Google Algorithms
Since its founding, Google has been constantly evolving and fueled by algorithms. Over the years, it has developed and updated algorithms in areas such as basic search, spam and quality, user experience, local search, visual searches, and fresh content. While some algorithms are still in use, Google has discontinued a few algorithms developed in previous years.
Below, we have listed Google’s search algorithms categorized by type.
Note: Google doesn’t name every algorithm it releases, but people in the SEO industry assign names to them.
PageRank Algorithm (1998)
An old search ranking algorithm that determines rankings based on the number of quality links a website has.
PageRank is an older algorithm that has been improved over the years. Today, Google still uses this algorithm, but not as intensively as it did in the past. Now, much more powerful systems are in place.
Google Hummingbird Algorithm (2013)
An algorithm designed to understand users’ search intent (user intent or search intent) and provide more accurate results on the search results page. The Hummingbird algorithm specifically aims to process long and complex search queries and match them with relevant results.
Google RankBrain Algorithm (2015)
Google’s first deep learning system.
RankBrain is an artificial intelligence algorithm created to understand which concepts are related to the queries users search for.
Google Neural Matching Algorithm (2018)
The Neural Matching algorithm is designed to connect users’ search queries with web content semantically, rather than just based on keywords.
Using a deep learning system, the algorithm interprets the meaning behind user search queries. Even if there isn’t an exact match in the search terms, it contextually links the user to the desired result.
Google SMITH Algorithm (2020)
Google SMITH (Siamese Multi-depth Transformer-based Hierarchical) is an algorithm created to understand and process long documents and queries.
Google BERT Algorithm (2019)
Google BERT (Bidirectional Encoder Representations from Transformers) is a new technique for Natural Language Processing (NLP) and, like other search algorithms, aims to understand the meaning behind the queries users search for.
The BERT algorithm focuses on small details and nuances in search queries.
Google MUM Algorithm (2021)
Google MUM (Multitask Unified Model) is another AI-powered search algorithm. It works by understanding complex queries from users and matching them with the most relevant results.
With its natural language understanding (NLU) model and multitasking techniques (such as content comprehension and cross-language understanding), MUM aims to help users reach their desired results with fewer queries.
Google Penguin Algorithm (2012)
Google released the Penguin algorithm in 2012 to combat spam on the web. It is an algorithm that works by filtering out spammy links to provide users with a better browsing experience.
Google Panda Algorithm (2011)
The Panda algorithm is an algorithm that ensures websites with high-quality content rank on the search results pages. It has been improved over the years with new versions.
Google Freshness Algorithm
The Google Freshness algorithm is a search algorithm that ensures the results listed for queries on Google are up-to-date. Users want to see fresh and current content.
For example, a user searching for “breaking news” expects to see the latest updates, not news from a few days ago.
The Freshness algorithm checks whether content is kept up-to-date. Another example is when searching for “UK visa fees,” the results listed should be the most current and relevant. Content creators need to keep such pages updated.
Google Pirate Algorithm
The Google Pirate algorithm is a search algorithm that reduces the visibility of pages containing pirated content (such as pirated music, movies, videos, etc.) in search rankings.
Google aims to prioritize showing sources with copyright protection to users, minimizing the appearance of pirated material.
Helpful Content Update (2022)
The Helpful Content Update is a Google update that focuses on evaluating content on web pages to ensure it is user-centered and provides value.
Google emphasizes that content should not be written solely to rank higher in search engines, but instead should genuinely benefit users, offer a good experience, and provide accurate information. The Helpful Content Update evaluates content based on its quality and usefulness.
Page Layout Algorithm Update or Google Top Heavy Algorithm
The algorithm that penalizes web pages with excessive ads, particularly those at the top of the page that hinder users from accessing content, is known as the Page Layout Algorithm Update or Top Heavy Algorithm.
It was released in 2012 and updated in 2014.
Google E-E-A-T (2022)
Google E-E-A-T stands for Experience, Expertise, Authoritativeness, and Trust, which are factors used to assess the quality of a web page.
Note: The concept was first introduced as E-A-T in the core update released on August 1, 2019. Later, on December 15, 2022, Experience was added to make it E-E-A-T.
Google Caffeine (2010)
Google Caffeine is an indexing system that allows newly published content to be indexed more quickly, ensuring that Google’s search engine has access to the most up-to-date and current information.
As the web grew over the years, with an increase in videos, photos, news, and real-time updates, user expectations from search engines also grew. Google Caffeine was one of the systems developed to quickly index real-time information, and it was a significant advancement at the time. The system was officially announced as complete on June 8, 2010.
