What Is the Google Algorithm?

The singular is a simplification. In its guide to ranking systems, Google says it uses automated systems that look at many factors and signals about hundreds of billions of web pages and other content in its index. Some of them make up the core ranking systems, the underlying technology that produces search results. Others deal with specific needs, such as information during a crisis or spam detection.

According to the same guide, the systems work mainly at page level. They also use site-wide signals and classifiers, but Google is clear that good site-wide signals do not mean every page on the site will rank well, just as poor ones do not mean every page will rank badly.

Several related terms tend to get mixed up with the algorithm. A ranking factor is a signal those systems take into account. A core update is a change to the core systems. A Google penalty, strictly speaking, is a manual action decided by a person. Googlebot crawls pages but does not rank them: ranking comes later, once a page is in the index.

Google's guide describes some of its better-known systems. It does not list all of them, and it does not say how much weight each one carries. The documented systems include: - BERT, which understands how combinations of words express different meanings and intent. - RankBrain, which relates words to concepts, so a page can be returned even if it does not contain every word in the search. - Neural matching, which matches the concepts in a query to those in a page. - Link analysis systems, including PageRank, one of the core systems since Google launched. - The site diversity system, which generally avoids showing more than two results from the same site in the top results. - Spam detection systems, including SpamBrain, which deal with content and behaviour that violate the spam policies.

Other systems on the list cover freshness, reviews, reliable information, local news and original content. MUM, Google says, is not currently used for general ranking, only for some specific applications.

The guide also records retired systems. Panda was announced in 2011 and became part of the core systems in 2015. Penguin, aimed at link spam, was announced in 2012 and integrated in 2016. The helpful content system was announced in 2022 and became part of the core systems in March 2024.

Changes are tested before launch. Google says that in 2023 it ran more than 700,000 experiments, which led to more than 4,000 improvements to Search. Some of that testing is done by external quality raters. According to Google, their ratings are used to benchmark the quality of results and do not directly affect ranking.

Major changes are announced on the Google Search Status Dashboard. For 2026, up to 18 October, it lists seven ranking updates: two core updates, in March and May; four spam updates, in March, June, August and September; and one Discover update, in February. The rollouts took between 19 and a half hours and 13 days and 16 hours.

A change to these systems can move a site's traffic more than anything the site itself changes. The practical risk is attributing that movement to the wrong cause: rising after an update and crediting the latest tweak, or falling and undoing work that was sound.

That makes the dates on the status dashboard a diagnostic tool. If traffic drops as a rollout begins, including on pages nobody has touched, the cause is probably external. If only the pages that were edited fall, the edit is the first suspect. While a rollout is still running, the data is still moving and any conclusion is premature.

The second consequence concerns strategy. Google does not publish a complete list of signals with their weights, so any list of "algorithm factors" is a third-party compilation. A more stable basis for work is the set of systems the guide describes, together with Google's guidance on helpful, reliable content.

• Record the start and end dates of every update on the status dashboard alongside your traffic data.
• Wait for a rollout to finish before drawing conclusions or reversing changes.
• Keep a group of unchanged pages when testing something, to separate your own effect from that of an update.
• Check in Search Console which pages and which queries moved, not just the total.
• Base decisions on what Google documents in its ranking systems guide rather than on isolated signals without a source.
• Always cite the guide or the announcement with its date, because systems change and some are retired.

• Talking about "the algorithm" as if it were a single formula waiting to be cracked.
• Crediting your own change for a rise or fall that coincides with a Google update.
• Confusing a drop after a core update with a penalty: a manual action shows up in Search Console, a core update does not.
• Repeating lists with a fixed number of factors as though Google had published them.
• Still optimising for Panda or Penguin as separate systems, years after Google folded them into the core systems.