Google Search Ranking Systems 2024

Industry Update
Technical SEO

Google Search Ranking Systems

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Current Systems - Part 1

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What’s It For?

How Does It Work?


(Bidirectional Encoder Representations)

Allows Google to better understand the meaning and intention of a message through words placed in differnet combinations

Using a technique that mimics cognitive attention to gather information about the relevant context of a word and then encode that into a vector that best represents the word

Crisis Information Systems

Providing specific bits of content during times of crisis or when an SOS needs to be in place, like at the time of a natural disaster. 

Shows local, federal and international alerts from authorities, and brings relative content readily available such as phone numbers, donations, maps, translations, and more

Deduplication Systems

Removes search results that are too similar by only showing those most relevant to the prompted search

Google sorts through all the content provided during a search and shows only the most relevant to the search conveniently on the first page

Exact match domain system

Doesn’t allow for domains that match queries exactly to become the most relevant but instead domains and sites with the most relevant content will be high in the rankings

Google uses this system to sort through sites that have designed domains to fit one exact search, for example; “best-parks-in-the-city.” This is just one of many factors used to determine the relevance of content

Freshness systems

Show the newest content in relation to the prompted search where it’s expected by the user

Some content being searched demands the most up to date information and articles. When a natural disaster strikes content that appears under that search will likely be news stories, and up-to-date information. Whereas if it’s a search when nothing has happened you may see emergency preparedness plans and other resources

Helpful content system

Used to ensure that people using the search engine see original and usefulinformation rather than that which has been curated to meet a specific search and gain traffic

Uses a variety of automated ranking systems to identify content that has little to no value for search results. Sites that have already been deemed of little value that have relevant content are less likely to appear in search results just as sites with relevant information could be less visible due to one article of no-value

Technically, the helpful content update no longer exists as a separate system after the March 2024 Google core update launched. Google’s core ranking algorithms now assess whether content is helpful.

Link analysis systems and PageRank

Systems designed to help Google understand what the page is about and what pages may be the most helpful because of how they link to one another

PageRank is the most widely relied on system for this. This system uses the link structure of the Web to calculate the proper ranking for each web page to improve and personalize search results for the user by providing the best results in response to the query

Local news systems 

Identify and show the most local and current news as its reported through features in search results like “Featured” and “Local News”

When a user prompts a search regarding local news or events including the most popular “news near me,” the system couples the users location with a featured carousel of topics and articles including top stories that best match that location


(Multitask Unified Model) 

This system is an AI that both generates and understands language that's not currently used in their general ranking but for more specific applications; such as improving search results for COVID-19 vaccine information or featured displays

A thousand times more powerful than BERT, this system is trained with 75 languages and many tasks at a time to gain better comprehension of information and world knowledge. It can also work to understand information from images and more in the future but is currently in experimental programs

Current Systems - Part 2

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Name What’s It For? How Does It Work? Reference

Neural matching

AI system used to help Google better understand the concept behind a query or page and then match those with like concepts together - a sophisticated retrieval system 

Rather than just using keywords to understand relevancy between articles and pages this system uses more general concepts of the information by looking at the entire page or query rather than just keywords. It allows for further personalization of the search by better understanding the user and concept behind the query

Original content systems

This system works to show original content before secondhand pages and articles merely citing it 

Using algorithms and constantly evolving efforts, this system has changed from showing only the most relevant content to highlighting those original stories that brought information to light. The original article stays in the forefront while the user can then look at more recent articles and pages alongside the original

Removal-based demotion systems

Used to remove certain types of content from search results with two main categories; legal removals and personal information removals

Allows for users to report information that should not be publicly available and once the system receives a large number of reports for a certain site or content it will reevaluate the search results to not include these results. The most common reports are valid copyright removal requests and exploitative removal requests

Page experience system

System that ensures users are receiving sites and content with the best overall experience 

This system evaluates a variety of benchmarks and then decides the overall experience a user will have with a website. Things like mobile-friendliness, how fast the page loads, security, and more. This helps in situations where multiple sites have relevant content but those that may be more user friendly and offer a better experience will be higher in the rankings

On Apr 21, 2023, Google completely removed the page experience system from the page. It was not moved to the “retired” systems section. It was removed entirely.

Clarification: Sullivan wrote a long post on Twitter, saying, “This just meant these weren’t ranking *systems* but instead signals used by other systems.” Why did Google make this change? “We dropped the systems that were actually signals so that if people did go to that page in the future, they wouldn’t (hopefully) get confused,” he added.

Passage ranking system 

AI system that identifies sections or “passages” of a site to better understand its relevance to a certain query

Designed to better help with specific searches, this system identifies full passages on a website to determine the overall relevance of the content in comparison to the search that was performed. It can help to find that “needle-in-a-haystack” piece of information you were looking for

Product reviews system 

Rewards those who provide high quality reviews, insightful and helpful content analysis and/or original research from enthusiasts who are experts on the topic 

Evaluates the content on product review content to determine its overall quality and relevance on an overall page basis. Those sites and pages with the best content and reviews will be pushed higher into the rankings


AI system used to understand the relationship beween words and concepts to return more relevant content

By understanding how words and concepts relate this system can prompt more and better information with search results that fit a query even if the information on the site doesn’t contain the exact words of the search

Reliable information systems

Works to show only the most reliable information in relation to your search by lowering rankings of low-quality sites and highlighting quality journalism

This system works in partnership with journalists by developing guidelines to use certain criteria in content and publishing to provide Google users with the most relevant and quality information possible. And where information may be less than desirable, Google will share content advisory warnings

Site diversity system 

Allows more sites to be seen and keeps relevant sites from having more than one or two search results at the top of the page

Looks to domains to help sort through results and not share more than one listing from one site unless other systems determine the content to be the most relevant

Spam detection systems

Removes information that defies Google spam policies to keep annoying and misleading information and ads out of your search results

Uses systems such as SpamBrain to sort through information and deal with the content that violates policies and any content that does not meet guidelines is either removed immediately or flagged by the system and then manually removed by staff

Retired Systems

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What’s It For?

How Does It Work?



A major update to overall ranking systems in 2013 

Continuous improvement and upgrades through new code and updates

Mobile-friendly ranking system 

A system that ranks mobile-friendly content higher

Now incorporated into the Google page experience system would return searches with content that renders better on mobile devices if users were using a mobile device for the search

Page speed system

System that gives preference to content and sites that load quickly on mobile device systems

Sorts through content and presents search results with relevancy and that would load quickly on the users mobile device

Panda system 

System designed to present exceptional and unique information 

Uses algorithms to present users with the highest quality and most original content in response to their query while also dropping rankings on sites that are not useful

Penguin system

System designed to combat link spam 

This system uses algorithms to find and then demote sites with spammy link-building practices so they don’t rise high in the search rankings

Secure sites system

Show sites in the search results with secure HTTPS to encourage growth in those sites

When all information across sites is equal, the system will show sites at the top of the search results with secure HTTPS first over those without

Industry Update
Technical SEO
Dean Long | Expert in Growth MarketingDean Long

Dean Long is a Sydney-based performance marketing and communication professional with expertise in paid search, paid social, affiliate, and digital advertising. He holds a Bachelor's degree in Information Systems and Management and is also a distinguished MBA graduate from Western Sydney University.