Google Confirms its most significant Ranking Factors
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Google Confirms its most significant Ranking Factors.
Google has published a document on their most notable ranking signals and those they no longer use. Google's ranking factors are the signals that Google's search algorithm uses to rank websites in their search engine results. These factors constantly evolve, but there are over 200 known ranking factors, which is a lot. Luckily Google has released a document that may help you decide what to focus on and what will "move the needle" for in-house and SEO consultancy teams. Google has published a new document that talks about the more "important" ranking systems Google has deployed over the years that are both currently in use and no longer in use in the Google Search algorithm. The document is named a guide to Google Search ranking systems.This document specifies that these are the ranking systems used by Google Search. Google also provides a brief explanation of each ranking system. Note that some are multiple systems, and some are single systems. To help guide you on these, we have listed the factors that will impact your rankings and some that are no longer relevant.
Vital Ranking Factors/ Systems
Bidirectional Encoder Representations from Transformers or BERT is an AI-based system Google uses that allows them to understand how combinations of words have different meanings and intent.
Crisis Information systems
Google has created systems that provide helpful information during crises, whether in a personal emergency, natural disaster, or other widespread crises.
Google's systems understand that when people seek information about personal crises, they should display hotlines and content from trusted organisations for specific search queries.
During natural disasters or widespread crises, Google's SOS Alerts system shows updates from international, national and local authorities. These updates may include phone numbers, sites, maps, translations, Etc.
With the amount of content on the web currently, searches on Google may find millions of matching web pages. Some may be highly similar to each other. In such cases, Google's SERPs will therefore show its users the most relevant results to avoid duplication of unhelpful content. Learn more about how deduplication works and how to see omitted results if desired when deduplication happens.The removal of duplicate content also happens with the use of featured snippets. For example, if Google chooses a web page listing to become a featured snippet, they don't repeat the listing later on the first page of the results. This deduplication system declutters the results and helps people locate relevant information more easily.
The exact match domain system
Google's ranking systems consider the terms in website domain names as one of many factors to determine if it is relevant to the search query. However, their exact match domain system ensures that they give only a little credit for content hosted under domains designed to match particular questions exactly. So, for example, someone might create a domain name containing the words "performance marketing agency" or "SEO consultancy Cornwall" in the hopes that using the keywords in the domain name would propel content high in the rankings. Luckily, Google's system adjusts for this.
Google has various "query deserves freshness" systems designed to show fresher content for queries where necessary. For example, someone searching for a recently released movie probably wants recent timely reviews.
Helpful content system
Google created the helpful content system to ensure people see original, valuable content written by real people, for real people, in the SERP rather than content made with the sole intent of gaining search engine traffic.
Link analysis systems and PageRank
Google has various systems that understand how pages link to each other to understand what the pages are about and which one might be most relevant and helpful in response to a query. Among these is PageRank, one of Google's core ranking systems. PageRank has evolved significantly since its launch and is part of Google's core ranking systems.
Local news system
Google has systems that work to identify and surface local news sources whenever relevant, such as through their "Top stories" and "Local news" features.
Multitask Unified Model or MUM is an AI system capable of understanding and generating language. It's not currently used for general search rankings but for specific applications, such as improving searches for COVID-19 vaccine information and improving featured snippet callouts they display.
Neural matching is an AI-based system that Google uses to comprehend the concepts in search queries and pages and match them.
Original content system
Google has systems to help ensure that they show original content prominently in search results. This original content system includes particular canonical markup creators, which can help Google better understand which pages are the primary, which are the secondary, and where pages have been duplicated.
Removal-based demotion systems, including legal removals and personal information removals
Google has policies to allow the removal of certain types of content when required. If Google processes a high volume of such reductions involving a particular site, Google will use that as a signal to improve the SERP results. In particular:
When Google receive a high volume of valid copyright removal requests involving a given site, they can use that to downgrade other content from the website on the results page. Google also applies a similar demotion signal to complaints around defamation, counterfeit products, and court-ordered removals.
Personal information removals
If Google processes many removal requests of personal information involving a site with exploitative removal practices, they can demote other content from the site in their results. Google also looks to see if the same pattern of behaviour is happening with other sites and apply demotions to content on those sites. For example, Google may use similar demotion practices for websites that receive a high volume of doxxing content removals.
Page experience system
People prefer sites that offer an excellent page experience. Therefore Google created a page experience system that assesses various criteria, such as how quickly pages load, mobile-friendliness, if the page lacks intrusive interstitials (overlays that stop users from reading the content on the page, usually relating to pop-up ads), and if pages load securely. The system prefers content with a better page experience when many possible matches have relatively equal relevance to the search.
Passage ranking system
Passage ranking is an AI system used by Google to identify individual sections or "passages" of a web page to understand better how relevant a page is to a search and its intent.
Product reviews system
The product reviews system aims to reward better high-quality product reviews, content that provides insightful analysis and original research written by experts or enthusiasts who know the topic well.
RankBrain is an AI system that helps Google understand how words are related to concepts. It means they can serve more useful relevant content, even if it doesn't contain all of the words used in a search query, by understanding that the content is related to other terms and concepts relating to the original search query.
The Google site diversity system works so that they generally won't show more than two web page listings from the same domain in their top SERP results so that no single website tends to dominate all the top SERP results. However, Google may still show more than two listings in cases where the system determines it is particularly relevant to do so for a particular search query. The site diversity system generally treats subdomains as part of a root domain. e.g. listings from a subdomain (https://www.dcw.co.uk/facilities/devon/) and the root domain (https://www.dcw.co.uk/) will all be considered the same website. However, sometimes subdomains are treated as their site for diversity purposes, such as locational-based searches, when relevant to do so.
Spam detection systems
Unfortunately, search faces a similar challenge to your inbox regarding spam because the internet includes vast amounts of spam that, if not dealt with, would prevent the SERPs from showing the most beneficial and relevant results. To fix this issue, Google employs spam detection systems, such as SpamBrain, to deal with content and behaviours that violate their spam policies. These Spam detection systems are constantly updated to keep up with the latest ways the spam threat evolves.
The Retired Ranking systems
Some of the old ranking systems are either no longer in use or incorporated into Google's new systems.
Hummingbird significantly improved Google's overall ranking systems in August 2013. However, Google's ranking systems have continued to evolve since then.
This system, announced in 2018 as the "Speed Update", meant that where all things were equal, content loading faster for mobile users would do better in Google's mobile search results. It has since been made part of the page experience system.
This system was designed to ensure better, high-quality, original content appeared on the search engine results page. Announced in 2011 and given the nickname "Panda," it evolved and became part of the Google core ranking systems in 2015.
Penguin was designed to combat link spam. Announced in 2012 and given the nickname "Penguin", it was integrated into the core ranking systems in 2016.
Secure sites system
This system, announced in 2014, meant that sites secured with HTTPS would do better in the rankings when all things were equal. In addition, it helped encourage the growth of secure websites when using HTTPS was still relatively uncommon. It has since been made part of the page experience system.