Google has become much more than a place to search for local food spots or random questions about celebrities. Thanks to the wealth of knowledge out there and all the content creators and services, people turn to Google for education, career advice, finance news, medical insights, travel plans – you name it. Google is helping us all with our big decisions and the more complex questions we have, and one scheduled tech update to help with that is MUM.
What does MUM stand for?
Standing for Multitask Unified Model, Google’s MUM provides a way of answering the more complex queries that can’t be answered with a few sentences in a passage or featured snippet. Think of Google’s tech bots becoming a bit smarter by broadening its resources to suss out how a greater range of sources can work to provide more refined answers.
Globalised SEO: foreign content considered
A key feature of MUM is its ability to scan across a range of platforms in different languages to pick out different sources of information – solving answers by using the total sum of knowledge about a topic, even if it’s in a different language! How would that be helpful; why is that a good thing? Well, why listen to a blogger down the road for an ‘authentic Spanish’ recipe when you’ve got an actual Spanish chef’s website sharing amazing recipes passed down for generations? It doesn’t get much more authentic than that. It’s just a little hard if you’re not fluent in Spanish, so that’s how MUM can help.
Another benefit is finding out key information that only a native might know about. Google used an example of using native Japanese content for search queries related to hiking Mount Fuji, drilling down to subtopics that only those in Japan could properly answer for you.
More than keywords?
MUM carries another feature with it, one that uses a mix of images and text to help answer queries. That’s made a lot of SEOs worry. How can you optimise for a question whose answer can be found partially in an image? Google says:
“Eventually, you might be able to take a photo of your hiking boots and ask, “Can I use these to hike Mt. Fuji? MUM would understand the image and connect it with your question to let you know your boots would work just fine. It could then point you to a blog with a list of recommended gear.”
When the search model is taking more than keywords into account, it’s searching an entity – a representation of a thing – as opposed to just text and can go deeper into subtopics by understanding it that way. Google goes on to explain:
“Since MUM can surface insights based on its deep knowledge of the world, it could highlight that while both mountains are roughly the same elevation, fall is the rainy season on Mt. Fuji so you might need a waterproof jacket. MUM could also surface helpful subtopics for deeper exploration – like the top-rated gear or best training exercises – with pointers to helpful articles, videos and images from across the web.”
How does MUM affect rankings?
If MUM is drawing from multiple websites from different languages for a query, what does a SERP answer look like? It’s still early days to answer this question. But, if MUM is using multiple platforms and sources, could we have snippets broken down into subsnippets to show different sources in one compact result? Maybe there’ll be a website link to answer the main part of a query with a passage, and then to the side: an image of a recommendation taken from another platform to highlight a key piece of information related to the query. A case of sharing the listing, or the SEO SERP trophy.
What about EAT and YMYL?
More acronyms! The SEO world loves them. MUM also fits into EAT and YMYL. EAT stands for Expertise, Authority, and Trustworthiness; YMYL stands for Your Money Your Life. These acronyms form part of how Google differentiates low-quality content from high-quality content.
Google categorises YMYL content as that of which, if presented untruthfully, deceptively, or inaccurately could directly impact the reader’s health, safety, happiness, or financial stability. And Google takes this very seriously, analysing YMYL pages for authoritative content, which brings us to EAT.
Google looks for if the creator of the main content is an expert on the topic or holds relevant credentials that’s available on the website. So, for example, if you’re searching for medical information, who would you trust: a GP with links pointing to their own profile page full of authority, or a marketing exec writing medical copy based on research? No disrespect to the marketing exec here, but YMYL would certainly favour the GP.
MUM aims to draw from authoritative sources and content that are as accurate and educational as possible, so it makes sense for a developed multitask model to work with and seek out EAT and YMYL content.
MUM’s impact on SEO: should we be worried?
Fitting in perfectly with the pun of ‘MUM’s the word’, the information we do have about the planned update is limited. There’s no clear release date, Google has announced it will roll out “in the coming months and years” and there’s not a lot about how exactly it will impact SEO.
Search Advocate at Google, John Mueller emphasises the incessancy of SEO:
“I don’t really see how [MUM] would reduce the need for SEO. Things always evolve. Remember the SEO joke about changing the lightbulb? [How many SEO experts does it take to change a light bulb, lightbulb, light, bulb, lamp, lighting, switch, sex, xxx, hardcore.] None of that’s been necessary for a while now, which is due to developments like these, and yet, people still have enough to do as SEO.”
It’s just about embracing a hybrid approach. Soon, the SERPs will be adopting the hybrid result for us to work with and take advantage of.
Understandably though, just like any news on AI-powered technology and developments, the initial qualms are natural, but we do adapt and learn to work with better technology that aims to make our lives easier. Humans and robots have been working together for a while now, and if there’s anyone who knows how to embrace new bot technology, it’s SEOs.
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