What is Google Algorithms

Google algorithomes.png

All search engines use highly-efficient algorithms to retrieve the most relevant and accurate results from their search index for specific queries. The development and evaluation of algorithms are crucial to all aspects of computer science, including artificial intelligence, databases, networking, graphics, security, operating systems, and more. This article aims at educating our readers about the definition and types of Google algorithms, how they affect search results, why Google needs algorithms, and the need to upgrade and introduce new algorithms. So, let us begin.


An algorithm is a set of well-defined procedures or instructions designed to perform a specific function or solve a computational problem. The task could be as easy as adding two numbers or a more complex operation such as playing a compressed video file.

In software programming or application development, algorithms are generally created as functions. These functions serve as small applications, arrangements, or lay-outs that a larger program can reference. For instance, an image viewing application may include a collection of functions that each uses a customized algorithm to render different image file formats. An image editing software may contain algorithms designed to process image data. Some examples of image processing algorithms include cropping, resizing, blurring, sharpening, red-eye reduction, and color enhancement.


With a vast amount of data available on the web, finding the right information without some help can be a tiring job. Google ranking systems help sort through hundreds of billions of webpages in our Search index to retrieve the most relevant, useful results in a fraction of a second and present them in a way that helps us find what we are looking for.

These ranking systems consist of not one but a whole series of algorithms. Google algorithms look at many factors, including your query’s words, relevance and usability of pages, the competence of sources, and your location and settings. The weight assigned to each factor varies depending on your query’s nature. For example, the content’s freshness plays a more significant role in answering questions about current news topics than it does about dictionary definitions. Similarly, Google algorithms track IP addresses to determine a user’s geographic location. As a result, the search results for the same keyword might vary for individuals searching from different locations. Also, Google algorithms can personalize search results based on your internet history.


Broadly, Google uses two kinds of algorithms, PageRank (PR) and Google algorithm for SEO. In this section, we will briefly take a look at the above and also highlight the major algorithm updates in the last decade.


PageRank is an algorithm employed by Google Search to rank web pages in their search engine results. PageRank is a way of gauging the importance of website pages. It works by counting the number and the quality of links to a page to determine a rough assessment of how important a website is. 

Page Rank was shutdown publicly by Google on March 7, 2016.


Google algorithms partially use keywords to establish page rankings. The most appropriate way to rank for specific keywords is by optimizing webpages for SEO. Essentially, SEO is a way to tell Google that a website or web page is about a particular topic.

6 Major Google Algorithm Updates in the Last Decade

      ●    Panda

      ●    Penguin

      ●    Hummingbird

      ●    Pigeon

      ●    Fred

      ●    Bert


Google is the best search engine on the web, and it has achieved this distinction because of its commitment to deliver the best results for each search.

Google requires large amounts of data to be able to make better decisions for any rank tracker. The more pertinent results people get when they search for a specific keyword, the more accurate will be the data that Google can extract and return for other searchers.

The job of Google algorithms is to reward the sites in the SERPs that deliver what users want. Google also prides itself on being the good guy of the Internet, and their search algorithm confirms this. The company’s old corporate motto of “Don’t be evil” is a stark warning for sites who try to tweak their system.


Over the last decade, we have seen several updates in google algorithms. So, the obvious question that now arises is why does Google keeps updating its algorithms? The answer to this will be evident once we understand the following core benefits offered by these changes.


Google aims to help each search user find the most relevant information they’re looking for as quickly as possible. Google also understands the need to meet the requirements of those searching on-the-move. Searchers no longer need to explicitly state keywords if they’re looking for something locally. For example, “Near me” is good enough for Google, provided you’ve granted access to your location.


Google prefers providing in-depth pieces of content that are likely to remain useful, provide meaningful, relevant, and long-term solutions with lasting SEO power.


Although not so obvious; however, Google algorithm changes do support a shift towards brand building.

Before Google started penalizing sites that used many internal links containing keyword-rich anchor text, over-optimization was the name of the game. However, SEO has since evolved, and building links, even though necessary, should not be a major focus anymore.

Corporate organizations, bloggers, and small business owners have become extremely methodical and meticulous when employing anchor text. The focus is on building links to improve a brand’s name and its relevance online rather than artificially boost its organic rankings.


The world around us is rapidly changing. Therefore, there is a constant need to update oneself to keep up with the pace. The same holds in the case of search engines also. In the case of a search engine, the problem is to find the most relevant content for a particular set of keywords or search terms.

Therefore, there is a frequent need to analyze existing algorithms concerning the amount of time, storage, or other resources needed to execute them and introduce new algorithms to deliver relevant and accurate search results to users.

We hope you enjoyed reading this article as much as we loved writing it for you.


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