mentioned earlier, the main feature of MUM is the deep perception of several modalities. While Google doesn't yet use MUM to enhance search, it has started beta testing multisearch in Google Lens.
        Google Lens MUM update
        Google Lens update. Image: Google
        Also, numerous Google patents signed in 2021 indicate that Google can already interpret audio, video, and images. For example, this one: feature-based video annotation.

        It means that, in the future, SEOs will be able to apply keyword research or TF-IDF analyses to design the content of audios and videos in the future so that the audios and videos have semantically meaningful descriptions.
        SEOs focus primarily on text content. But with MUM, Google makes SERPs significantly more diverse in terms of media formats, as it gets better at understanding and contextualizing video, images, audio, and text. For example, you can already see this when looking at the classification of images in image search or the automatic marking of timestamps in YouTube videos.

        With MUM becoming more active, SEOs will have to do SEO work for different media types, not just text-based.

        I think that with MUM, Google is starting to answer more search queries in Google results, this will increase, and sites may be at risk of getting less and less organic traffic.

        It also means that only sites that create the best content and that can best meet their users' design and semantic expectations will survive.
        — Mert Erkal, International SEO Expert, Founder at
        How To Adapt Your SEO Strategy To Changing Trends

        MUM vs. BERT: What is the difference?

        BERT was launched in 2019. Its purpose was to help the search engine better understand users' search queries.
        BERT is Google's neural network-based natural language processing (NLP) pre-training technique. BERT stands for Bidirectional Encoder Representations from Transformers.

        Google said BERT helps better understand the nuances and context of words in searches and better match those queries with more relevant results. It is also used for featured snippets, as described above.
        BERT travel example
        BERT example. Image: Google
        Google provided this example to explain BERT: A search for "2019 brazil traveler to the USA need a visa," the word "to" and its relationship to the other words in the query are essential for understanding the meaning.

        Before BERT, Google wouldn't understand the importance of this connection and would return results about U.S. citizens traveling to Brazil.

        With BERT, Search became able to grasp this nuance and know that the widespread word "to" actually matters a lot here, and Google provided a much more relevant result for this query," Google explained.
        — Mert Erkal, International SEO Expert, Founder at
        Like most upgrades, MUM is positioned to be far superior to its predecessor. Both systems are built on the same type of architecture, called the Transformer Architecture. However, MUM has more multitasking capabilities than BERT. Therefore, Google claims that MUM reportedly provides 1,000 times better results than BERT regarding nuanced results.
        MUM has the potential to transform how Google helps you with complex tasks. MUM uses the T5 text-to-text framework and is 1,000 times more powerful than BERT.

        MUM not only understands language but also generates it. It's trained across 75 different languages and multiple tasks simultaneously, allowing it to develop a more comprehensive understanding of information and world knowledge than previous models. And MUM is multimodal, so it understands information across text and images and, in the future, can expand to more modalities like video and audio.
        — Mert Erkal, International SEO Expert, Founder at

        How does AI affect search?

        There are many types of AI, from voice search to natural language generation. Of course, they all have their features, but understanding how AI affects search is sufficient to know the basic characteristics of such machines.

        Initially, humans train machines, and after they work independently and improve themselves based on their experience. This happens because all AI technologies are great at finding patterns in data for prediction.

        An example of this skill can be found in the search section "People also ask."
        People also ask
        AI has become an exciting advance in technological development. And it, without any doubt, affects both SEO and content marketing.
        How Artificial Intelligence Changes SEO: Asking Experts
        We see that AI-assisted content production is gaining momentum, and Google spokespersons have declared that such content is against Google's guidelines and will be considered SPAM. They recently updated this type of content in the Google Webmaster Guidelines; They started to state that they do not find AI-supported content that will benefit users against their guidelines, provided that it does not provide a ranking advantage. Over time, as the use of such tools increases, Google will probably change its stance on this issue.

        With our brand, we are also in the content production business. We realized that we could use such tools much more efficiently than human writers. We think such tools can provide efficiency in producing quality content, provided that the finishing touch is done by a human.
        — Mert Erkal, International SEO Expert, Founder at


        MUM is very user-focused and essentially makes the user the center of the search engine. The natural language understanding, the updated interface, and the search's intuitiveness is a direct confirmation of this.

        Despite all the changes, we can say that MUM does not require a radical change in SEO strategy. Classic SEO and quality content are fundamental criteria for ranking pages.

        However, do not ignore the new features. Working with different types of content and following a deeper user path will play into your hands.
        We hope that this article was helpful for you. You can follow Mert on Twitter and feel free to ask any questions on the topic.

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        The opinion of the guest post authors may not coincide with the opinion of the Serpstat editorial staff and specialists.

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