Many informative sources are available on the internet. A single click can find you the most accurate and relevant results to your query, be it any subject. Google Search Engine is the dominating search engine in the market since 1997. Although the search results show up almost instantly, there is a bit more complexity to the process than it seems.
According to NetMarketShare, Google continues to dominate search engine use with 70.38% on desktop in 2020.
Earlier, Google used to make only a few updates but now, Google makes thousands of updates in a year. Major updates such as Fred, Intrusive Interstitials Update, Mobilegeddon, RankBrain, Panda, Penguin, Hummingbird, Pigeon, Payday, EMD (Exact Match Domain), or Page Layout Algorithm are the ones that do not go unnoticed.
Read the full article below, to know in detail, the progression of Google Search Algorithms and the significant changes, over the years:
How does the Google search engine work?
Ranking systems help Google find the most relevant results for specific queries. Ranking factors based on algorithms that enable querying billions of pages in the search index help the search engine to find the most accurate results in a fraction of a second.
What are search algorithms?
Search algorithms help the query to retrieve specific data from the niched search indexes and quickly produce the most accurate and relevant results. Google ranking systems are made up of several such search algorithms. Search algorithms take into consideration many factors, including the words of your query, relevance, usability of pages, the expertise of sources, and your location and settings, and therefore presents the most relevant results to the user.
Key Factors of Google Search Algorithm that produces relevant results
The Google search algorithm depends on certain key factors to help produce the most relevant and accurate results.
Decoding the meaning of your question/word:
Google search algorithms employ simple steps to establish what sort of information the user is looking for and to understand the intent behind the query. The simple steps may range from interpreting the spellings to trying to replace certain words in our query with the synonyms of it, or it looks at the language or how specific information is required. According to Google itself, This system took over five years to develop and significantly improves results in over 30% of searches across languages.
Checking the relevance of the webpage:
Google Search Algorithms analyze webpage content according to the context of the query. The most simple relevance is identified through similarity in keywords in query and web page content. Information is tagged relevant when web pages have common keywords to search query in its metadata, description, headings, and body of the text. Google uses aggregated and anonymized interaction data to assess whether search results are relevant to queries. Google uses an elegant system that transforms data into signals that enable machine learning models to better estimate the relevance factor.
Testing the quality of the content:
Google search algorithm also ensures the results are prioritized towards the most reliable sources available. Google analyses the pages according to their expertise, authoritativeness, and trustworthiness on a given topic. The Google search algorithm prioritizes sites that seem to be valued and frequented by users. Google even keeps refining its systems through feedback from the search quality evaluation process, to better access the quality of the information in web pages.
Ensuring the usability of web pages:
Google ranking systems also evaluate the usability of web pages. Google algorithm checks to make sure whether the websites are user-friendly. Various factors affect the usability of a website, such as whether the site appears correctly in different browsers, whether the page loading times work well for users with slow Internet connections, page speed, or whether it is designed for all device types and sizes.
Looking at the context and settings:
Google Search algorithms specifically show information relevant to the user’s location, language, and other personal factors. Same queries may have different results from time to time depending on the specificity of the query. Google studies the context and setting of a user before providing search results to accurately predict the most relevant information that may be required. According to Google itself, Google queries trillions of searches each year and 15% of the queries processed each day are new.
Reason for Changes in Google's Search Algorithm
Google updates its search algorithm numerous times in a year, at least 500-600 times each year. Competing with other search engines, Google updates can affect the content and sites and how they query. Once in a while, Google makes some significant changes or search algorithm updates that considerably affect the SERPs (Search Engine Results Pages). SERPs are Google's results for our search queries.
SERP study is essential as it determines how our site ranks on Google's first page. SERP is important for Search Engine Optimisation (SEO) and how Google’s search algorithm ranks the web pages. Google aims to provide users with valuable, authentic content that benefits the users. SERP ensures shady, unauthentic, and pirated sites are penalized.
Major Google's Search Algorithm Changes or Updates
There are some significant updates that Google has made over the years. Some of the important ones are listed below:
The Panda Update
Google first launched Google Panda Update on February 13, 2011. It uses an algorithm that was named after Google Engineer Biswanath Panda. Google made this update significantly to reduce the ranking for low-quality sites. This filter targeted shady areas and lowered their SEO power which cut their order in SERPs.
Site owners saw a drop or surge in rankings since this update. After the Panda update, Google was able to identify the scammy sites more accurately. Before the update, sites having destructive quality content ranked high and dominated Google's results. Panda's update impacted 12% of areas in the USA.
The high-quality content sites were back on track in the search results after the update. There have been many updates for Panda since 2011.
The Penguin Update
Google launched the Penguin update in April 2012 to better focus its results to improve user experience. The update mainly involved penalizing sites that seemed to spam its search results. The Penguin update issued penalties to sites for buying links or obtaining them through link networks designed primarily to boost Google rankings. The update depended on Google's periodic algorithm updates and penalized the link spams.
The Hummingbird Update
Google first introduced the Hummingbird update in September 2013. The update focused on conversational or human search. The primary intent of this update was to find the intent behind a query and therefore provide search results. Google used about 200 ranking factors to produce relevant and quality content and sites. The combination of conversational language processing and intent-based search was the first step to turn the dream of semantic search into reality.
The Pigeon Update
Google first made the Pigeon update in July 2014. It was explicitly aimed at lifting the ranking of local searches. The update incorporated a new algorithm that provides more relevant and accurate local results. According to Google, this algorithm improved the distance and location ranking parameters of the search engine. This update uplifted the local businesses and helped people find them even without using geo-specific keywords. After this update, the searches became more user-friendly.
The Mobilegeddon Update
The Mobilegeddon update first came out on April 21, 2015. This update prioritized the display of websites on smartphones and other mobile devices. According to Google, it effects or impacts only the search results in mobile devices. Also, it affects the search results in all languages globally. It mainly targeted individual pages and not websites.
The Fred Update
Google launched the Fred update in March 2017. The update was related to improving content quality, specifically penalizing sites using unfair monetary tactics which negatively impact user experience. It seemed Google targeted excessive heavy ad placement, poor quality backlinks, and a few other factors to result in traffic penalties.
Fred was a catchy name for any updates related to improving content quality that was not associated with the Panda update. It has been in talks predominantly since 2017.
Conclusion
Major search algorithm updates can be upsetting, but Google aims to produce the best possible SERPs and provide user-friendly and rich content. Another main reason behind Google's search algorithms' changes is that Google wants its search results to be accurate and relevant. These frequent changes in Google's search algorithm helped it filter the unauthentic webpages and give due credit to sites that produce quality content according to user requirements. Google has had a long history of famous algorithm updates and search engine changes. All of these changes were to better query user input and provide the best results possible to users.
