Google - how the search engine works


There is no human being, who don't know the brand, the word Google , but... have you ever tried to thinking about what is behind? How it works? Why is it so fast and relevant? How he would exactly know what you are looking for?


Overview of Google's Search Algorithm

 google search

Google's search algorithm is a complex system that is designed to crawl the web, index its content, and then serve the most relevant results to users' queries. The algorithm is constantly evolving, with updates being made on a regular basis to improve the accuracy and relevance of the results.


One of the key components of the algorithm is the use of over 200 ranking factors or signals, which are used to determine the relevance and authority of a website. These ranking factors are grouped into three main categories: content-related factors, backlink-related factors, and website-related factors.


Content-related factors include the keywords used in the content of a web page, the relevance of the content to the user's query, the quality of the content, and the overall user experience. Google's algorithm uses natural language processing and machine learning to understand the intent behind the user's query, and it uses this information to match the query with the most relevant pages in its index.


Backlink-related factors include the number and quality of backlinks that point to a web page. Backlinks are links from other websites that point to a specific page, and they are used to indicate the authority and trustworthiness of a website. Google's algorithm uses backlinks as a measure of the popularity and relevance of a website, and it uses this information to rank the pages in its index.


Website-related factors include the design and navigation of a website, the loading speed of the pages, and the overall user experience. Google's algorithm looks at the design and navigation of a website, as well as the loading speed of the pages, to determine the overall user experience, and it uses this information to rank the pages in its index.


Google's algorithm also uses a variety of other techniques to determine the relevance and authority of a website. These include:


  • • Latent Semantic Indexing (LSI) - LSI is a technique that is used to understand the relationship between words and concepts. Google's algorithm uses LSI to understand the context of a web page and to match it with the user's query.


  • • Latent Dirichlet Allocation (LDA) - LDA is a machine learning technique that is used to identify topics in a text. Google's algorithm uses LDA to understand the main topics of a web page and to match it with the user's query.


  • • Neural Matching - Neural Matching is a machine learning technique that is used to match a user's query with the most relevant pages in the index. It uses neural networks to understand the intent behind the user's query and to match it with the most relevant pages.


  • • RankBrain - RankBrain is a machine learning algorithm that is used to understand the intent behind a user's query. It uses natural language processing and machine learning to understand the intent behind the query and to match it with the most relevant pages in the index.


In addition to these techniques, Google's algorithm also uses a variety of other signals to determine the relevance and authority of a website. These include the location of the user, the device used to conduct the search, and the time of the search.


Crawling and indexing

Crawling and indexing are the first steps in the process of delivering search results through Google's algorithm. Crawling is the process of discovering new and updated pages on the web and indexing is the process of adding those pages to Google's database of web pages, which is called the "index."


Google's crawlers, also known as "spiders" or "robots", are responsible for scanning the web and finding new and updated pages. The crawlers follow links from one page to another, and they index the content of each page they find. The links can be found in the website's menu, in the website's sitemap, or through other websites linking to it.


  • How you, as the site owner can communicate with these spiders, or robots?

    • Website owners can take several steps to help Google's robots discover what their website is about and improve its visibility in the search results.


      One of the most important steps is to create a sitemap. A sitemap is a file that lists all of the pages on a website, and it helps Google's robots to find and index all of the pages on the website. Sitemaps can be created using a variety of tools, including Google Search Console.


      Another important step is to create and submit a robots.txt file. This file is used to indicate to Google's robots which pages on a website should be indexed and which pages should be excluded from the index. This can help to prevent the indexing of duplicate or irrelevant pages, and it can also help to prevent the indexing of pages that contain sensitive information.


      Website owners should also make sure that their website is mobile-friendly and optimized for different devices. Google's algorithm prioritizes mobile-friendly websites in the search results, so it's important to make sure


      that the website is easily accessible and readable on mobile devices.

      Website owners should also make sure that their website has a clear and intuitive navigation structure. This can help Google's robots to find and index all of the pages on the website, and it can also help users to find the information they are looking for.


      Additionally, website owners should use structured data to provide additional information about the content of their website. Structured data, also known as schema markup, is a way to provide information


The crawlers use a technique called "breadth-first crawling" which means that they start with a few well-known pages and follow all the links on those pages to discover new pages. The crawlers continue this process, following all the links they find, until they have indexed a significant portion of the web. The crawlers repeat this process on a regular basis to find new and updated pages.


Once a page has been indexed, it is added to Google's database of web pages, which is called the "index". The index is a massive database that stores information about billions of web pages, and it is used to quickly retrieve the most relevant pages when a user conducts a search. The index is updated constantly, with new pages being added and old pages being removed as they are discovered and indexed.


When a user conducts a search on Google, the algorithm uses the index to quickly retrieve the most relevant pages. The algorithm uses a variety of techniques, such as natural language processing and machine learning, to understand the intent behind the user's query, and it uses this information to match the query with the most relevant pages in the index.


Google also uses a technique called "dynamic crawling" which allows the crawlers to adapt to the changes in the web in real-time. This means that the crawlers can discover new pages and update the index immediately, providing the most updated results to the users.


It's worth mentioning that, Google has a limit on the number of pages it can crawl and index from a single website, this limit is called "crawl budget" and it's determined by the website's structure, the number of pages and the amount of changes happening on the website. Websites with large number of pages, or frequently updated content may have a higher crawl budget than other websites.


Ranking Factors

Ranking factors are a crucial component of Google's search algorithm, as they are used to determine the relevance and authority of a website. These factors are used to rank the pages in the index and decide which pages will be shown to the users in the search results.


Some of the most important ranking factors include:


  • • Keywords: The keywords that are used in the content of a web page are one of the most important ranking factors. Google's algorithm looks for the keywords that are used in the content and in the meta tags, such as title tags and header tags, and it uses this information to determine the relevance of a page. However, it's not just about the number of times a keyword is used on a page, the algorithm also takes into account the keyword's relevance to the topic of the page and its proximity to other relevant keywords.


  • • Content Quality: The overall quality of the content on a web page is also an important ranking factor. Google's algorithm looks for pages that have high-quality, informative content that is relevant to the user's query. The algorithm also looks at the readability and the engagement level of the content, as well as the time spent on the page by users.


  • • Backlinks: The number and quality of backlinks that point to a web page are also an important ranking factor. Backlinks are links from other websites that point to a specific page, and they are used to indicate the authority and trustworthiness of a website. Google's algorithm uses backlinks as a measure of the popularity and relevance of a website, and it uses this information to rank the pages in its index. However, it's not only the number of backlinks that matters, the algorithm also takes into account the quality of the backlinks, as backlinks from reputable and high-authority websites carry more weight than backlinks from low-quality or spammy websites.


  • • Domain Authority: The overall authority and trustworthiness of a domain is also a ranking factor. Google's algorithm uses a combination of factors such as the age of the domain, the number of backlinks pointing to the domain, and the overall quality of the content on the domain to determine its authority.


  • • User Experience: The user experience is also an important ranking factor, and Google's algorithm looks at the design and navigation of a website, as well as the loading speed of the pages. A website with a good user experience will be favored in the search results. This includes factors such as mobile-friendliness, page speed, and the overall usability of the website.


  • • Social Signals: Social signals, such as shares, likes, and mentions on social media platforms, also play a role in the search ranking. Google's algorithm takes into account the social signals as a measure of the popularity of a website and the relevance of its content.


  • • Structured Data: Structured data, also known as schema markup, is a way to provide information about a website's content to the search engines. Google's algorithm uses structured data to understand the content of a web page and to display it in a more user-friendly format in the search results, such as rich snippets, this can also improve the visibility of the website in the search results.


It's worth noting that these ranking factors are not equally weighted, and the relative importance of each factor may change over time. Google's algorithm is constantly evolving, and the relative importance of each factor may change as the algorithm is updated.


In a nutshell, ranking factors are a crucial component of Google's search algorithm, as they are used to determine the relevance and authority of a website. These factors include keywords, content quality, backlinks, domain authority, user experience, social signals and structured data.


Content Quality

We mentioned above the "Content Quality". But, Google algo is just a robot, so how it being decided, if the content is high quality, or not?


Google's algorithm uses a variety of techniques to estimate the quality of a website's content. These include natural language processing, machine learning, and manual evaluations by human quality raters.


One of the main ways that Google estimates the quality of a website's content is by analyzing the content itself. The algorithm uses natural language processing to understand the meaning and intent behind the content, and it uses this information to determine the relevance and authority of a website.


The algorithm also looks at the overall structure and organization of the content. It checks if the content is well-written, easy to read, and if it is formatted in a way that makes it easy for the user to consume. The algorithm also checks for the presence of headings, subheadings, and lists, which help to break up the content and make it more readable.


Another way that Google estimates the quality of a website's content is by analyzing the engagement level of the users. The algorithm looks at the time spent on the page, the bounce rate, and the number of pages viewed by the users. High engagement levels indicate that the content is interesting and relevant to the users, which in turn implies that the content is of high quality.


Google also uses manual evaluations by human quality raters to assess the quality of a website's content. These raters are trained to evaluate the content based on a set of guidelines that reflect the overall quality and relevance of a website's content. They look at factors such as the relevance of the content to the user's query, the quality of the writing, the credibility of the information, and the overall user experience.


These evaluations are used to train Google's algorithm and improve its ability to understand and assess the quality of a website's content. The evaluations are also used to identify patterns and trends in the way that users interact with the content, which helps the algorithm to better understand the relevance and authority of a website.


Additionally, Google also uses the data collected from user's interactions with the website, such as click-through rate and dwell time, to understand how users are engaging with the content, this data can be used to assess the quality of the content.


Wrapping it up, Google's algorithm uses a variety of techniques to estimate the quality of a website's content, including natural language processing, machine learning, and manual evaluations by human quality raters. These techniques are used to determine the relevance and authority of a website, and they help to ensure that the search results are accurate and relevant to the user's query. Website owners should focus on creating high-quality, informative content that is relevant to the user's query, and that is easy to read and well-organized. Furthermore, website owners should make sure their website is user-friendly and engaging, this can help to improve the quality of the content and increase its visibility in the search results.


Learn more about the Natural Language processing mentioned above in our other blog post


Algorithm Updates

Algorithm updates are a regular occurrence in the world of search engine optimization, and they are a critical component of Google's search algorithm. These updates are made to improve the accuracy and relevance of the search results, and they can have a significant impact on the visibility and ranking of a website.


Google makes several updates to its algorithm each year, and these updates can be grouped into two main categories: core updates and minor updates. Core updates are major updates that are designed to make significant changes to the algorithm, and they are typically announced by Google. Minor updates, on the other hand, are smaller updates that are designed to make more subtle changes to the algorithm, and they are not typically announced by Google.


One of the most notable and impactful updates is the Google Panda algorithm, which was first launched in 2011, this update was designed to target low-quality, thin, or duplicate content. The update aimed to improve the quality of the search results by penalizing websites that had low-quality content, or that were scraping content from other websites. This update had a significant impact on many websites and led to a significant drop in their visibility and ranking.


Another significant update is Google Penguin, which was first launched in 2012, this update was designed to target websites that were using manipulative link building techniques, such as buying links or participating in link farms. The update aimed to improve the quality of the search results by penalizing websites that were using these techniques to artificially boost their visibility and ranking.


Google also made updates to the algorithm to make sure that the search results are mobile-friendly, this update is known as "Mobilegeddon" which was launched in 2015, this update aimed to improve the mobile search results by prioritizing websites that are mobile-friendly, and penalizing websites that are not optimized for mobile devices.


Google also made updates to the algorithm to take into account the user's intent and context when conducting a search, this update is known as "BERT" which was launched in 2019, this update aimed to improve the understanding of the user's intent and context when conducting a search. The update used natural language processing techniques to better understand the meaning behind the user's query and match it with the most relevant search results. This update also helped to improve the accuracy of the search results by providing more relevant results for long-tail keywords, and it was expected to have an impact on around 10% of the search queries.


Google also made updates to the algorithm to better understand the user's location and language, this update is known as "Google E-A-T" which was launched in 2020, this update aimed to improve the relevance and accuracy of the search results by taking into account the user's location and language. The update also helped to improve the search results by prioritizing websites that have expertise, authoritativeness, and trustworthiness on the topic of the user's query.


How Google Uses Cookies to Show better suitable Results

Cookies are small text files that are stored on a user's device by a website, and they are used to remember a user's preferences and activity. Google uses cookies to track a user's browsing history and search queries, which allows the search algorithm to deliver more personalized and relevant results.


When a user conducts a search on Google, the algorithm uses the information stored in the cookies to understand the user's search intent and preferences. For example, if a user frequently searches for information about a particular topic, the algorithm will take this into account and show more results related to that topic.


Google also uses cookies to track the websites that a user visits and the pages they view, which allows the algorithm to understand the user's interests and preferences. This information is used to personalize the search results and show the user the most relevant content.


Cookies also allow Google to remember a user's search settings, such as their location and language preferences. This means that when a user conducts a search, the results will be tailored to their specific location and language, making the search experience more relevant and convenient.


Moreover, Google uses the data collected from cookies to show targeted ads to users, this is done by Google Adsense program, which allows website owners to place ads on their site, and the ads are targeted to the user's interests and preferences, as determined by the information stored in their cookies.


It's worth mentioning that cookies are not the only way Google uses to track user's data, it also uses other technologies like browser fingerprints, IP addresses, and more.


Howcome, that the whole search is so incredibly fast and accurate?

Google's search and serving of search results is incredibly fast and efficient, thanks to its advanced architecture and technology.


One of the key factors that enables Google to serve search results so quickly is its distributed computing system. Google's search index is stored on thousands of servers that are distributed across multiple data centers around the world. When a user conducts a search, the query is sent to the closest data center, where it is processed by a cluster of servers. These servers use advanced algorithms to quickly find the most relevant pages in the index and return the search results to the user.


Google also uses a technique called "sharding" to further improve the speed and efficiency of its search results. Sharding is the process of breaking the index into smaller pieces, called "shards," and distributing them across multiple servers. This allows Google to process search queries in parallel, which helps to improve the speed and efficiency of the search results.


Another key factor that enables Google to serve search results so quickly is its use of caching. Caching is the process of storing frequently-accessed data in memory, so that it can be quickly retrieved when needed. Google uses caching extensively throughout its system, from the data centers to the edge locations, to help speed up the search results.


Google also uses a technique called "pre-fetching" to improve the speed of search results. Pre-fetching is the process of predicting the user's next search query and proactively fetching the results from the index. This helps to reduce the time it takes to display the search results, as the results are already available in the cache.


Additionally, Google uses machine learning and artificial intelligence to improve the speed and accuracy of its search results. The algorithm uses machine learning to understand the intent behind the user's query and match it with the most relevant pages in the index. It also uses artificial intelligence to understand the context of the user's query, which helps to improve the accuracy of the search results.


Conclusion

Google's search algorithm is a complex and ever-evolving system that uses a variety of techniques to determine the relevance and authority of a website. The algorithm includes several components such as crawling and indexing, ranking factors, algorithm updates, and user experience. Website owners can help Google robots to discover what their website is about by creating a sitemap, submitting a robots.txt file, making sure the website is mobile-friendly, having a clear and intuitive navigation structure and using structured data. Furthermore, Google's search and serving of search results is incredibly fast and efficient, thanks to its advanced architecture and technology, such as its distributed computing system, sharding, caching, pre-fetching, machine learning, and artificial intelligence. These technologies, coupled with a massive amount of data centers, make Google one of the fastest and reliable search engines available. The goal of all these components and techniques is to provide the most accurate and relevant results to the user's query, which is crucial for the user's experience. By understanding how Google's search algorithm works, website owners can optimize their website and improve its visibility in the search results.


Admin

Read next: