Google ranking systems: what they are, how they work and strategies
A complex machine, which in a fraction of a second is tasked with sorting information from hundreds of billions of web pages to provide users with the most useful information and always ensure the best possible experience. These are Google’s sophisticated algorithms, which as we know are activated behind the scenes every time we launch a query on the search engine, following precise instructions. Today we are going to learn about precisely the Google Search ranking systems, the ranking systems that Google uses to rank content by analyzing and evaluating hundreds of signals and details, ranging from the meaning of the keywords in the query to the quality of the content, via loading speed and relevance to the user’s context. Over the past few years, Google has refined its communication to explain how these algorithms work, introducing a clearer distinction between currently active systems, the underlying technologies that power the results, and legacy systems that are now integrated or deprecated. The goal? To provide transparency and offer site owners, webmasters, SEOs, and content creators practical guidance for optimizing their websites. Our guide then delves into what Google’s ranking systems are, how they work to answer user queries and structure SERPs, and what signals and technologies underlie them, while also trying to draw useful insights to improve the organic visibility of our pages.
What are Google’s ranking systems
Google’s ranking systems are automated algorithms designed to sort search results based on criteria of relevance, quality and usefulness. These systems analyze numerous signals – from keywords to source reliability, from page usability to geographic context – to determine which content best responds to user queries.
Ranking systems are thus the engine that powers Search and enables users to get (ideally) useful, relevant, and reliable answers to every query: operating constantly in the background, they examine, evaluate, and rank the content on the Web, transforming billions of pieces of information available on the Web into organized and easily accessible answers.
Each system is designed to work to certain classification requirements, and their role is critical in linking the vast amount of information available online with the user’s actual needs, sorting the results so that they accurately meet the intent of the search.
This complex mechanism relies on several “ranking systems, ” some of which are part of Google’s main ranking systems, which are the underlying technologies that produce search results in response to queries, while others are involved in specific ranking needs.
Why ranking systems are crucial
Google’s ranking systems are an indispensable element of Search management. Their function is not limited solely to the ranking of web pages, but helps to ensure the accuracy and relevance of the results proposed to users. Without them, the search engine would not be able to meet the growing expectations of the public, who expect not only quick, but also highly accurate answers.
The main task of ranking systems is to interpret user queries in their precise context, relating search intent to the most reliable and useful content on the web. To do this, these algorithms evaluate each result from multiple perspectives, considering both the intrinsic value of the content and its relationship to the site that hosts it. This multilevel approach makes it possible to establish a precise hierarchy of results, rewarding relevant, quality and well-optimized information.
The centrality of ranking systems in the operation of Google is also a signal to those who manage a website. Each new technological development or update introduced can directly affect the visibility of online content, making it essential to constantly adapt to the logic of ranking to keep up with changes.
What is the difference between ranking systems and updates
Understanding the difference between ranking systems and updates is important to understanding Google’s modern approach to Search. Until a few years ago, the terms “system ‘ and ’update ” were used almost interchangeably, often creating confusion among webmasters and content creators. In 2022, Google decided to introduce a new lexical approach that clearly distinguished between these two components.
When we talk about ranking systems, we are referring to permanent technologies that operate constantly in the background to sort search results. These systems, such as PageRank, BERT, or Neural Matching, are part of the foundation of Google’s ranking and continue to be used over the long term. Updates, on the other hand, are temporary, targeted interventions aimed at refining an existing system or adding new ranking capabilities. They do not, therefore, represent stand-alone technologies, but episodic changes that improve an existing system.
This shift in perspective has been important not only to clarify the functional distinction between the two terms, but also to eliminate historical ambiguities in Google’s communication. For example, a system such as “Reviews System” is not a simple update: it is a complete, self-contained technology designed to work steadily over the long term and improve the overall functioning of Search.
How Google’s ranking systems work
Google’s ranking systems work as an automated engine that analyzes billions of pieces of content in a split second to organize search results in the most useful and relevant way. This process starts with query interpretation, goes through user intent analysis, and finally ranks relevant content based on multiple signals and criteria. Through the integration of advanced techniques, such as artificial intelligence and natural language models, these algorithms evaluate each result considering a variety of perspectives, never losing sight of the goal of satisfying the user’s search intent.
Each ranking system contributes in its own specific way, with different technologies working together to offer appropriate answers to each search query. On the one hand there are the core systems, which constantly operate on all queries to define the overall ranking, on the other hand we find algorithms that are triggered only in particular situations, as demonstrated by the use of systems for fresh content or local news. This combined approach is the key that allows Google to maintain a very high level of accuracy and reliability.
Google search, key signals used to evaluate pages and content
Given the vast amount of information available, it would be virtually impossible to find what we’re looking for on the Web without an organizing tool: that’s what Google’s ranking systems do, which are designed precisely to sort “hundreds of billions of web pages and other content in the search index to provide useful and relevant results in a split second.”
As mentioned, these algorithms are based on an (extensive) set of factors that also vary in weight and importance depending on the type of search-for example, the date of publication of content plays a stronger role in answering queries related to topical issues than queries about dictionary definitions-but they all fall into five broad categories of major factors that determine the results of a query:
- Meaning. Analyzing the intent of the query to understand what the user is really looking for and linking it to relevant content. This includes the use of advanced language models capable of interpreting semantic nuances and synonyms and understanding how the few words entered in the search box match the most useful content available.
- Relevance. The extent to which a page’s content responds directly to the query, assessing elements such as the presence of the same keywords used by the user on the page, in the headers or body of the text, or the overall analysis of the topic covered. To do this, they use aggregated and anonymized data on interactions to verify that the page has other relevant content besides just keywords.
- Quality. A central parameter that serves to ensure that content that proves most useful is prioritized , particularly by analyzing the page’s ability to demonstrate experience, expertise, authority and reliability – Google’s E-E-A-T parameters – as well as originality and impact for the user.
- Usability. Google calls for favoring content that is more accessible and easily usable by people. Technical factors such as page load speed, overall design for navigation or optimization for mobile devices are critical in determining the overall usability of a piece of content.
- Context. Contextual information such as geographic location, personal settings, and search history help Google personalize results, making them more useful to the user based on the specific situation.
These signals, analyzed separately and in combination, allow Google to dynamically and precisely define the ranking of results, favoring content that not only answers the query, but is useful for the specific user at that particular moment.
Site-wide or page-level signals: a necessary clarification
One aspect that has gained increasing importance in recent years is the distinction between “page-level” and “site-wide” signals, which represent two complementary dimensions that Google uses to evaluate content and determine its ranking in SERPs.
Page-level signals focus on the specific criteria of an individual web page, directly analyzing aspects such as relevance to the query, keyword usage, content quality, and usability. In other words, they determine whether that individual page is useful and fully responds to what the user is looking for.
In contrast, site-wide signals look at the site as a whole, analyzing its overall editorial quality , user experience, and compliance with Google guidelines. This approach considers factors such as the consistency of a domain’s content, percentage of poor quality pages, spam signals, and overall reliability. The integration of site-wide signals allows Google to get a broader picture, which goes beyond examining a single page, to define a site’s overall reputation and modulate the ranking of all pages within it.
The introduction and evolution of site-wide signals, highlighted over the years by historical rankers such as Panda and Penguin, has shifted the focus from optimization solely focused on individual pages to a more coherent and comprehensive view of the entire site. Whereas in the past a well-optimized page could stand out regardless of the rest of the site, today its ranking is inevitably influenced by the overall quality of the domain. In other words, a site with negative site-wide signals could penalize even good, well-constructed content, dragging down its ranking.
At the same time, Google continues to look at individual page-specific signals to ensure that relevant content can still stand out, even on sites with broader issues. This balance between “site-wide” and “page-level” signals creates a more sophisticated and comprehensive ranking system, incentivizing webmasters to attend to both the overall architecture of the site and the quality of each individual piece of content.
Difference between ranking systems and updates
One of the key aspects of understanding Google’s logic is to distinguish between a ranking system and an update of the system itself. This concept, officially clarified by an article by Danny Sullivan in 2022, reflects a major shift in search engine communication: whereas in the past terms like “update” and “system” were used almost synonymously, today a clear line has been drawn between these two elements.
In brief:
- Ranking systems. These are the centralized technologies that constantly operate “in the background” and produce SERP results. Examples of active systems are BERT, PageRank, or Neural Matching. These algorithms never pause, but can be optimized over time.
- Systems Updates. These represent enhancement changes made to an existing ranking system. Updates, often announced by Google transparently, serve to make the system more effective with respect to new web scenarios, update it to user needs, or resolve pre-existing limitations. For example, the “Product Reviews Update” of 2021 was an improvement to the reviews system.
With this distinction, Google not only clarifies the dynamic nature of its tools, but also avoids semantic confusion: an update is occasional, while a system is designed to function stably and permanently. This is also where the lexical evolution comes from: systems such as the “Reviews System” or “Page Experience” are not simply updates, but autonomous algorithmic frameworks.
What Google ranking systems are active today
Google’s ranking systems represent the core of rankings in Search and determine how web pages are ranked in response to user queries. They operate using a complex selection of signals, which evaluate both individual pages (through “page-level” signals) and the site as a whole (through “site-wide” signals) to determine the most relevant and useful results for user queries.
Among currently active ranking systems we can distinguish between basic technologies, applied on a large scale to all queries, and systems designed to handle more specific needs or special situations, such as handling fresh content or reliable information. Also contributing to the overall safety and quality of SERPs are rankers that penalize problematic content or promote variety and trustworthiness. In all cases, the goal remains to ensure balanced ranking and meet the demands of modern users with advanced and constantly evolving technologies.
The list of ranking systems currently in operation is updated regularly, and here we offer the omplete list organized by category, with explanations related to their operation and their role in Google Search.
- Core systems of Google Search
Core systems represent the foundation of Search and are active on all queries. Their primary function is to interpret the meaning of the search and analyze the content of relevant pages. They operate primarily at the page-level.
- BERT. Short for Bidirectional Encoder Representations from Transformers, BERT allows Google to understand how word order and combinations affect the meaning of a query. This AI-based system aims to improve understanding of linguistic nuances by interpreting complex intents.
- MUM (Multitask Unified Model). Short for Multitask Unified Model, MUM is a fast, multilingual artificial intelligence system that understands and generates content, used to support complex or specific queries, such as searching for health content or improving callouts of featured snippets that appear in SERPs. It is not currently used for general ranking in Search.
- Neural matching. This is the system that recognizes representations and conceptual relationships between queries and content. This artificial intelligence algorithm interprets how words are related to underlying concepts, even in the absence of direct matching.
- RankBrain. Introduced in 2015, RankBrain represents one of Google’s first artificial intelligence systems designed to understand implicit meanings and previously unseen queries. It works to return relevant results even when keywords do not exactly match the content by understanding correlations to other words and concepts.
- Link analysis systems and PageRank (Link analysis). Google uses several systems to analyze links between pages and determine their relevance and authority within the web. Among these is PageRank, the historical system that calculates the value of pages based on the network of links connecting them, introduced since the early days of Google, which continues to influence ranking with an operating model and logic that has evolved over time.
- Specific systems for special needs
Google uses ranking systems designed to intervene in specific contexts or on specific types of queries. These algorithms are not as ubiquitous as core systems, but they come into action in situations where their ranking capabilities improve the relevance and usefulness of results by influencing ranking. They operate predominantly at the page-level.
- Passages (Passage ranking). This system uses artificial intelligence to identify relevant sections within a web page that directly answer a query. A single “passage” (or block of text) can be shown among the results, enhancing detailed content even in less optimized pages overall.
- Fresh content systems (Freshness). In some queries (e.g., searches related to recent news or events), timely and fresher content takes priority. These systems reward pages that provide more recent and complete information where freshness is needed and expected, meeting the criterion of “query deserves freshness.” For example, if someone is looking for information about a newly released movie, they will probably want recent reviews rather than articles older than when production began; or, normally a search for “earthquake” might bring up material on the lead-up to such an event related resources, but if an incident has occurred recently, articles with more up-to-date news and content might appear.
- Deduplication systems (Deduplication). These algorithms detect and remove duplicate or overly similar content among search results to deliver a more orderly and inclusive SERP of truly unique pages. Google searches can find thousands or even millions of matching web pages, which can sometimes be very similar to each other, and the algorithms show only the most relevant results to avoid unnecessary duplication. Featured snippets also benefit from this system, avoiding repetition of a result shown prominently on the first page of results.
- Exact match domain system (Exact match domain). This algorithm prevents domains with a name that exactly matches the query from receiving a disproportionate ranking advantage. Google considers the domain name one of the signals, but limits its weight to balance the actual relevance. For example, there is no point in creating a domain name containing the words “the best places to eat lunch” in the hope that all those words in the domain name will push the content up the rankings and provide ranking advantages.
- Local news systems (Local news). Algorithms that give visibility to news sources closely related to a specific geographic context, if relevant to the query, through “Top Stories ‘ and ’Local News” features.
- Reliable information systems (Reliable information). There are various systems for displaying reliable information, such as surfacing more authoritative pages, rewarding quality journalism, and degrading low-quality content; if reliable information is lacking, the systems automatically display content alerts for fast-moving topics or report that Google does not have much confidence-a high degree of certainty-in the overall quality of the results available for search, suggesting to the user how to search in ways that might lead to more useful results.
- Crisis information systems (Crisis information). Google has developed technologies dedicated to personal crisis or natural disaster contexts, responding with relevant content. Specifically, personal crisis situations involve cases where people search for information with queries related to suicide, sexual assault, poison ingestion, gender-based violence, or drug addiction, in response to which Google displays hotlines and content from trusted organizations. More general crises are SOS alerts during times of natural disasters or large-scale crisis and emergency situations, such as floods, fires, earthquakes, hurricanes and other disasters, for which Google shows updates from local, national or international authorities with emergency phone numbers and websites, maps, translations of helpful phrases, donation opportunities and more.
- Dedicated systems for quality and safety
To elevate high-level content and penalize bad practices, Google uses specific algorithms designed to preserve the overall quality of SERPs and protect users. Operating primarily site-wide, they ensure that domains meet Google’s guidelines, protect users from unreliable or manipulative content, and promote the overall quality of SERPs.
- Review System (Review). An algorithm designed to reward high-quality reviews, content that provides in-depth analysis and original research, written by experts or enthusiasts who know the topic well. It was initially called Product Reviews System because it focused only on product reviews, but in April 2023 it was extended to other types of content as well.
- Original content systems (Original content). Designed to reward original and authentic content, including quality journalism, by preventing users from finding worthless copy or citations. Includes support for special canonical markup that content authors can use to help Google better understand what the main page is if a page has been duplicated in multiple places.
- Site diversity system (Site diversity). Designed to ensure that one domain does not monopolize the first page of results, the system limits the visibility of multiple pages from the same site under certain circumstances, maintaining variety and diversity in the SERP. Google may still show more than two results in cases where the systems determines that they are particularly relevant to a given search. Generally, the site diversity system considers subdomains as part of a main domain; that is, tabs from a subdomain (subdomain.example.com) and the main domain (example.com) will all be considered from the same site. However, sometimes subdomains are treated as separate sites for diversity purposes, if that is relevant.
- Removal-based demotion systems. Google has implemented rules that allow the removal of certain types of content, those that are harmful or violate copyright, privacy or laws. If a site receives a high volume of requests or valid signals highlighting such violations, it risks an overall demotion in search rankings. Google specifically distinguishes between legal removals – demotion signals for copyright infringement or claims of defamation, counterfeit goods, and removals by court order; in the case of child pornography, identified content is immediately removed and sites with a high percentage of child pornography content suffer a demotion of all content – and personal information removals– demotion of sites that engage in retaliatory exploitation practices of removals (and possibly also on sites that engage in the same pattern of behavior) or doxxing, explicit personal images created or shared without consent, and explicit nonconsensual fake content.
- Spam detection systems (Spam detection). Search continues to fight huge amounts of spam content through the SpamBrain system. These algorithms detect and remove pages that violate Google policies, countering ranking manipulation techniques (black-hat SEO), and are constantly updated to keep up with the latest ways in which the spam threat evolves, such as in the recent case of site reputation abuse.
Ranking systems no longer active: why Google withdraws algorithms and what happens
Over the years, Google has introduced numerous systems to improve the quality and relevance of the results offered in Search. Some of these systems, now considered “retired,” have had a revolutionary impact in the evolution of SEO and the way content is evaluated. Although no longer operating independently, their principles and technologies have been integrated into core ranking systems or successor systems, contributing to the fundamental structure that still guides ranking today.
Some of the most famous algorithms in history include Panda and Penguin, which profoundly changed the rules of the game by penalizing low-quality content and unfair link spam practices. With the introduction of algorithms dedicated to content quality and user experience, as in the case of the Page Experience system or Helpful Content System, Google pushed web creators and SEO professionals to focus on higher standards, rewarding not only relevance, but also factors such as usability and reliability. These systems represent a key chapter in the history of search engine optimization, and understanding their evolution helps to assess how Google has constantly adapted its tools to deliver an ecosystem based on overall quality.
Which ranking systems are “retired”
The official guide page also lists for historical purposes some of Google’s systems that are no longer independently active, but are now found to be embedded in later or have become part of the search engine’s broader core ranking systems (which are the underlying technologies that produce search results in response to queries).
- Helpful Content. Introduced in 2022 as “Helpful Content Update,” this system promoted useful and original content designed for people rather than to manipulate search engines. In March 2024, it was integrated into the core ranking systems, enriching a broader system that can identify results that are truly useful to users.
- Hummingbird. Launched in August 2013, it was a significant improvement to Google’s ranking systems-which since then “have continued to evolve, just as they had evolved before,” the guide points out. Hummingbird updated the way the search engine interprets queries, focusing on a more natural understanding of user queries. Although it has been retired, the principles it introduced continue to be a key part of current ranking systems.
- Panda. Launched in 2011, Panda was designed to reward high-quality, original content while penalizing pages with duplicate or low-value content. This system was integrated into the core ranking systems in 2015, becoming an essential part of defining the concept of quality content.
- Penguin. Announced in 2012 as Penguin Update, this system combated link spam by detecting unnatural or manipulative links created to alter rankings. In 2016, Penguin was incorporated into core ranking systems, and its principles continue to influence link evaluation.
- Mobile-friendly ranking system. This system ensured that mobile-friendly content had priority over content that offered a poor mobile experience, mostly intervening in situations where the level of relevance between results was relatively equal. Having become an integral part of Page Experience, it is no longer a stand-alone system, but its signals are still present in the main ranking systems.
- Page Experience system (Page Experience). Introduced in 2020 as a stand-alone system to evaluate user experience factors such as passing Core Web Vitals, loading speed, security (HTTPS) and mobile optimization, Page Experience has been redefined over time. Google now views it as a concept rather than a specific signal, with its aspects integrated into other core ranking systems. To be precise, Danny Sullivan clarified that the Page Experience complex has never actually been a ranking system, but “signals used by other systems”
- Secure sites system (Secure sites). Announced in 2014, it was an algorithm that, other things being equal, ensured that HTTPS-protected sites were given priority in rankings; it was later incorporated into Page Experience. According to Google, it helped encourage the growth of secure sites at a time when the use of HTTPS was still quite rare.
- Page speed system (Page speed). Originally announced in 2018 as the “Page Speed Update, ” this algorithm acted as a tie-breaker to better rank content with fast loading times, especially on mobile devices. It later became part of the Page Experience system.
The evolution of Google – and SEO
This information is useful first of all to have a compass on what are the main systems that are currently at work to form Google’s rankings and SERPs, but also to know some interesting details about Google’s consideration of these systems and what contribution they actually provide to ranking.
For example, we can see that in most cases these are tie-breaker systems, that is, they serve to break the parity of factors and conditions thus determining which page and which content should appear first. It is then curious to find out that Google still uses a system that interprets the exact match for the domain, but then concretely tells us that it is not worth investing in such a constructed domain name just for ranking purposes because it would be in vain.
More generally, however, this guide gives us practical information for our business, starting with the lexical shift desired by the search engine-although (at least for now) we will not change the old articles renaming updates to system, thus leaving the old names, also as a matter of habit.
To be sure, this is yet another sign of how much Google is changing and continuing to evolve, both in the way it presents information to users and in algorithm updates, which consequently determine an adaptation of SEO best practices as well, which must keep up with what it means to properly optimize a website today.
For example, until not so long ago the definition of relevance simply meant that a web page had to be about what the user was searching for, but today that is no longer sufficient because content must also be useful, original, and tied directly to the search intent. Google is increasingly moving away from keyword identification to an understanding of the multiple meanings inherent in search queries, and it has made it clear to creators to stop writing content focused only on keywords because it appears unnatural and forced.
The other considerable aspect is context, the setting in which something is said or done, which provides meaning to those actions or settings: today the context of a search query can influence the results, and Google is redefining what it means to be relevant by understanding the user’s context.
Managing ranking systems: best SEO strategies.
The continuing evolution of Google Search and its ranking systems therefore requires a strategic approach to effectively manage the signals that influence ranking in SERPs. For SEO professionals, this means adopting practices that take into account both “page-level” signals, which analyze the quality and usefulness of each piece of content, and “site-wide” signals, which assess the reputation and overall quality of the site.
- Focus on overall site quality
In a landscape where “site-wide” signals are becoming increasingly relevant, it is crucial to work on the overall perception of the domain and brand by Google, which as we know has become crucial for ranking. This means not just improving individual pages, but requires a focused effort to create a consistent, organized and reliable site.
To keep the overall quality of the site high, it is necessary to among other things:
- Ensure consistency in published content, avoiding large quality discrepancies between sections or pages. Low quality content in one part of the site can negatively affect the overall reputation.
- Optimize information architecture to facilitate user navigation and content discovery by Google. Good category structuring, well-constructed internal links, and organized URLs help send a strong signal of trustworthiness.
- Monitor user experience across the domain, considering factors such as performance, accessibility, and security (HTTPS). This is not just about avoiding penalties, but demonstrating attention to the usability of the site as a whole.
- Resolve technical or editorial issues on a global scale: 404 errors, sub-optimal redirects or poor pages can affect the algorithms that analyze the site site-wide.
Google uses site-wide signals to examine the overall trustworthiness of a domain. Creating a healthy, anomaly-free ecosystem improves not only the ranking of individual content, but also the ability to respond to queries competitively.
- Content review and optimization
Content management remains a key pillar of SEO. With the integration of increasingly advanced systems such as Helpful Content System into core ranking systems, content quality takes on greater weight than in the past. Reducing the presence of duplicate, outdated or low-quality content on the site is no longer just a good practice, but a necessity.
Here are some key tips for optimizing content:
- Eliminate or update outdated content, especially content that no longer meets quality or usefulness criteria for the user. Reviewing static articles and pages improves both user experience and signals sent to Google.
- Properly manage duplicate content, using canonical markup or removing repetitive versions that do not add value. Google’s deduplication systems can significantly penalize sites with redundant pages.
- Create content with a user focus, avoiding generalist or overly keyword-focused approaches. Originality, usefulness and relevance with search intent are now the focus of winning strategies.
- Look for consolidation opportunities: multiple pages covering similar topics can often be combined into a single in-depth and comprehensive resource, improving its perceived value.
Regular updates help the site maintain a strong presence in SERPs and convey to ranking systems a clear commitment to reliability and optimization.
- Adapting to the core signals of ranking systems
In addition to specific content or site quality, another crucial aspect of dealing with modern Google ranking systems is aligning with the core signals on which these systems are based. Factors such as E-E-A-T, site loading speed, and responsive design have become inescapable standards for SEO.
To better adapt to the core signals of ranking systems, it is useful to consider the following approaches:
- Enhance E-E-A-T, publish content created by experienced and authoritative authors, with clear references to their expertise (biographies, author pages, citations). It allows you to mark presence to the online brand, strengthening its reputation through reliable links and mentions.
- Optimize loading speed: Tools such as Core Web Vitals are the specific metrics by which to measure site performance. Reducing load times improves both user experience and alignment with Google preferences.
- Embrace mobile-first indexing: verify that the site performs perfectly on mobile devices, ensuring an optimal experience even for users on the go. This is essential to ensure good rankings in a world where smartphone searches dominate SERPs.
- Integrate contextual signals: leverage geolocation data and frequent queries to personalize sections of the site and make content more useful for the target audience.
Keeping an approach in line with evolving ranking systems involves constant work on several fronts: technical analysis, content review, and user experience optimization. This balance allows you to achieve lasting results and be ready to respond to future changes in Google Search.
