Google MUM as a Ranking Factor
Last year, at its annual developers’ conference, Google announced that it was investigating a new technology called MUM (Multitask Unified Model) internally. The aim was to use it to help its ranking systems better comprehend language. As a result, many site owners and online businesses are wondering if MUM is now one of Google’s SEO ranking signals. MUM is said to be a new milestone in AI, meant to make it easier for Google to understand and meet complex demands in searches. According to Google, the system is a lot more powerful than their earlier BERT algorithm, the NLP transfer learning predecessor.
Google is hoping the MUM algorithm system will be capable of comprehending knowledge and information better, using the Text-To-Text Transfer Transformer (‘T5’) to place NLP tasks into a unified text-to-text format.
Google says MUM is used for question answering, document summarisation, and classification activities like sentiment analysis. MUM is clearly highly prioritised at Google and will therefore be significant not only to Google’s search team but to the SEO industry as well. However, is Google currently using it as a ranking signal?
SEOs Claim That MUM Is a Ranking Factor
When MUM was first announced, many people naturally questioned whether it would affect search rankings in general and their own website’s rankings in particular. Every year, Google makes countless changes to its ranking signals, and although many of these updates are not that significant to end users, some have much more of an impact.
BERT is one such case. Google itself dubbed it the most significant change in five years when it was launched worldwide in 2019. And as was to be expected, BERT did indeed have an impact on around 10% of search queries.
RankBrain, which was launched in spring 2015 and is still active, is another of Google’s algorithmic updates that has significantly affected the SERPs in the past. And now SEO experts and site owners are sitting up and taking notice of the increased importance Google has started giving to MUM.
But is MUM, or is it not, one of Google’s SEO ranking factors and signals?
The Case for MUM Being a Ranking Factor
It took Google six months after its launch to announce that RankBrain had been rolled out, while most updates are not confirmed or announced at all. However, Google has improved its practice on sharing important changes before they’re implemented. In November 2018, for instance, the search engine company announced BERT for the first time before launching it in October 2019 for user queries in the English language, then rolling it out worldwide in December of that year.
SEOs were given even longer to prepare for the Core Web Vitals and the Page Experience signal, which Google announced more than a year before their scheduled implementation in June 2021. Google’s already announced that MUM is on its way, and that it’s going to be a major change.
Some SEOs, however, think that MUM could already have been the cause of a drop in rankings that many websites experienced in spring and summer of 2021.
The Case Against MUM Being a Ranking Factor
The President of Google Search, Pandu Nayak, introduced MUM in May 2021, hinting heavily that it was not yet in play. He said that the search engines of today cannot answer search queries like an expert does. But with Google’s MUM algorithm, Google’s search engine is set to get better at answering complex questions, enabling users to conduct fewer searches than ever before to find the answers they need.
Google then announced that MUM will be launched in the distant future, talking in terms of months and years rather than ‘in the now’. Google’s Danny Sullivan also confirmed that the SEO community will be notified in advance before MUM goes live in search.
Nayak explained that they are still improving the MUM system algorithm, although they have already used it to advance Google’s search engine results for users who are looking for COVID-19 vaccine information, for instance. He also said that Google will be offering better methods of allowing users to search using a combination of words and photos in Google Lens in the near future.
As of now, MUM isn’t being utilised to boost or improve search results like neural matching, RankBrain, and BERT do. He also stated that any uses of MUM in the future would be subjected to a thorough evaluation process that includes assessing the usage of AI in a responsible fashion.
MUM is Not a Ranking Factor
In conclusion, then, Google is not currently using MUM as an SEO ranking factor. It’s a language AI model based on Transformer, Google’s open-source neural network architecture. After training it on large data sets as the search engine did with BERT, Google will then fine-tune it for particular uses on smaller data sets, in the same way that it’s currently testing it on improving Covid-19 vaccine search results.
Google shared a few ways in which they could use MUM in the near future, including:
- Understanding information in different formats, such as images, web pages, and more.
- Surfacing helpful subtopics for deeper exploration.
- Surfacing insights based on its comprehension of the world.
- Using it to transfer knowledge across different languages, to break down language barriers.
SEOs might be able to think of ways to optimise better for MUM, but it is too soon to be pursuing these kinds of strategies at present. Nonetheless, there’s no doubt that Google search’s knowledge is expanding at a breakneck speed. As Google’s search algorithms get more sophisticated and better able to understand the nuances and intent in language, the attempts by some SEO practitioners to deceive and manipulate will be less successful and easier to detect.
With an NLP technology 1000x more powerful than RankBrain on the horizon, optimising for human experience is more crucial than ever. For SEOs to stay ahead of MUM, they should concentrate on writing content that’s designed to satisfy the user’s needs.
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