What is Google MUM Algorithm?

Google started to integrate artificial intelligence and machine learning into its search engine, with the aim of better understanding user searches and presenting the most relevant search result to the target audience as soon as possible.

It started in 2019 when Google implemented an algorithm called “BERT,” or Bidirectional Encoder Representations from Transformers. BERT semantically describes the full meaning of a word by connecting it with words that come before or after it. 

In other words, BERT can be defined as an algorithm that helps bring the most relevant results to the top by understanding “long-tailed” keywords much faster. 

Google introduced the MUM algorithm it developed to improve the search engine at its I/O conference in May 2021, and in 2022, MUM was actively used to improve the user search experience within the search engine.

“MUM” or Multitask Unified Model algorithm is defined as a new Google search engine algorithm, which is more powerful than BERT, which is established to semantically analyze and create content and keywords like a human does. 

This multi-media approach means that MUM can unlock information from different formats and make connections among different types of information, enabling Google to provide better answers to complex search queries

What Is The Purpose Of The Google MUM Algorithm?

According to the analysis made by Google, users who especially use complex search queries can reach the desired result by clicking through 8 different links/sources. 

With the newly used Multitask Unified Model algorithm, Google is trying to lower the number of those 8 different clicks.

Using MUM artificial intelligence technology, the user will be able to access clearer search results for the following queries; 

• Search queries with long phrases
• Search queries containing multiple but related phrases
• Comparisons based on long search queries
• Queries made with visual preferences
• Calls made via artificial intelligence-based smart devices (Smart assistant, voice calls, etc.)

New Search Options in Google Lens 

It is necessary to plan your content strategy by taking Google’s approach into account. If the content is being prepared for a certain product, it is necessary to address every step of the target user experience. 

For example, if bicycle parts will be sold online, the matching content should represent the whole user journey involved. 

It is recommended to consider all kinds of questions and information that will take the user from needing a new bicycle part to buying a part from the website or from the store, and website optimization is recommended in this regard.  

For example, let’s analyze together how you can reach users who want to buy bicycle chains. The user research is probably within the following search queries:

• Which chain fits my bike?
• Bicycle chain prices.
• How to change a bicycle chain?
• Where can I get my bike chain repaired?
• How to repair a bicycle chain?

Answering all these user queries within the website gives way for common points to be made in the customer’s entire journey. 

Effective Use of Google Merchant Center 

Google Merchant Center is a program that allows products to be verified with Google and to be listed on various Google service pages. 

Basically, when Google needs to make a product recommendation, it leverages a product from its Merchant Center’s verified product pool. 

The more up-to-date and effective the Merchant Center structure is, the more users can be reached within the search results.

Setting up Markup Structure for all Pages. 

If users want to appear in search results on Google, it is necessary to help Google find relevant information on your pages. The most obvious method of doing so is to make appropriate markups in the content used.

* YouTube Metadata : Helps Google analyze video content and break it down into smaller pieces. Videos can be segmented by adding subtitles and also adding timestamps so that Google has a breakdown of the video content.

* Schema Markup : Helps get feature snippets in search results and highlights important pieces of content on the web page. It can be used to enhance product pages, Q&A sections, reviews, business details and blog articles.

·       HTML Tags : It is preferred to highlight important text parts and define images on the WEB page. Titles, meta descriptions, titles, and image alt texts are among the essential HTML tags for SEO; along with support featured snippets and image search.  

Multimodal Content Creation. 

In the past, Google preferred to answer some queries with text, some with video, and some with images. Google today includes text, images and video altogether in the search results for almost all queries. In other words, it offers results by choosing multiple different content types.  

If it is important to be visible in search results with video, visual, and text content along with the web page. It is also necessary for an admin to construct a multi-domininal structure that includes images, text, and video in the page’s content structure.

Dividing page contents into few parts. 

The clean content structure helps Google pull paragraphs of text or video segments from the content. To create clean content structures, the following points should be considered:

• Content should be divided into paragraphs and subsections. 
• Paragraph titles should be rich in keywords.
• Appropriate marking should be used to highlight sections.
• Sections should begin with short paragraphs that fully answer the query.

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