How SEO Works Now: The 2026 Guide for Marketers

Phonexa

28 minute read

Understanding how Google works is key to SEO success, but the search giant is reluctant to reveal much about its algorithms. Yet new insights into Google’s search algorithm and operations are emerging, shedding light on how SEO works.

We’ve learned a lot more about how Google works recently. It seems Google pays more attention to user engagement and what people do on your site than anyone thought, and it tracks more signals than we knew.

Read on to learn more about Google search algorithms, how SEO works around them, and how to optimize your website for Google’s organic search. 

“Before AI, just as many other things, SEO was manual most of the time: gathering keywords, researching competitors, identifying content gaps, and so on. Now, though, we can research, draft, and update content much faster, as well as we can process tons of information within minutes or hours rather than days and weeks. Analytics doesn’t scare us anymore.

At the same time, SERPs have changed just as much: AI Overviews, conversational AI Mode, and generated answers are changing what “ranking” actually means. On top of classic SEO, we now get Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO).” – Dmytro Kovtoniuk, an SEO specialist at Phonexa.

How Google Works: Algorithms Explained

How Google works comes down to algorithms: sets of rules and processes that connect users with the most relevant and useful results in response to their queries. Under the hood, Google stores information about websites in its index, which is continuously updated with the help of Google crawlers ‒ bots that collect website data needed for indexing.

Source: Google

Here is how Google works when a user enters a query: it matches it with its database of websites – in a fraction of a second – and presents the most useful sources at the top of the list, going from the most helpful to the least helpful among relevant websites.

Knowing exactly how Google works at the matching and ranking stages is the holy grail of SEO. Simply having relevant information on a given topic doesn’t guarantee your site will appear on a SERP, because many other variables are involved, like content freshness, technical site characteristics, the availability of certain content elements, and many more. 

Based on Google’s publicly available documentation, we’re not sure we understand how Google works across all the factors that affect rankings, and we know even less about how they interact or complement each other to push sites to the top.

In some ways, how SEO works in practice looks a lot like it did ten years ago. We find the leading websites in a niche, analyze what makes them strong, and try to build content that gives users more value than they get anywhere else.

“The AI boom led to everyone publishing AI content to scale fast. However, although we can find some success cases even with AI content, the March 2024 core update made it clear that only helpful content that matches real user intent works, backed by real experience and expertise.

What hasn’t changed is how little we know about ranking factors. The 2024 leak of Google’s Content Warehouse API documentation listed more than 14,000 attributes, but nobody knows how much each factor counts or how they affect each other.“ – Dmytro Kovtoniuk, an SEO specialist at Phonexa.

In reality, SEO specialists rely on both official information and analytical data to piece together how Google works. Meanwhile, Google changes rules regularly, making the puzzle-solving ever so interesting yet ever so complex. 

Google Algorithm Technologies

Google’s core algorithm includes various components that sort search results to fit current consumer trends and continuously present more accurate responses to user queries. Some of these appear in the official documentation, while others are rarely or never discussed, and the public learns about them from personal practice or even anecdotally from colleagues. 

RankBrain

In 2015, Google introduced RankBrain, a self-improving AI technology that uses machine learning to better process user queries and resolve ambiguity. In two years, RankBrain evolved from handling around 15% of search results to processing all of them. It changed how Google works with queries it has never seen before. 

BERT  

Introduced by Google in 2019, BERT is a natural language processing (NLP) technology developed to better contextualize queries. While previous models analyzed each word in a query separately, BERT takes a keyword phrase as a whole and offers users more precise results. 

For example, if you typed “Brazil traveler to the USA need a visa,” the search engine without BERT wouldn’t know if you were traveling from the USA to Brazil or vice versa. Now, the search engine understands the context provided by the syntax which is a real shift in how Google works with natural language. 

Source: Google

DeepRank

DeepRank is one of the latest additions to the family of Google AI algorithms. It applies BERT’s capabilities to ranking. DeepRank is also trained on a large dataset to provide it with an understanding of common-sense language. 

MUM

MUM is a further advancement in the NLP technology application for matching queries with search results. Introduced in 2021, it’s considered “1,000 times more powerful than BERT” because of its multimodality, which enables multitasking and understanding of 75 languages and different content formats. 

Here’s an example of how MUM can understand a search intent and context of the query:

Source: Google

Naturally, it requires more resources than BERT and is therefore used only in selected cases, such as queries related to COVID-19. 

Google Search Algorithms Based on User Behavior

NavBoost

NavBoost is a core Google search algorithm designed to deliver higher-quality results by learning user behavior from click data, including click-through rates and hovering, and by incorporating data from human evaluators. Speaking of user behavior data, Google stores information about every query made within the last 13 months and matches it with the results of human-made quality tests to build its search algorithms.

Google uses click data to see which sites people actually find useful, then adjusts its results. NavBoost only keeps clicks from the last 13 months, so old popularity doesn’t last. A page that did well two years ago has to keep earning its clicks.

NavBoost divides its data into sets by factors such as desktop vs. mobile users and location. That essentially means Google may show different results to a query based on the user’s device and location. For example, when searching for pizza places, Google might provide results based on users’ click history for the same query in that area. Similarly, when typing the bank’s name, Google may show results for local branches or online banking, depending on whether the user is searching from a desktop or mobile device. It is an example of how SEO works today: past results fade unless you support them. 

Glue 

Glue is the extension of NavBoost that stores information about users’ behavior across image carousels, direct answers, maps, etc. That said, neither NavBoost nor Glue is involved in the initial selection of the websites from the query. 

Usually, sorting down to the tens of thousands of results happens without AI tools that require extra processing time. After the initial filtering, NavBoost and Glue (but not only them) narrow it down to a few hundred websites, rank them, and display them on a SERP.

→ Google handles each search in stages, with different tools at each one. The first stage scans millions of pages quickly, so it uses very little AI. Ranking the best matches takes more time and computing power, so that’s where the heavier AI comes in. That’s how Google works behind every search.

The framework that organizes the results on a page and is responsible for the interface is called Tangram (formerly Tetris). 

Google openly discusses and promotes top-notch AI technologies that help understand user intent and find the most relevant results, but it avoids mentioning the tools that examine users’ behavior on search pages, whether older systems like NavBoost or newer ones like Glue.

And here’s why: 

• First, keeping ranking algorithms secret reduces the chances of new or less popular websites appearing at the top of the list. 
• Second, these technologies give Google more opportunities to manipulate search results, even though I have no doubt it misuses that power.
• Finally, storing users’ click history will prompt the “big brother is watching you” kind of talk. Meanwhile, Google seeks to distance itself from platforms like Facebook, which generate content based on users’ personal information and browsing history.

Factors Used by Google Search Algorithms

To see how Google works when it ranks pages, look at the five factors it evaluates: 

1. Meaning: The most important factor in a result appearing at the top is its relevance to the user’s query. Google tries to interpret the prompt’s meaning, correct spelling errors, resolve ambiguities, activate a sophisticated synonyms system, and identify a variety of websites that contain related content.
2. Relevance: If a webpage has the same keywords as your query, that’s a strong relevance signal. But Google’s approach is more nuanced. It also analyzes whether the page’s content relates to the query in other ways. So, a search for “dogs” won’t just return pages that repeat the word, but ones with related content like dog images, videos, or descriptions of dog breeds.
3. Quality: Google prioritizes websites that show high expertise, authority, and trustworthiness. The evaluation involves checking if reputable websites link to the content, suggesting reliability. Another factor is the availability of user reviews on the site. They also collect user feedback during the search quality process to make their judgment more precise. 
4. Usability: When other factors are equal, Google compares website usability, which includes factors such as accessibility, mobile-friendliness, navigation, load speed, etc. 
5. Context: Is the most personal part of how Google works. In tailoring search results, Google considers context and settings, including your location and search history.

How Does Google Receive the Metrics?

We know the algorithms Google employs and the factors it evaluates to search, rank, and display results. The missing piece is the specific metrics Google uses to implement evaluation data and sources. And those metrics convey a lot about how SEO works. 

On-Page Content

I’ve already mentioned Google crawlers that visit sites to collect the information needed for indexing. They regularly scrutinize textual content, images, videos, and metadata to assess a website’s current state.

But not only that. Crawlers can also gather data on website quality: does your site include a navigation bar, is it easily accessible to everyone, and does it have broken links? Additionally, crawlers can identify whether your website includes links to other websites, possibly ones with a good reputation. Backlinks are still very important to how SEO works: NPDigital analyzed 25,000 search terms and found that, on average, the first result on Google search has 3.27x more backlinks than positions #2 through #10.

Quality Tests Conducted by Humans

A less-discussed aspect that still has a huge impact on how Google works is regular quality tests performed manually by human evaluators. Google states that these tests don’t directly impact actual website rankings, but “help us benchmark the quality of our results.” In my opinion, if they can influence how the results are displayed, they can also change rankings. 

Google has created a comprehensive guideline document for human raters, discussing how to properly evaluate search results proposed by Google. Part of the document focuses on understanding user intentions and defining the relevance of the results. However, the paper pays special attention to webpage quality. 

Testers are instructed to evaluate each website’s experience, expertise, authoritativeness, and trust using a Page Quality scoring system from 1 to 10. They are encouraged to find reputation information about websites and their creators, check ‘About Us’ and ‘Contact Us’ pages, compare content engagement with other websites, and more.

Although website authoritativeness plays a major role in website evaluation, pages with a perfect reputation shouldn’t rank higher than less reputable ones if their content is less relevant to the user’s query.

Source: Search Quality Evaluator Guidelines

Source: Search Quality Evaluator Guidelines

Human evaluators use multiple factors when deciding which results are better for user queries. Since they are instructed to prioritize pages with the highest quality scores, the Google search algorithm also learns to prioritize those results. Such a feedback loop is an essential part of how Google works. 

Click Signals

The next data source is crucial to how Google works, yet it has never been explained to the public.

We already know Google analyzes user behavior to provide a more personal experience, whether it’s showing results for local businesses or guessing the intentions of desktop users versus mobile ones. But how exactly does Google know what results are more relevant for a particular user group?

Now, when we combine the data from Google’s internal PDF presentations with Pandu Nayak’s testimonials (VP of Search at Google), we can have an “Of course!” moment and exclaim, “It’s the clicks!”

Source: U.S. Department of Justice, Trial Exhibit – UPX0228

Until recently, the only known user history Google used to enhance its functionality was search history, which allowed it to offer relevant autocomplete suggestions and slightly influence result rankings. However, with billions of click-and-hover records, Google has much greater capabilities than previously recognized. 

For example, it now analyzes user impression data to assess which results are more popular for specific queries and adjusts its algorithms accordingly. Likewise, tracking clicks can help Google estimate bounce rates by measuring how long users stay on a site.

And if you’ve ever wondered why SEO suggests adding essential pages to your site, such as About Us, here’s the answer: Google generally prefers fully developed websites. So, if all else is equal, it ranks sites with an About Us page higher. 

However, Google recognizes that it is essential to examine other factors besides clicks to understand user behavior. In a 2016 paper, they argue that the three factors for evaluating SERPs are clicks, user attention, and satisfaction (hence, the CAS model). The framework is now nearly a decade old, but the underlying idea has only become more relevant; modern SERPs are far more visually complex than in 2016, with AI overviews, vertical modules, and rich results all competing for attention alongside the classic blue links. 

“Google doesn’t reward clicks. It rewards satisfied searches. Systems like NavBoost learn from long-term interaction data, so they can tell a click that ended the search from one that sent the user straight back to the results. In a way, SEO now looks a lot like SMM for websites: engagement, repeat visits, branded searches, and audience loyalty all show Google that people actually want your content. It also raises an open question: why were competitors like OpenAI and Perplexity so eager to buy Chrome when the DOJ pushed for its sale? Maybe because whoever owns the browser sees how people really behave after the click. The takeaway is simple: stop optimizing for the click and start optimizing for the moment after it.”– Taras Slavych, SEO Team Lead at Phonexa 

Instead of relying solely on clicks, this holistic approach incorporates mouse movements to learn about user attention and accounts for situations where users don’t click on the search results even after viewing relevant items. 

Source: A.Chuklin, Maarten de Rijke – “Incorporating Clicks, Attention and Satisfaction into a Search Engine Result Page Evaluation Model”

The CAS model sheds light on how Google works when ranking search results and is particularly helpful for predicting user behavior on modern search pages with complex layouts and multiple content types. 

Google describes this process as a ‘dialogue’ in which it accumulates information about user behavior to generate result lists. In a sense, how Google works and how it conducts a search is a continuous communication between the search engine and its users: on one side, users receive relevant results, while on the other, Google reads how users respond through click tracking and other instruments. Consider that Google acquires billions of new pieces of data daily to adjust its matching techniques.

For example, one presentation describes how search results containing “DVM” (Doctor of Veterinary Medicine) were under-ranked for queries starting with “Dr” (Doctor). The click data volume suggested to Google’s search algorithms that “DVM” results are a subset of “Dr” results. 

Understanding How SEO Works

SEO means learning how Google works and improving your website so it ranks higher. Most of the work comes down to content, speed, and site structure.

Based on Google’s documentation and an overview of the results of previous adjustments, this is how SEO works:

• Keyword optimization: Adding relevant keywords to your content for search queries
• Content quality: Creating genuinely original and valuable content
• Mobile-friendliness: Everything should work easily on mobile devices
• Page speed: Making sure loading times are in the standard range for a better user experience
• Backlinks: Building reputable links from other websites to establish authority
• User experience: Creating an easy-to-use and easy-to-understand website layout and navigation
• Meta tags: Efficiently using title tags and meta descriptions
• Regular updates: Keeping content fresh and updated

Some Google search algorithm updates are easy to detect, such as changes to title tags or meta description length in SERPs. Others are not on the surface. By changing its rules, Google creates a dynamic, competitive process.

Reevaluating How SEO Works With the New Evidence From Google

Information about Google data structures and algorithms that has become public in the last month or two allows for a better understanding of what’s going on under the search engine’s hood. That doesn’t necessarily mean the rules should change, but it does mean the focus will shift from on-page SEO to off-page SEO.

Well-known SEO experts have said that the general understanding of how Google works was wrong and that the SEO model must change. 

Here’s how Google works now, based on the new evidence: 

• Google places much more emphasis on user behavior than previously thought. Past interactions with search results influence which results Google retrieves from the index and how its algorithm ranks them. For Google, user impressions are a main factor in assessing website quality. By learning which websites humans select for which queries, Google learns what’s actually on the website. 

Source: U.S. Department of Justice, Trial Exhibit – UPX0203

• Page quality tests conducted by human raters play a significant role in fine-tuning all of Google’s search algorithms. They help Google understand which website qualities matter for evaluating authoritativeness and then apply that knowledge to its algorithms. Human evaluation and user behavior history may now matter more than backlinks. 
• The “mobile first” rule is not just merely a figure of speech: the raters conduct quality tests only on mobile devices. For example, if you optimize your page meta description to look nice on a SERP (i.e., to be fully visible or include keywords in the visible part), judge it by how it looks on a small-screen device. 
• Google assesses technical data about websites not only by crawling websites but also by evaluating user behavior on the site. It considers factors such as website performance, accessibility, and the availability of essential elements that support a positive user experience, and ranks websites accordingly. 
• NavBoost is Google’s not-so-secret weapon, storing user behavior information for 13 months. That time frame should give webpage owners extra incentive to create new content or update existing content. 

What Changed in 2026

The last time we updated this article, at the start of 2024, the biggest SEO story was the NavBoost leak: Internal Google documents surfaced through U.S. antitrust proceedings. Then it became clear that user click behavior on the results page influences organic rankings far more than most SEO professionals had assumed.

Those click signals are still important, but they are not as important as they seemed back then. Something bigger has been happening alongside them, and it arguably matters more to the economics of search traffic today: 

• Google is answering more queries inside its own interface, and fewer of those queries end up on third-party websites.

AI Overviews now appear across almost all searches, which is, of course, more than they did a year ago: 

• AI Mode supports extended research sessions without requiring users to leave Google.
• Vertical modules covering hotels, flights, jobs, shopping, and local businesses have expanded into new categories.
• Direct-answer boxes cover much of what the vertical modules don’t.

Together, these formats have absorbed a large share of the clicks that used to flow out to publishers, aggregators, and comparison sites.

For any business that depends on organic search, the more important question in 2026 is not just how to rank higher, or even how SEO works, but whether that ranking still reaches your actual business.

Google Is Not Just the Referee

For years, the industry’s picture of how Google works was simple: a neutral algorithm rewarding good content. But it is not that simple.

Google runs organic rankings, sells paid placements above them, and operates its own vertical products (Hotels, Flights, Shopping, Local, Finance) that compete with those same results. It also builds AI experiences that summarize publisher content, and its own policies decide which intermediary businesses stay visible.

When one company is at once the referee, the stadium owner, the ticket seller, and (in some categories) a player on the field, its interests pull in different directions from everyone else’s.

“I wouldn’t say Google is biased. Rather, it has its own criteria for determining which results are the most useful. For us SEOs, there’s nothing new here; we’ve spent years trying to figure out exactly what it will favor next.” – Vlada Pianyk, an SEO specialist at Phonexa.

Case Studies: What Happens to Aggregators

Overall, Google doesn’t like aggregators and websites that borrow authority. For instance, Forbes rented out its domain authority to commercial sections that had nothing to do with what the magazine actually covered. It worked well for years, but not after Google changed its rules around site reputation. 

Source: Google

The same thing happened to many coupon sections. During 2022 and 2023, several major U.S. and UK newspapers set up coupon subdomains through white-label deals. Several lost much of their visibility once Google started treating those subdomains as separate reputational entities. 

The same goes for NerdWallet, Bankrate, and the other finance aggregators. These are strong brands with real editorial teams, and nobody is saying they can not go up again. 

However, even the best-run, search-dependent aggregators are now absorbing pressure from many directions: core updates, AI Overviews handling “best credit card” queries on the results page, more direct competition from banks and lenders running their own content, and Google Finance modules eating into the top of the SERP.

Across these niches, we can see that businesses whose main job was organizing information Google needed access to are taking the hits right now. Brands that are still holding up tend to have something else: proprietary data, real customer relationships, and real matching that Google can’t just replicate.

AI Search Makes Information Arbitrage Weaker

AI removes the economic value of being a middle layer that summarizes information available elsewhere. AI can do it even better, so users are no longer incentivized to stay on aggregators.

The top-listed articles are the most exposed here, just like generic product reviews built from publicly available spec sheets or category explainer articles written entirely from public sources.

“I believe AI has completely destroyed the value of generic content. Another article about the “10 Best X” can now appear faster than it takes someone to pour a cup of coffee. That’s why the content that wins is one that offers what a typical prompt lacks: experience, data, expertise, and genuine human thought.” – Vlada Pianyk, an SEO specialist at Phonexa.

AI mostly affects the content types that publishers and comparison sites rely on to drive traffic. The economics that made these pages worth building in the first place are eroding, even when the pages still rank well. As a result, there’s no need to build a business around these as the primary asset.

Your Brand Should Become the Arbitrage Layer

An SEO page is a fragile asset. It exists at the pleasure of an algorithm, and its value can disappear when rankings drop.

A vertical brand is a different kind of asset because it organizes demand, not the page that shows it for a limited time.

Look at the difference:

• The old model: Google → “Best Home Insurance” article → affiliate click → insurance provider.
• A new, stronger model: Google, ads, social, direct traffic → an insurance-focused brand that customers know → customer inquiry → qualification → matching → insurance provider.

What we call “the stronger version” is stronger because it doesn’t rely on a single traffic source. AI Overviews can handle the query, or a competitor can outrank the article, but the brand will still have the demand it created because it has already built recognition, a mailing list, a qualification process, and buyer relationships.

Your business has to own some genuinely valuable things: brand recognition inside your specific vertical, first-party customer data, documented consent, qualification and scoring logic, buyer relationships and pricing, a conversion history you can learn from, source performance data, distribution routing, and revenue attribution.

Own the Lead, Not Just the Click

A click doesn’t have the same value it used to, and that affects how SEO works for lead generation. A lead – a consented, qualified customer inquiry with actual information attached to it – is a real asset. And unlike a ranking on a search page, it’s an asset you have more control over, like managing user experiences when they land on a page, the form or the call flow that captures the inquiry, the qualification logic that sorts out which leads are worth what, the matching logic that picks the right buyer for each lead, and more.

Owning a lead, however, isn’t the same thing as owning a person’s data outright. A customer’s information belongs to that customer, and what you can do with it is limited by their consent and by whichever privacy law applies (TCPA, GDPR, various state consent regimes, and so on). What the marketer really owns is the relationship and the process: the permission to reach out, the qualification information the customer can share, and the infrastructure to make revenue.

SEO Becomes an Acquisition Channel, Not the Business Model

Google will keep changing how it ranks, displays, summarizes, and monetizes results, and AI overviews will expand. Ranking factors are likely to shift again, probably several times over the next few years. 

None of that is under your control. What you can control, however, is how much of your business depends on any of it.

SEO still matters, often a great deal, actually. It’s a strong acquisition channel with reasonable unit economics, and letting it atrophy is a mistake. But it’s one channel out of several, feeding into a brand, a lead management system, and a network of buyer relationships. 

If an algorithm update cuts your SEO in half, your business will survive. But the more you rely on SEO as your one and only marketing channel, the more likely the same update is to be fatal.

With all of that in mind, here’s how SEO works in 2026 at the level of basic principles:

1. Site performance and technical health. Google’s algorithm evaluates real-world user experience metrics, which is why slow and inaccessible pages, as well as pages with bad Core Web Vitals, progressively lose rankings.
2. User engagement signals. Click behavior and on-site engagement directly affect rankings. Pages that get clicked, dwelled on, and rarely bounce perform better than their organic competitors.
3. Mobile-first everything. Google’s rater guidelines are built around mobile, and a large share of quality tasks are evaluated on phones. If your snippet, page, or form only looks right on desktop, most of the traffic that matters sees the broken version. 
4. Brand trust. Reputation, authorship transparency, About and Contact pages, and independent brand mentions all factor into how Google weighs a website’s trustworthiness.
5. Intent-matched content. Google has gotten much better at reading the intent behind a query, so pages that answer the specific version of the question a user actually meant to ask outperform pages that target the keyword generically.
6. Holistic site quality. No single page-level improvement, no matter how big, can compensate for a weak site. Especially since Google evaluates sites as a whole.

These points explain how to make SEO work as a channel. However, you also need to learn what SEO shouldn’t do anymore: carry the whole business by itself.

This is how SEO works now: build a brand people in your niche actually know, then handle your leads yourself. Collect them, check which ones are worth something, and send each one to the right buyer.

Then Google becomes your acquisition channel, and your brand owns the business.

“Google isn’t a place you own traffic anymore. It’s a place you rent attention. Treat it as an acquisition channel, and make sure every visitor it sends ends up in a system you control, because rankings can vanish overnight but your leads and brand don’t. At the same time, run the rest of your marketing with search in mind. PR, social, email, partnerships, and paid campaigns all create brand searches, mentions, and returning visitors, and those are exactly the signals that support your future rankings.“ – Taras Slavych, SEO Team Lead at Phonexa.

How Phonexa Fits This Model

Everything up to this point has been a strategic argument about how SEO works as a channel. The operational side of it, which is the actual work of building a business that owns intent, requires infrastructure. Phonexa was built for exactly that.

LMS Sync is the core piece for managing leads, handling the entire lead journey, from initial capture through validation, qualification, scoring, and distribution. If your strategy is to own the lead-generation process, LMS Sync can be your system of record.

Ping Post and Ping Tree, both part of LMS Sync, are where the distribution happens: 

• Ping Post allows you to offer a lead to multiple buyers simultaneously, with the winning buyer only receiving the full lead information after agreeing to a price.
• Ping Tree adds waterfall logic on top of that, offering a lead to buyers in a defined sequence until one takes it.

LMS Sync captures and stores each consent record right alongside the lead itself, so what actually gets distributed downstream is a documented, permission-based customer inquiry. In lead generation verticals where TCPA and one-to-one consent rules apply, this documentation helps you avoid legal issues.

Call Logic handles the same logic on the call side: call tracking, qualification, distribution, and analytics. For verticals where high-intent leads convert best over the phone – insurance, home services, and most of the finance space all fall into this category – Call Logic is irreplaceable.

Here are the two core products you get at a single price:

Here are the six extra features you get as a client with Phonexa:

Get started now and learn how Phonexa can help you grow your ROI. 

Frequently Asked Questions

How Google works in 2026? 

In 2026, how Google works goes beyond blue links. AI overviews, AI modes, and vertical answers address many questions directly, but clicks and engagement still affect organic traffic. 

What are Google algorithms?

They are the core of how Google works: complex software systems that interpret the meaning of users’ queries, retrieve data about websites with relevant content from the Google search index, and display it on search pages. 

What factors does Google’s search algorithm use to evaluate websites?

Factors that affect a site’s ranking among organic competitors on Google search pages include query meaning and context, website content quality and relevance, and website usability. An effective SEO strategy accounts for these factors, ensuring a website aligns with Google’s algorithms.

How does Google search work with SEO?

Search engine optimization is a web development strategy that aims to improve website ranking in the search engines. Because Google is the most popular search engine, SEO focuses on aligning with Google’s ranking algorithms.

How many algorithms does Google use?

Google uses many algorithms for different aspects of search. The exact number isn’t known by the general public. These algorithms include RankBrain, BERT, NavBoost, Glue, Tangram, and MUM. 

How does local SEO work?

Understanding how local SEO works involves optimizing your website to appear in more relevant local searches. The process includes incorporating local keywords and ensuring your business is listed in local directories.