--- title: "What Google actually names in its own ranking systems guide" url: https://seomadman.com/research/google-ranking-systems-documented section: research published: 2026-07-14T00:00:00.000Z modified: 2026-07-14T00:00:00.000Z author: Adam Hafez topics: ["Core updates", "Technical SEO"] --- # What Google actually names in its own ranking systems guide ## The short answer Google's own ranking systems guide names 17 current systems, from BERT and RankBrain to SpamBrain and site diversity, plus four retired ones including the helpful content system, now folded into core ranking. It gives each a short functional description, never a weight or formula, and it does not name NavBoost. ## Key takeaways - Google's ranking systems guide names 17 current systems and 4 retired ones, each with a one or two sentence functional description. - BERT, MUM, neural matching, passage ranking and RankBrain are the five systems the page itself labels as AI systems. - The page states plainly that the helpful content system has been retired and folded into core ranking systems, contradicting any assumption that it still runs as a separate signal. - SpamBrain is named as one system within a broader "spam detection systems" section, not as its own standalone heading. - NavBoost, the click-based re-ranking system described in DOJ trial testimony, does not appear anywhere on Google's own official systems page. SEO discourse mostly runs on what got leaked or what a witness said under oath in an antitrust trial. Less discussed is that Google also just publishes a list. The "Guide to Google Search ranking systems," maintained on Google's own developer documentation, names specific systems by name and gives each one a short, plain description of its job. It is not a spec and it is not a weight table, but it is real, it is current, and almost nobody quotes it directly. ## Systems the page labels as AI systems Five of the named systems get the same qualifier from Google: "AI system." **BERT** (Bidirectional Encoder Representations from Transformers) "allows us to understand how combinations of words express different meanings and intent." **MUM** (Multitask Unified Model) is described as capable of understanding and generating language, but the guide is explicit that it is "not currently used for general ranking," only for narrower applications such as COVID-19 vaccine information searches and featured snippet callouts. **Neural matching** understands "representations of concepts in queries and pages" and matches them to each other. The **passage ranking system** identifies individual sections of a page to judge relevance to a search more precisely than page-level matching allows. **RankBrain** helps Google "understand how words are related to concepts," so a page can rank for a query even without the exact words used in the search. **The distinction between RankBrain and neural matching is one Google draws itself, not one this piece is inferring.** Both concern understanding meaning beyond literal keyword matching, and Google lists them as separate systems with separate one-line descriptions rather than treating one as a successor to the other. ## Systems for specific ranking needs The rest of the guide's current entries handle narrower jobs rather than general language understanding. **Crisis information systems** cover both personal crises, such as suicide or poison-related queries surfacing hotline content, and wide-scale events through the SOS Alerts system. **Deduplication systems** keep near-identical pages from cluttering one results page. The **exact match domain system** stops a domain name alone, such as one built from a keyword phrase, from earning outsized ranking credit. **Freshness systems** raise newer content for queries where Google judges recency matters, its own example being a just-released movie or a recent earthquake. **Link analysis systems and PageRank** remain listed as part of Google's core ranking systems, in use "since Google first launched," though the guide says how PageRank works "has evolved a lot since then." **Local news systems** surface local sources through features like Top Stories and Local News. **Original content systems** aim to show original reporting ahead of sites that merely cite it, supported by canonical markup. **Removal-based demotion systems** downrank sites with a significant volume of valid legal removals or personal-information removal complaints. **Reliable information systems** work to surface authoritative pages, elevate quality journalism, and, when reliable information is thin, show content advisories on rapidly changing topics. The **reviews system** rewards "high quality reviews... written by experts or enthusiasts who know the topic well." The **site diversity system** generally limits results to two listings per site, treating most subdomains as part of the root domain. **Spam detection systems**, the guide says, include **SpamBrain by name** among the tools used against spam policy violations, a detail worth flagging because SpamBrain gets no heading of its own; it is named inside the spam detection section rather than listed as a standalone entry the way BERT or RankBrain are. ## What got retired, and why it matters The guide keeps a "Retired systems" section for exactly this reason: names change status, and Google says so rather than quietly dropping them. As of this page's current version, four systems are listed there: **Hummingbird**, a major 2013 ranking overhaul; **Panda**, folded into core ranking systems in 2015; **Penguin**, aimed at link spam and folded in during 2016; and, notably, the **helpful content system**, which Google's guide now describes as incorporated into its broader core ranking systems rather than continuing to operate as a separate one. Anyone still describing "the helpful content system" as a distinct, currently-running system is describing an earlier state of Google's own documentation, not its current one. ## Why we care This site already published a piece on [NavBoost](/research/navboost-doj-trial-click-signals), built entirely from DOJ trial testimony and a leaked internal document, precisely because Google has never put NavBoost on a page like this one. That gap is the honest finding here: Google maintains a real, named, publicly documented list of ranking systems, and NavBoost, described under oath by its own VP of Search as "one of the important signals," is not on it. That does not mean the guide is dishonest or that NavBoost is fabricated; it means the industry's two best public windows into Google's ranking systems, official documentation and trial disclosure, currently describe two non-overlapping sets of names, and treating either set as the complete picture overstates what either source actually offers. Read the guide for what Google is willing to name and describe in its own words, and read the NavBoost piece for what it takes a subpoena to surface. Neither is the full architecture, and Google's own page says so directly: this is "some of our more notable ranking systems," not all of them. ## Frequently asked questions ### Does Google's official systems guide mention NavBoost? No. NavBoost does not appear anywhere on the current ranking systems guide. It is known publicly only through DOJ v. Google trial testimony and a separately leaked internal document, both covered in a separate piece on this site, not through anything Google has published on its own developer documentation. ### Is the helpful content system still a separate ranking system? No, not as a standalone system. Google's guide lists it under "Retired systems," stating it was folded into the broader core ranking systems rather than continuing to run on its own. ### Does Google say how much each named system affects rankings? No. The guide gives short, plain-language functional descriptions of what each system is for, not a weight, a percentage, or a formula. Treat every description here as what the system is meant to do, not as a measurement of its influence on any given query. ## Sources 1. [A guide to Google Search ranking systems](https://developers.google.com/search/docs/appearance/ranking-systems-guide) - Google Search Central (primary)