How Search Engine Algorithms Work: Everything You Need to Know

How Search Engine Algorithms Work: Everything You Need to Know

What Is the Search Algorithm?

There are almost 2 billion websites on the Internet, and this number is constantly growing. New domains are registered every day. When there is a lot of information, an effective search is important. Its effectiveness is determined by how quickly everyone gets the answers to their question. How do you determine which of the possible websites gives the most accurate information? Sometimes the purpose of the search becomes research. In this case, the first ten to twenty links displayed in the results are important. Consider the relevance, especially when it comes to news. Therefore, search results from different people are rarely similar to each other, even when they are looking for the same thing. The results page, also called SERP, displays carefully selected sources of information that are most appropriate for each case. To determine in what order to present a set of similar links, take at least a dozen factors into account. This includes the authority of each site, the subject of the search, niche, or industry, the relevance of each page, and the reliability and safety of the information source.

The process of determining in which order the links appear on a search results page is called ranking. This is a fairly broad concept. For example, there will be one set of ranking factors for organic results. Advertisements or paid search results can also compete with each other. If several ad options can be displayed for one request, they also go through the ranking to determine the most suitable one. The ranking can also concern indirect recommendations, such as a list of similar searches or recommended applications. Ranking success or effectiveness is fairly easy to determine. The closer a position is to the top of the list, the better. It is important to remember that the formula for success in each case will be unique.

Special codes of rules are responsible for ranking. This includes search engines algorithms, designed to manage the process as efficiently as possible. In this article, we’ll look at what an algorithm is and what to consider for your links to rank successfully. The algorithm must accomplish two tasks. It should understand what the user wants to find and produce suitable results as quickly as possible. For example, each of us at least once tried to find a book, movie, or song based on a small passage or phrase that they remembered. It was not possible even to remember the words, only the melody. Such searches are so popular that Google even launched a special feature in the mobile version of search – Hum to search. All this happens thanks to well-thought-out and rather complex algorithms such as what, how, and where the search service will look for depends on them. Even if we have not yet fully decided what we want to find. This is the main difference between how algorithms work and formulas. A formula displays a mathematical ratio or rule. This is not always simple, but always definite. The formula needs to know for sure what to do and in what sequence. The algorithm itself can choose the appropriate set of criteria or rules to be applied in a particular case. For example, the formula calculates the approximate time of arrival at the place after calling a taxi through a mobile application. To define algorithms in this situation, we can say that it is they who analyze the traffic situation to suggest a route. An efficient route is not necessarily the shortest.

Much the same thing happens when we enter a search into the search bar. Search algorithms sometimes get to work even before we fill the input line. Some are responsible for recognizing the request, and others for finding possible answer options. Everything in order. You need to analyze the search itself and understand what the search results should be talking about. This allows you to find really useful results and determines how the search is carried out in general. If you need to find out the score in a match, the snippet will instantly answer this question. The nearest links will most likely contain detailed comments on the game. The relevance of the information will be high because this information will not be valuable to you tomorrow. When it comes to writing a paper about the theory of football, the news will be a little less useful and the search will display the rule books and other research on your topic.

To better understand searches, modern search services attach great importance to the semantics of natural languages. The widespread application of advances in this area of ​​science allows you to better understand the meaning of words. To decipher the semantic constructions that may be implied in each case. In order to effectively understand what we ourselves cannot fully formulate, it is necessary to take into account literally everything. These can be possible typos, common misconceptions, and words that are often confused, as well as regional specificity, dialects, polysemy, phraseological units, and so on.

When the request is processed and the algorithm knows what the user is looking for, the work has just begun. Now is the turn of searching for suitable matches in the base of indexed links. When we enter “money,” the search results will likely also include matches for the words “finance” or “wealth.” This is because search engines are not limited to one word or meaning. They also need to process synonyms, compare all the options with each other, choose the most suitable ones, and then compare the final list with the request itself. The set of factors influencing the position of the same link in the ranking will constantly change. For example, depending on the user’s search history, geolocation, region, and language.

Since the Internet is a very dynamic information environment, search algorithms for indexing and ranking sites need to be constantly updated. If an algorithm is a set of rules or actions, how can it be updated and improved? You need to create a high-quality system for evaluating the effectiveness of the results of the algorithm. You can understand whether the search has improved and to what extent. The second component will be a learning platform. Google still relies on human help. In order to assess the relevance, the results of the algorithms are tested by qualified specialists. The detailed Google manual describes the basics and methods for a proper understanding of algorithms. The main advantage of this method is that only humans are able to accurately match the concept or idea of ​​a search to what links were suggested on the results page. To make the process faster and more efficient, Google sees machine learning and artificial intelligence as its top priorities for all products, including search.

This is useful because you can automate everything that concerns more objective indicators in addition to the subjective criteria that require a person to assess. The number of links, the speed of search processing, and the selection of indexing parameters are examples. This is where machine learning comes into play. Updating searching algorithms required human assistance in a number of stages. A hypothesis was formulated about what and how can be improved. On the basis of the hypothesis, criteria for evaluating the results “before” and “after” were developed. Further, there was formed a pool of updates and training materials for the rules and logic of the algorithm. The results of the new version were compared with the original and the presence of qualitative changes was assessed. Only then was made a decision whether the update was effective.

Updating the algorithm is also an algorithm of its own kind. This is why machine learning has become an effective component of Google’s core learning engine. Instead of engaging people at each of the described stages, a set of rules was developed aimed at a single goal: to train search algorithms, evaluate results, and make decisions as independently as possible.

Basic Principles of Search Algorithms

Google identifies several main stages of a search service when generating a results page:

  1. Analysis of words and expressions
  2. Selection of suitable pages
  3. Ranking of relevant materials
  4. Selection and display of the most relevant results
  5. Accounting for user information

As you can see, the first task is to formulate the criteria for evaluating the effectiveness of the results. For this, it is necessary to understand what the user wrote and meant. One of the many components that are taken into account when solving this problem is accounting for common mistakes and typos. For more details on how Google deals with this, Mark Paskin spoke in this video:

The search engine algorithm tries to determine the nature of the information by analyzing the user’s search intent. The different classifications define four to six main search intents. The essence of this approach is that when searching for information, people are usually at one of the standard stages. They show general unfounded interest. They are looking for more accurate information about an existing problem, they are studying options for a possible solution, or they want more accurate information about only one of the options. Help is provided by special words that often define the nature of the request: buy, review, delivery, reviews, guidance, and so on. It is also important to consider the relevance of the request to better select the type of materials. For example, priority should be given to news and the latest developments or news articles of a general nature.

Famous Google Algorithms and How They Work

Google is constantly working to develop and improve search results. To see how Google search engine algorithm works, it’s worth noting that there is more than one algorithm. There are quite a few of them and each is responsible for individual variables, ratings, assessment, or training. Talking about how often changes are made, John Mueller noted that at this stage this happens almost constantly. Frequent but significant updates are also called Google core updates. Updates like this are rarely accompanied by official comments; in many ways, tracking the consequences falls on the shoulders of the SEO community and enthusiasts. The principle behind the analysis is fairly simple – comparing key website metrics before and after the estimated release date. The main difficulty lies in interpretation since, without clues to what exactly to look for, it can take weeks to find significant factors. Read related articles – UPDATE: Google May 4, 2020, Core Web Vitals: Google’s New Ranking Factor.

Google’s algorithms have gone through several major updates. The most significant of them got their own names: Penguin, Panda, Hummingbird, etc. Major updates are often centered around a specific topic or problem they are intended to address. Therefore, many SEO specialists often divide search results by the period before and after the name update.

Panda (2011)

The main focus was on fighting plagiarism, duplicate content, spam, and keyword abuse. Pages were ranked on a content quality scale, and the scores were used as a significant ranking factor. Five years later, Panda became part of Google’s root algorithm, significantly accelerating the implementation of minor updates and the speed of processing page content.

Penguin(2012)

Aiming at combating link farms, private blog networks, and irrelevant and spammy links, Penguin also addressed the issue of over-optimized anchor texts. The actions of the algorithm primarily affected those sites whose link profile did not pass the test and was marked as unnatural. This was due to the massive purchase of cheap low-quality backlinks. According to the latest guidelines, a healthy backlink profile should be balanced and contain as many different sources as possible, while avoiding suspicious or dangerous ones.

Hummingbird (2013)

This was another major update to tackle keyword abuse and low-quality content. There was a transition from processing individual keywords to determining the user’s search intentions. Instead of guessing the keywords that would get the best results, focus on the information itself, and how it would be applied. When processing and ranking links, the importance of synonyms, similar topics, and semantically similar searches have increased significantly.

For more information read the article – Google Panda, Penguin, and Hummingbird: Algorithms That Affect SEO.

Mobile Results (2015, 2018)

This update was never given a name, although it changed the use of search in many ways. The main focus was on pages without corresponding mobile versions and site performance on mobile devices in general. There was an important prioritization shift in rankings towards pages that were well adapted for viewing and working on mobile devices. Optimization included many aspects: from the size and types of content, to how well the content is served on the page, whether loading by external files is not blocked, and so on. Even now, the performance of mobile versions of pages remains a rather serious issue for many sites.

RankBrain (2015)

Continuing the fight against irrelevant and low-quality content, Google has also put a lot of emphasis on user experience with this update. RankBrain is a grading system built on the principle of machine learning and analysis. The update is considered to be a Hummingbird add-on, designed to improve the quality of the interpretation of user requests and their subsequent comparison with indexed pages. Evaluation by the RankBrain algorithm is one of the key factors underlying effective ranking in the formation of search results.

Read the related article – RankBrain Google: The Definitive Guide.

Medic (2018)

This update primarily affects healthcare websites. The target audience of the new algorithm is much wider and includes any online resources containing information that can affect significant aspects of users’ lives. For example, finance, law, education, and so on. The main signals that the Medic took into account to form the assessment: Your Money or Your Life (YMYL) and Expertise-Authority-Trust (E-A-T). Engaging experts from each industry and attribution has become a part of page content evaluation since the launch of this algorithm.

BERT (2018)

The combined efforts of Panda, Hummingbird, and RankBrain are the foundation for the next step in fighting low-quality content. An algorithm created by Google applies for the latest advances in natural language processing to evaluate text content and style. The search engine is better at identifying suitable keywords for generating organic results. Lack of context, clear subject matter, and style have become important signals when ranking pages.

More information in this article – Google BERT Update.

Algorithms and Ranking

The algorithm evaluates the page content according to criteria such as relevance, quality, and style. It is impossible to determine the share and importance of each factor in evaluating each page. Here are some important guidelines and practices that you should pay attention to.

Three main parameters affect a page’s ranking performance. Quality is the sum of technical performance and content relevance. Value helps to establish how willing site visitors are to discuss and share content. Authority indicates how relevant the content is within an industry or niche. Let’s take a closer look at these parameters.

When assessing the quality of a page, pay attention to several technical points. Some simpler ones include the title, the meta description of the page, and how its content is structured. Sophisticated checks include the presence of external and internal links, the use of secure communication protocols, and the absence of redirect chains. According to the latest Google guidelines, the success of a page will depend on how useful and friendly it is to the end-user. The technical implementation is closely related to the user experience. Time to the first byte, image optimization, correct use of external scripts, and style sheets allow us to judge how long the page will load on a particular device. Content quality also plays a huge role.

How the content is structured, the text is laid out, and even where the images are located will largely determine whether your post is useful. Long load times can directly affect bounce rate growth, and well-executed mobile optimization will increase the time spent on your site. Therefore, for successful and effective ranking, create sites for people, not robots. After all, in the end, it is the real users who will become your audience and bring success to the project.

When it comes to the value of a link or content to a user, you never know which works best. A good example of a useful objective metric for search algorithms is a personal search history. This data can tell search algorithms on how to find matches for the searches received and add context when the search is too general or there are many matches. The value of the material is influenced by how often it is shared and quoted. The quantity and quality of backlinks help highlight the most relevant results. Backlinks do not always directly affect the position of your page in the search, but the more content is shared on social networks, forums, and quoted on specialized resources, the more chances it will rise even higher.

The authority or weight of a link reflects how useful it is not only for ordinary users and professionals. When assessing this factor, they take into account how often the content of the page has been referenced by profile resources and how important its value is within the industry or market segment. Also, great importance is attached to the rating and authority of the domains which placed links, topics, and indicators of their citation among the potential target audience of your page.

Algorithms and Content Types

It has always been easier to process text information than media files. With the development of recognition, data analysis, neural networks, and artificial intelligence, new opportunities are opening up. These opportunities relate to the work of search services. The processing of natural languages ​​has advanced due to the growth of computing power and the power of the equipment that performs calculations. The development of machine vision makes it possible to train neural networks to recognize and describe not only images in general but also their parts, the relationship between them, and the context of what is happening. Neural networks are ever better at processing abstract concepts, learning to analyze incomplete and fragmentary data, and imitate as much as possible the cognitive functions of the human brain.

At this stage of technological development, the border between text and visual information processing is gradually blurring. The main tools for analyzing multimedia content remain additive metadata such as ID3 tags, the use of schema, and custom HTML tags. When posting images, use optimized files and formats and take the time to describe them. Some popular data visualization formats, such as infographics, have taken a different path. Modern platforms allow you to create SEO-friendly content that won’t face typical image indexing issues. This is most often achieved through the use of cascading styles and the latest hypertext markup capabilities to combine readable text with the desired graphic forms.

Even textual data has a number of disadvantages that one can run into when building websites. This concerns the dynamic content generated by JavaScript scripts. Only a few search engines have the ability to work correctly with script instructions to date, and Google provides full JavaScript support. Using dynamically generated content can lead to delays in indexing. Abuse or misuse of scripts can lead to warnings and penalties. Whatever type of content you post, try to always pay due attention to existing guidelines and best practices.

Why It Is Important to Understand How Algorithms Work

You don’t have to be a good mechanic to become a driver. No driving school can do without explaining the basic principles of a car, engine, clutch, and gearbox. You do not need to understand the intricacies of how search engines work to create sites. Understanding the basics of search engine optimization will help your projects achieve success. Google has repeatedly pointed out that sites and content should be built for people first. However, many webmasters still see the manipulation of search algorithms as the main key to success.

Practically speaking, in-depth knowledge of web development, search engine optimization principles and knowing how algorithms work helps to identify problems and find effective solutions. If you create a quality product from both a technical and a content point of view, you know your target audience well and understand your subject matter, there should be no problems. There is always room for improvement. Even the most sophisticated content strategy will benefit from additional SEO analysis.

Whatever sites you create, try to prioritize the value of the content you publish to your users. This approach will help to avoid the most common mistakes.

Author

George Caravanschii George Caravanschii

George is a freelance digital analyst with a business background and over 10 years of experience in different fields: from SMM to SEO and development. He is the founder of Quirk and a member of the Inspiir team, where he is working closely with stakeholders from many popular brands, helping businesses grow and nurturing meaningful projects. George writes regularly on topics including the technical side of SEO, ranking factors, and domain authority.

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