"What exactly is the Google algorithm?" "Why do rankings shift so dramatically during core updates?" "What should I focus on in the AI Overview era of 2026?"—these are common questions shared by SEO professionals. The Google algorithm is the rule set that determines the ranking of search results, and understanding how it works is the starting point of any SEO strategy. To make sustainable improvements without being swayed by daily tweaks or major core updates, you first need to know what the Google algorithm sees and how it evaluates content.
This article systematically explains the definition of the Google algorithm, the three-step mechanism behind how search results are generated, the main ranking factors (content relevance, quality, E-E-A-T, usability, and backlinks), the history of major updates, the latest trends in the AI search era of 2026, and concrete strategies and applications for handling algorithm volatility—all from the perspective of practical web operations. The goal is to help SEO managers, web marketers, and content creators treat the algorithm not as an "unknown threat" but as a "design guideline."
What is the Google Algorithm? Definition and Overview
Definition of the Google Algorithm
The Google algorithm is the collective set of calculation rules (programs) that Google Search uses to select and rank the most relevant pages from the vast web in response to a user's query. The ranking of a page in search results is determined by this algorithm weighing more than 200 signals (evaluation factors) in combination. Google does not publish the specific internals of the algorithm or the weighting of each factor, so the SEO industry has built its understanding through official announcements, patents, experiments, and various guidelines.
What's important is that the Google algorithm is not a monolithic program but a composite of multiple subsystems (RankBrain, BERT, MUM, the helpful content system, the spam detection system, and more). Each plays a distinct role and works in concert to produce search results. Algorithm changes are accumulated as small daily tweaks, while major updates called "core updates" are rolled out a few times per year—a two-layer operational structure.
The Purpose of the Google Algorithm: The User-First Principle
The fundamental purpose of the Google algorithm is to present the most relevant and useful information to users. Google has consistently advocated a "user-first" philosophy—"focus on the user and all else will follow"—and every algorithm revision is implemented in line with this purpose. The foundational principle is straightforward: content that accurately addresses search intent, comes from trustworthy sources, and provides a comfortable reading experience gets rewarded.
Conversely, tactics that deceive users—hidden text, excessive ads, low-quality auto-generated content, link buying—are detected by the algorithm and devalued. The essence of SEO is not "beating Google" but "delivering value to users so that Google rewards you as a result." This is the operating philosophy that emerges from understanding the algorithm. Rather than reacting to every algorithm shift, keeping the user-first orientation as your anchor is what produces stable, long-term organic traffic.
The Relationship Between the Algorithm and Updates
"Google algorithm" and "Google update" are often confused. The algorithm refers to the ranking rules themselves, while updates refer to the changes and revisions applied to those rules. Google performs thousands of small algorithm adjustments per year, most of which are not announced in advance. On the other hand, changes that significantly affect overall search results are rolled out as "core updates" two to four times per year, with prior announcements on Google's official accounts and the Search Status Dashboard.
In addition to core updates, Google also runs updates focused on specific areas. Examples include the "spam update" aimed at strengthening anti-spam detection, the "helpful content update" (now integrated into the core system) that evaluates user-first content, and the "reviews update" that improves review site quality. These purpose-specific revisions running alongside core updates is the modern operating style of Google. To avoid being shaken by every change, it is essential to understand the overall design philosophy of the algorithm rather than chasing each new tactic.
How the Google Algorithm Works: Three Steps to Search Results
Step 1: Crawling
The first step Google takes to produce search results is crawling. A crawler (an automated browsing program) called Googlebot follows links on the web, discovers pages, and retrieves their HTML content. Information about newly published, updated, or deleted pages is captured continuously through this crawl process. Whether a page becomes a crawl target depends on internal and external linking paths, XML sitemap submissions, robots.txt settings, and similar signals.
For medium to large sites, the concept of "crawl budget" is important. Because Google sets a limit on the crawl resources allocated to each site, having too many low-quality or duplicate pages reduces the crawl frequency of the pages you actually want evaluated. Visualizing crawl behavior via Search Console's "Crawl stats" report and using noindex, canonical, and robots.txt strategically to exclude low-value URLs from crawling is a prerequisite for being correctly evaluated by the algorithm.
Step 2: Indexing
Pages obtained through crawling are then registered in the search engine's database, called the index. During indexing, the page's HTML is parsed to extract text, images, video, structured data, and more, and the system understands what the page is about before adding it to the database. Pages that are not indexed will never appear in search results no matter how good their content is, so continuously monitoring index status is a fundamental SEO task.
As of 2026, Google has become quite strict in judging whether a page is "worth indexing." Pages with thin content, high duplication with other pages, or judged to provide low user value increasingly remain unindexed after being crawled—or are excluded after being re-evaluated. Sites that frequently see "Crawled - currently not indexed" or "Discovered - currently not indexed" in Search Console's "Page indexing" report should move beyond simply chasing page counts and commit to consolidating, deleting, or rewriting low-quality pages, which is the shortest path to lifting overall site evaluation.
Step 3: Ranking
When a user enters a search query, Google extracts highly relevant pages from the index and determines rankings by weighing more than 200 signals in combination. This is the "ranking" step, the core of what people mean by "the Google algorithm." Ranking determination involves the relevance of the query and content, the quality of the page and the site overall, E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness), the quality and quantity of backlinks, usability signals, the searcher's intent and context, geography, language, and more, all interacting in complex ways.
In recent ranking, machine learning systems (RankBrain, BERT, MUM, and more) play a major role. They deeply understand the intent and context of search queries, enabling evaluation that goes beyond surface-level keyword matching. Conversational queries like "where's the nearest cafe?", searches phrased as questions rather than keywords, and multimodal searches combining images and audio—human-like language understanding and intent interpretation are now reflected in ranking. This is why the algorithm should be understood not as a simple formula but as a composite AI system.
Major Ranking Factors of the Google Algorithm
Content Relevance and Alignment with Search Intent
At the foundation of ranking factors is the relevance between the search query and the content. The starting point of evaluation is what the page is about and how precisely it satisfies search intent for the user's query. Relevance is judged not only through keyword matches in titles, headings, and body text, but also through comparison with other pages on the same topic, natural use of co-occurring terms, and alignment with the four types of search intent (Know, Do, Go, Buy)—all on a contextual understanding basis.
In practice, the design starting point is whether your content covers what users searching for your target keyword are actually looking for. The standard approach is to analyze the headings, coverage, and information depth shared by the top-ranking pages, and verify that your own content addresses search intent without gaps or excess. Rather than keyword stuffing, multi-faceted explanation of a topic—the "deep dive into the subject"—is the foundation of design that the algorithm rewards.
Content Quality and E-E-A-T
The evaluation framework Google emphasizes for content quality is E-E-A-T (Experience / Expertise / Authoritativeness / Trustworthiness). It was originally E-A-T (Expertise, Authoritativeness, Trustworthiness), but "Experience" was added in December 2022, placing greater value on first-hand information based on the writer's lived experience. Google states that E-E-A-T is not a direct ranking factor itself, but a combination of signals used to identify content with strong E-E-A-T is used in ranking—making it substantively a critical evaluation axis.
Particularly in topics called YMYL (Your Money or Your Life)—health, medicine, finance, law, and other areas that significantly affect people's lives—E-E-A-T standards are applied with much greater rigor. Expert review, clearly stated operator information, cited sources, and presentation of credentials or achievements directly affect evaluation, so medical and financial media especially need to invest in strengthening E-E-A-T. In practice, organizing author profiles, expanding the operator information page, clearly citing sources, and building a review process are concrete actions that strengthen E-E-A-T signals.
Usability and Page Experience
In addition to content itself, page usability and reading experience also affect ranking. Google officially lists Core Web Vitals (LCP, INP, CLS), mobile-friendliness, HTTPS, and the absence of intrusive interstitial ads as page experience signals. As Google has stated, "when other signals are equal, content that is more accessible to users tends to perform better," so usability plays the role of a tie-breaker—when content is equivalent, the more usable page wins.
As of 2026, the mobile-first index, which evaluates ranking on the assumption that mobile browsing accounts for the majority, is fully standardized. Responsive design, optimized rendering speed, sufficient tap-target sizes, font legibility, suppression of layout shift, and other elements that enable comfortable mobile reading are now prerequisites. Use PageSpeed Insights and Search Console's "Core Web Vitals" report to periodically check the metrics and aim to keep them in the "Good" band (LCP <= 2.5s, INP < 200ms, CLS <= 0.1).
Quality and Quantity of Backlinks
Links from other sites (backlinks) have been a ranking factor Google has emphasized since its founding and remain an important signal today. Backlinks function as "recommendations from others," and backlinks that naturally accumulate from highly relevant sites are strong signals of a site's authority and trustworthiness. On the other hand, link buying, link farms, and unnatural auto-generated backlinks are detected by Google's anti-spam algorithms (from the old Penguin to today's SpamBrain) and become subject to penalties.
In practice, the principle is "quality over quantity." Earning a single natural link from an authoritative site within your industry contributes far more to evaluation than collecting large volumes of links from low-relevance sites. To earn high-quality backlinks, the orthodox approach is to create and amplify "content worth linking to"—publishing original data, releasing research reports, interviewing experts, speaking at industry events, issuing press releases, and consistently building presence through SNS and communities. Rather than artificially collecting links in the short term, the right stance—aligned with the algorithm—is to create conditions where backlinks accumulate naturally over the medium to long term.
History of Google Algorithm Updates: Reviewing the Major Shifts
Panda, Penguin, Hummingbird: Foundation Building in the Early 2010s
Looking back at the history of the Google algorithm, the 2011 "Panda update" was a major turning point. It substantially devalued low-quality and copied content, becoming the starting point of modern SEO with content quality at its core. The 2012 "Penguin update" targeted unnatural backlinks and was deployed as a countermeasure against link spam. Both have since been integrated into SpamBrain and the core algorithm, and the rigor against low-quality content and spam links has been consistent up to today.
The 2013 "Hummingbird" was a large-scale algorithm rewrite aimed at supporting conversational search, accomplishing a shift from word-by-word matching to whole-query semantic understanding. From this point on, conversational and question-style queries like "where's the nearest cafe?" began returning context-aware results, laying the foundation for today's natural language understanding systems such as BERT and MUM.
Mobile Support and the Medic Update: Quality Strengthening Period 2015-2017
The 2015 "Mobile Friendly Update" (nicknamed Mobilegeddon) was a historic revision that explicitly added the presence of mobile support to ranking factors. From that point, responsive design and mobile optimization became prerequisites for SEO, and from 2018 the "mobile-first index," which prioritizes evaluating mobile content, was applied in phases. The algorithm caught up with the social shift toward smartphones becoming the dominant search device.
As a Japan-specific development, the December 2017 "Medic Update" was an important milestone. Against the backdrop of issues with medical curation sites such as WELQ, then a social problem, search rankings for low-credibility information in the medical and health fields were significantly lowered. From this point, the importance of E-A-T (as it was then called) in YMYL areas began to be strongly recognized in the Japanese market as well, and measures such as expert supervision, operator information, and source attribution became established as industry standards.
BERT, Core Updates, and Helpful Content: Connecting to the AI Era
The 2019 introduction of "BERT" was a major revision that brought deep learning into natural language processing in earnest, enabling Google to understand the relationships between words around a search query. As a result, accuracy on long-form queries and complex questions with prepositions improved significantly. The 2021 "MUM (Multitask Unified Model)," said to be 1,000 times more powerful than BERT, is a multilingual and multimodal model that enables cross-image-and-text understanding and the handling of complex compound queries.
The "Helpful Content Update" that arrived in August 2022 globally devalued "content written for search engines that provides no user value." It was integrated into the core system in the core updates from September 2023 onward, and is now incorporated continuously into core updates rather than running as a standalone named system. Around the same time, "Experience" was added to E-A-T, becoming E-E-A-T, and the value of first-hand information based on the writer's lived experience was more clearly positioned as an evaluation axis.
Latest Google Algorithm Trends in 2026: Search in the AI Overview Era
Full-Scale Rollout of AI Overview (SGE)
Between 2024 and 2025, Google's generative AI search feature "AI Overview" (formerly SGE) was rolled out at full scale in countries worldwide including Japan, and by 2026, AI-generated answer summaries appear at the top of search result pages in a large share of cases. Because AI Overview synthesizes information from multiple web pages to generate an answer in response to a user's question, "zero-click searches" where users get their answer without clicking the traditional blue links have increased notably. Pages ranking below position 2 tend to see significant click reductions, and the prerequisites of SEO strategy are shifting.
The fundamental approach for AI Overview is to design content that AI is more likely to choose as a citation source. Clear heading structure, writing that leads with the conclusion, implementation of structured data (especially FAQPage, HowTo, Article), citation of trustworthy sources, and publishing original data or first-hand information all increase the likelihood of being picked as an AI citation. We need to redefine the value of "being seen even without being clicked" and design a comprehensive marketing strategy that includes routes other than organic search—branded search, direct traffic, and SNS-driven visits.
AI Mode and the Conversational Search Shift
"AI Mode," officially rolled out in the US in 2025 and now supporting Japanese, is a new feature where the entire search page is composed as a conversation with AI. Instead of the conventional list of links, users narrow down information by repeatedly asking AI questions, and links to source sites are shown only in a limited way. Search behavior itself is shifting from "looking for links" to "asking AI," and we are entering an era where the definition of SEO itself needs to be expanded.
In response to this change, a new concept called "AI search engine optimization" (referred to as AIO, AEO, GEO, and so on) is gaining traction. To get AI models to accurately learn and reference your site's information, what becomes important is being recognized as an entity (a specific person, place, or concept), providing structured data, being referenced by trusted third-party media, and being included in Wikipedia or the Knowledge Graph. Maintaining traditional SEO fundamentals while adapting to the new evaluation axes for AI search is the approach SEO professionals need to take from 2026 onward.
Core Updates and Evaluation Trends in 2026
Starting with the "March 2026 core update," Google has continued to deploy core updates. The trends most visible in recent core updates are intensified countermeasures against low-quality AI-generated content, increased emphasis on originality and expertise, and the thorough prioritization of user value. Sites that have only the surface trappings of E-E-A-T, and template-style content that only superficially answers search intent, are losing rankings more easily with each core update.
Also worth noting is that in February 2026, a core update dedicated to Google Discover was deployed for the first time. As a result, evaluation criteria for SERPs (search result pages) and Discover may begin to update separately, and media that depend on Discover traffic now need to monitor it on a separate axis from search rankings. Tracking SERPs and Discover separately and adopting designs that address both is what stabilizes traffic going forward.
Strategies and Applications for Handling Google Algorithm Volatility
How to Respond When Rankings Drop During a Core Update
When rankings drop during a core update, the most important thing is "not to panic and rush into countermeasures." Rankings continue to fluctuate during the typical 2-to-4-week rollout period, so making decisions based on numbers seen before rollout completion is premature. The correct order is to first verify rollout completion on the Google Search Status Dashboard, and then analyze Search Console data.
The concrete analysis procedure is to compare the periods before and after the update in Search Console's "Search performance" report and identify which pages and queries are fluctuating. Find the patterns common to pages that dropped—weak E-E-A-T, thin content, gaps from search intent, insufficient internal linking, association with low-quality pages—and pursue improvement on both content quality and on-page technical sides. Because immediate post-drop improvements are reflected only at the next update, a measured improvement plan on a 3-to-6-month cycle is necessary.
SEO Design That Doesn't Get Shaken by the Algorithm
The strongest position against algorithm volatility is to maintain a state where, no matter how Google changes, you continue to be evaluated as "a site that delivers value to users." Concretely, this means continuing to execute "measures aligned with the algorithm's fundamental purpose"—deep alignment with search intent, continuous strengthening of E-E-A-T, publishing original data and first-hand information, enriching expert review and operator information, maintaining Core Web Vitals, building a logical site structure, and earning backlinks naturally.
These do not produce quick results, but they enable building "asset-style" SEO that maintains and grows evaluation through every core update. Conversely, SEO that depends on techniques and tricks gets rattled with every algorithm revision and cannot sustain stable organic traffic. The mindset of "build a foundation that holds rankings for 3 years" rather than "raise rankings in 3 months" is fundamentally a stronger approach under modern algorithms.
Application: Using the Algorithm as a Design Guideline
By using the Google algorithm as a "design guideline for your site" rather than "something to defend against," you can transform SEO into an offensive practice. For example, when building a new site, design the site structure with the three steps "crawl -> index -> rank" in mind from the start, so each page is optimized from day one across crawlability, indexability, and usability. When planning new articles, build in search intent, E-E-A-T, and AI Overview citation suitability as the initial design requirements.
It is also effective to replace your content operations evaluation metric from "number of pages published" with "algorithm fit." By setting KPIs and observing them regularly—the ratio of "Crawled - currently not indexed" in Search Console, the percentage of Core Web Vitals in the "Good" band, and the completion rate of E-E-A-T-related items (author profiles, operator information, source attribution)—you can quantitatively track how close your site is to a structure the algorithm easily rewards. Using the algorithm as a map rather than an enemy is what stabilizes the long-term outcomes of SEO.
Summary: The Google Algorithm Embodies the "User-First" Design Philosophy
The Google algorithm is a composite evaluation system designed to deliver the most relevant, valuable information to users. Search results are generated through the three steps "crawl -> index -> rank," and at the ranking stage, more than 200 signals are weighed in combination—content relevance, quality, E-E-A-T, usability, backlinks, and more. Core updates two to four times per year carry out major revisions of evaluation criteria, and countless small revisions accumulate continuously in between.
In 2026, search behavior itself has changed substantially with the spread of AI Overview and AI Mode, and the definition of SEO has been expanded to include optimization for AI search. At the same time, the foundational principles—user-first, providing valuable content, ensuring trustworthiness—have remained consistent since the Panda update of 2011, and measures grounded in this axis continue to have the resilience of not being shaken by algorithm changes.
What is important for practitioners is to use the Google algorithm as a "design guideline for your site" rather than treating it as an "unknown threat." Aligning with search intent, continuously strengthening E-E-A-T, thorough on-page optimization, optimizing Core Web Vitals, and implementing structured data with AI search in mind—steadily layering these up is the shortest route to building a site that continues to be evaluated no matter how the algorithm changes. Use this article as a starting point to inspect your site through an algorithm lens and step into operating your website as a long-term asset that earns the trust of both users and Google.
