For all these reasons, Google 's current algorithm ( BERT ) is becoming less and less relevant. Indeed, Internet users are forced to increase the number of searches to obtain the desired information (8 searches on average).
It is in this context that Google has developed the MUM Multitask Unified Model algorithm, the deployment date of which is still unknown. And, as with every development, SEO or natural referencing will most likely be impacted. Here's how to prepare for it.
Digital illustration depicting blue binary data (0 and 1) falling on a dark background, symbolizing Google's algorithm and the digital transformation linked to the arrival of Google MUM.
Google MUM & SEO : focus on relevance, not optimization
Google 's various evolutions ( Google SGE , Google EEAT , Core Web Vitals , etc.) all follow the same direction: to offer the most relevant results to users.
Knowing that Internet users mainly consult the first results of the SERP, one might think that it is because they are the most relevant. However, this is far from being the case. Currently, the best results are mainly the pages that are the best optimized.
Also, it is not uncommon for the most relevant, expert and explicit pages regarding the targeted query to end up at the bottom of the SERP if they are poorly optimized. And even then, when they are present.
This is why, for some time now, Google has been trying to highlight results based on their relevance to the question asked (query) and not just with regard to optimization.
With Google MUM , the search engine wants to go even further in terms of the relevance of search results. Indeed, the latter would be able to respond to very complex queries that include several parameters. To anticipate, you need to work on the semantic field of your pages and blog articles. But what is it?
In SEO , the semantic field corresponds to the set of terms ig database that relate to an Internet user's query. It brings more precision and context to web content , which helps search engines understand its meaning and find the answer to queries even when the keywords are not exactly the same.
In addition, the richness of the semantic field contributes to a greater relevance in the eyes of Google , which will then qualify the site as an expert. In its eyes, the latter is reliable and trustworthy. However, this changes everything for SEO .
But, to meet the Google MUM relevance criterion and complex queries, it is also necessary to work more in the long tail.
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Google MUM & natural referencing: favor the long tail
One of the peculiarities of Google MUM is that it is a multitasking algorithm . If the search engine as we know it ( BERT ) is already capable of performing several tasks at the same time, Google MUM should go much further and consider more parameters, such as:
the language used;
the format of the content;
the location of the Internet user;
search history;
keyword clustering;
multilingual analysis;
interpretation of results, regardless of content format;
instant translation;
The goal? Refine the understanding of the query to display more relevant and more complete results, all while working even faster to reduce Internet users' waiting times. Because yes, Google MUM would be 1,000 times more powerful than the BERT algorithm .
It therefore becomes imperative to build your content around complex queries and no longer around a few keywords. You must then think in long tail to work on more precise subjects.
This is an even more important point as it allows you to optimize your site for voice search . Indeed, when you know that more than a billion voice searches are carried out each month, you quickly understand the interest. If in a classic search, Internet users simply enter a few words in the search bar, with voice search, they make complete sentences. As you can imagine, the impact is significant for your SEO.
