KScorer picks the meaning of a query, Intent Brain and Orbit pick the format of the answer
After seeing with KScorer how Google settles between the possible meanings of a query (for [mercury], the planet, the metal or a fintech company), a second decision remains: what kind of result to show. [mercury planet] calls for videos, images and an encyclopedia, [mercure hotel london] for a hotel pack and a booking page, [mercury in fish pregnancy] for an official health site, [best mercury-free thermometer] for product comparisons. That choice falls to two other systems, Intent Brain and Orbit. KScorer answers the question “what is the query about?”; Intent Brain and Orbit answer “what kind of result, from what kind of source?”.
What NavBoost and KScorer showed, and what Intent Brain and Orbit add
The five Google systems involved, in the order they act
- Continuously, from the logsGlue
What it does Counts, for every query, the clicks on every result and what follows them: a click followed by a long visit is a good click. Instant Glue does the same count over the last 24 hours.
Its goal Know which results satisfy people. See the NavBoost infographic.
- When each page is indexedOrbit
What it does Sorts every page into 86 categories (tutorial, forum, product page, official site…), with a score from 0 to 100 per category. It classifies queries too.
Its goal Know what kind of page every result is.
- When Google understands the queryKScorer
What it does Settles between the possible meanings of a query: for [mercury], the planet, the metal or the fintech.
Its goal Choose what the results page will be about. See the KScorer infographic.
- When Google understands the queryIntent Brain
What it does Gives, for the query, the language and the country, the probability of 20 broad intents (images, video, place, forum, official site…), computed from the clicks counted by Glue.
Its goal Know which answer format and which source type satisfy people.
- Just before displaySuperroot
What it does Assembles the results page: links, image blocks, local pack, videos…
Its goal Build the SERP the user sees.
Our finding
Twenty “broad intents” per query, each tied to a tab, a result format or a page category
Intent Brain is a Google Search component that works out, for every query, language and country, which answer format satisfies users. It spreads the query across twenty “broad intents”, Google’s own term (BroadIntent in the schemas: images, video, place, forum, official site…), and measures the satisfaction obtained for each one, from the clicks counted by Glue, NavBoost’s click memory. Most of these values also state what they trigger in the SERP: a tab to promote (mode_link), a result format or filter (result_format_id), an expected page category (document_intent).
- Google measures from clicks, in every language and every country, the answer format a query expects: [mercury] does not expect the same thing on google.com as [mercure] on google.fr.
- Nine broad intents drive a visible SERP element: a promoted tab (Images, Videos, Maps, Apps, Shopping, News), a result format or the Forums filter.
- Eight point to a page category that Orbit attaches to every document in the index: the query and the page are described with the same names (encyclopedia, government, forum…).
Tabs and result formats
Seven broad intents trigger a Google tab or a result format on the page.
IMAGEimagestab IMAGESformat RESULT_FORMAT_ID_IMAGESVIDEOvideostab VIDEOSformat RESULT_FORMAT_ID_VIDEOSLOCALplaces and addresses, in Maps or a local packtab MAPSformat RESULT_FORMAT_ID_LOCALSHOPPINGproducts to buytab SHOPPINGformat RESULT_FORMAT_ID_PRODUCTSNEWSnewstab NEWSformat RESULT_FORMAT_ID_NEWSAPPSappstab APPLICATIONSSHORT_VIDEOshort videosformat RESULT_FORMAT_ID_SHORT_VIDEOS
Lived experience and discussion
Two broad intents lead to the Forums filter and each points to a page category. Google has counted the first since July 3, 2023, three weeks after the Perspectives filter (content posted by people, renamed Forums in 2024) reached mobile, and the second since August 29, 2023.
AUTHENTICITYlived experience, a person’s first-hand accountformat RESULT_FORMAT_ID_FORUMSpage category of the same namecounted since July 3, 2023UGC_DISCUSSIONa discussion between usersformat RESULT_FORMAT_ID_FORUMSpage category of the same namecounted since August 29, 2023
Web, exploration, freshness, video by use
Five values trigger no specific element.
FRESHrecent results; the freshness counters measure satisfaction by the age of the date shown in the snippetTOLEDOa video suited to the expected use (learning, getting informed, being entertained, finding a song, watching a dubbed version), according to TOLEDO, Google’s video system: it adds to the analysis of the query, then a TOLEDO twiddler, a rule that reorders results, adjusts where videos sit. YouTube search uses the same five uses.counted since October 9, 2023EXPLOREexploring a topic, as in the SERP’s “Explore” blockWEBclassic web linksUNKNOWNundetermined
The expected source type
Six broad intents say which source the query calls for. Each points to the page category of the same name, which Orbit attaches to pages in the index.
INFORMATION_SOURCE_GOVERNMENTan official site, a government bodypage category of the same nameINFORMATION_SOURCE_ENCYCLOPEDIAan encyclopediapage category of the same nameINFORMATION_SOURCE_NEWS_PUBLISHERa news publisherpage category of the same nameINFORMATION_SOURCE_MERCHANTa merchantpage category of the same nameINFORMATION_SOURCE_UGCcontent published by userspage category of the same nameINFORMATION_SOURCE_OTHERanother kind of sourcepage category of the same name
Blue background: the broad intent points to an Orbit page category (8 of 20).
In the schemas
BroadIntentthe list of the twenty broad intentsmode_linkthe tab to promote: Images, Videos, Maps…result_format_idthe result format or filter: images, products, Forums…document_intentthe expected page category, in Orbit’s vocabularylogging_start_time_in_unix_epoch_secondsthe date a broad intent started being counted
[mercury] in the US, [mercure] in France: the same word calls for neither the same meaning nor the same format
Take [mercury]. On October 28, 2026, we captured the results page for [mercury] on google.com and for [mercure] on google.fr, then identified the entities (planet, metal, brand, place…) each of the top ten results is about. The formula of KScorerKScorer’s refres_question_rank signalΣ (1 / rank × score of the entity in the page), over the top 10 resultsEach result gives the meaning the score of its entity in the page (from 0 to 1), divided by its rank: the 1st counts for 1, the 2nd for 1/2, the 10th for 1/10. A meaning’s share is its total set against the total of all meanings compared.Engineers’ comment: “Sum of (1/web_rank * refres score of all question entities) over top 10 results.”, the system that settles between the meanings of a query, then gives each meaning’s share: every result gives a meaning the weight of the entity in the page, divided by its rank.
mercury
google.com · United States, in English · 368,000 searches a month
Five of the top ten results come from the fintech: its help center, its app, its login page, its legal page, its Facebook page. The planet places only a National Geographic video, in 8th position.
mercure
google.fr · France, in French · 60,500 searches a month
Both hotel meanings rest on a single result, the chain’s website, in 2nd position. Under the search bar, the suggestion chips offer Liquide (liquid), Planète, Hôtel, Rouge (red), Définition.
Eight queries around [mercury], eight answer formats
For eight more precise queries around the same word, here is what the real SERPs show (captured on October 28, 2026 on google.com, on desktop), with the broad intents they reflect and the page categories they put on top.
- mercury planet
Wikipedia, NASA, the Smithsonian, the Planetary Society…, plus videos, short videos, a “What people are saying” block and images.
Broad intentsIMAGEVIDEOSHORT_VIDEOINFORMATION_SOURCE_ENCYCLOPEDIAPage categoriesINFORMATION_SOURCE_ENCYCLOPEDIA - mercure hotel london
A hotel pack at the top of the page, with the city’s Mercure hotels, then the Accor group’s website, Tripadvisor, Kayak and booking sites.
Broad intentsLOCALPage categoriesRESERVATIONTRAVEL_GUIDE - mercury retrograde 2026
Seven of the top ten snippets show a 2026 date, at Vogue, Cosmopolitan, the Statesman, Astrostyle…: the query wants this year’s dates.
Broad intentsFRESHINFORMATION_SOURCE_NEWS_PUBLISHERPage categoriesTIME_SENSITIVITYINFORMATION_SOURCE_NEWS_PUBLISHER - mercury in fish pregnancy
The FDA first, then the NIH twice, the EPA, two Australian government agencies and the Mayo Clinic: six of the top ten are public bodies.
Broad intentsINFORMATION_SOURCE_GOVERNMENTPage categoriesINFORMATION_SOURCE_GOVERNMENTYMYL_HEALTH_OR_SAFETY - broken mercury thermometer
A “Discussions and forums” block with Reddit threads (“I broke a mercury thermometer”), Quora and two wikiHow tutorials.
Broad intentsUGC_DISCUSSIONAUTHENTICITYPage categoriesFORUMUGC_DISCUSSIONTUTORIAL - best mercury-free thermometer
Popular Science, CNN Underscored and Consumer Reports next to Walmart and Target, several product blocks and a forums block.
Broad intentsSHOPPINGINFORMATION_SOURCE_MERCHANTPage categoriesPRODUCT_TOPNPRODUCT_COMPARISONSHOPPING_MERCHANT_PRODUCTLISTICLE - freddie mercury
The knowledge panel, a carousel, short videos, a “What people are saying” block and images.
Broad intentsVIDEOSHORT_VIDEOIMAGEPage categoriesINFORMATION_SOURCE_ENCYCLOPEDIANEWS - freddie mercury bohemian rhapsody
The song’s knowledge panel with its listening buttons, short videos, YouTube, Spotify and a “What people are saying” block.
Broad intentsTOLEDOVIDEOSHORT_VIDEOPage categoriesLISTENLYRICS
Switching tabs counts as an answer
For every broad intent, Intent Brain counts satisfaction in two ways:
- on the page: the satisfaction a result of that type brings. On [mercure hotel london], it is a click on the hotel pack followed by a visit that lasts;
- in the tab: the satisfaction that follows a switch to the matching tab. The user who leaves the SERP for Maps also expresses the LOCAL broad intent.
The two shares are stored in separate counters: Google knows whether a query is satisfied by a block on the page, or whether people prefer the full tab.
A calculation Google patented for images
A Google patent (US8346815B2, 2011) computes a query’s image intent by comparing how often it is typed in Google Images with how often it is typed in web search, complemented by clicks on images. Intent Brain applies the same logic to six tabs: Images, Videos, Maps, Apps, Shopping and News.
From Glue’s clicks to the query’s statistics
These counters come from Glue, NavBoost’s click memory. Instant Glue, its real-time version, keeps the same counters over the last 24 hours. Intent Brain groups them by query, language and country and adds the probability of each broad intent. A query too rare to have statistics of its own takes those of close queries that share its characteristic words (its salient terms).
In the schemas
The counters of a broad intent
probthe probability that the query carries this broad intentnum_queriesthe queries where it is served, by a result or by a tabnum_queries_with_impressionthe queries where a result of this type is showngoodness_sumtotal satisfaction (goodness, NavBoost’s satisfaction measure)result_num_queriesthe queries served by a result on the pageresult_goodness_sumthe satisfaction those results bringmode_num_queriesthe queries served by switching to the tabmode_goodness_sumthe satisfaction that follows the tab switchnum_query_events_since_intent_logging_startthe queries counted since the broad intent started being counted
A query’s statistics
query · language · countrythe query, the language and the country: statistics are kept for each combinationtotal_queriesthe total number of searchestotal_mobile_queriesthe share made on mobileqbst_term_statsthe query’s characteristic words (salient terms), with their weightbroad_intent_dataone entry per broad intent, with its countersintent_catalogthe same counters for intents more precise than the twenty broad ones, referred to by name
Freshness is measured by the date shown in the snippet
For every broad intent, Intent Brain breaks satisfaction down by the age of the date shown in the snippet. The 2024 leak defines that date, bylineDate, as “the date that will be shown in the snippets in web search results”. On [mercury retrograde 2026], seven of the top ten results show a 2026 date: these counters tell Google whether people are satisfied with yesterday’s page or with last year’s. Set against all dated results, they give the query’s need for freshness, the FRESH broad intent.
The US antitrust trial against Google showed what these counters do in real time. A 2018 internal Google document, cited in 2023, describes the query [nice pictures] on the day of the Nice attack: “Instant Glue will suppress Image Universal. News and pictures from Nice, France is the main intent of the query.” Within hours, an image query becomes a news query.
In the schemas: the freshness counters
result_goodness_sum_byline_age_lt_1dsatisfaction from results dated less than a day agoresult_goodness_sum_byline_age_lt_3d… less than three days agoresult_goodness_sum_byline_age_lt_30d… less than 30 days agoresult_goodness_sum_byline_age_lt_90d… less than 90 days agoresult_goodness_sum_byline_age_lt_365d… less than a year agoresult_goodness_sum_has_byline_agesatisfaction from all results that show a dateresult_goodness_sum_fresh_vesatisfaction obtained in a fresh page element, such as a news block
Orbit classifies every page, and the SEO trade’s search intents are in it
Orbit is the Google system that sorts every page in the index into categories: what the page lets you do (book, log in…), its format (tutorial, review, forum…) and who publishes it (news, government, merchant…).
It gives every page a score from 0 to 100 for each of the 86 categories, and those scores are stored with the page in the index (the 2024 leak shows them among indexing data).
KScorer uses it to check that the top 10 pages confirm a meaning.
Categories add up: a car insurance comparison published by an insurer is at once a product comparison, a merchant page and YMYL financial content.
The four search intents the SEO trade uses to classify queries (navigational, informational, commercial, transactional) are found in these categories. So are two of the “3 Cs”, the method Ahrefs popularized for analyzing a SERP before writing: look at the top results’ content type (product page, article, category page…), content format (tutorial, comparison, list, review…) and content angle (for beginners, cheap, updated this year…). Orbit names the type and the format; the angle remains the writer’s ground.
Navigational
LOGINaccount loginCONTACT_PAGEcontact pageCUSTOMER_SUPPORTcustomer supportREGISTERsign-up
Informational
TUTORIALtutorialRECIPESrecipesMANUALmanualREPAIRrepairSTUDY_GUIDEstudy guideINFORMATION_SOURCE_ENCYCLOPEDIAencyclopedia
Commercial
PRODUCT_REVIEWproduct reviewPRODUCT_COMPARISONproduct comparisonPRODUCT_BUYING_GUIDEbuying guidePRODUCT_TOPNtop N productsSPECStechnical specs
Transactional
SHOPPING_MERCHANT_PRODUCTmerchant product pageRESERVATIONbookingCOUPONcouponRENTrentalREAL_ESTATE_LISTINGreal estate listingJOB_POSTINGjob posting
Google retires the categories it answers itself
27 categories carry the deprecated mark: engineers must no longer use them in new development. Most describe a need Google meets itself, in the SERP or in Maps: directions, opening hours, menu, showtimes, calculator, translation, flight tracking, definition, sports scores… A page that only gives opening hours or converts a unit therefore answers a need Google handles without it.
Commerce splits into five roles
The two broad commerce labels, BUYING_GUIDE and SHOPPING_REVIEW_OR_BUYING_GUIDE, are retired in favor of five categories: the merchant product page, the product review, the comparison, the buying guide and the top N. Google therefore knows whether a page is for buying or for choosing, and how. Orbit also names sensitive topics: three YMYL categories, mugshots and non-consensual intimate images, whose sites Google demotes when they receive many removal requests.
In the schemas: the other categories in service
Editorial formats
NEWSnewsREVIEWreviewRANKINGrankingLISTICLElist articleAGGREGATORaggregatorMEME_DOCUMENTmeme document
Contributions
FORUMforumUGC_DISCUSSIONdiscussion between usersAUTHENTICITYlived experienceQNAquestions and answersSOCIAL_MEDIAsocial media
Who publishes
Seven source types, against six source broad intents in Intent Brain: the research institute has no counterpart on the query side.
INFORMATION_SOURCE_GOVERNMENTgovernmentINFORMATION_SOURCE_NEWS_PUBLISHERnews publisherINFORMATION_SOURCE_MERCHANTmerchantINFORMATION_SOURCE_UGCuser contentINFORMATION_SOURCE_RESEARCH_INSTITUTEresearch instituteINFORMATION_SOURCE_OTHERother source
Sensitive topics
YMYL_HEALTH_OR_SAFETYYMYL: health or safetyYMYL_FINANCIAL_SECURITYYMYL: financial securityYMYL_SOCIETYYMYL: societySYMPTOMSsymptomsMUGSHOTmugshotNCEI_ISPInon-consensual intimate images and deepfakes
Uses and time
TRAVEL_GUIDEtravel guideLYRICSsong lyricsLISTENlistenSHEET_MUSICsheet musicTIME_SENSITIVITYtime sensitivity
Google has a label for listicles, and it measures it
The word SEOs use for “10 best…” articles is Google’s word too: LISTICLE. Three neighbors come with it: LISTICLE_OR_AGGREGATOR, AGGREGATOR (pages that compile content from elsewhere) and LISTICLE_EXP, an experimental variant. All four go to the logs without serving as a filter: Google tracks them closely.
Self-promotional rankings were caught out
Lily Ray, a leading US figure in SEO, documented the problem. In May 2025, she showed that a ranking in which a company names itself “best” is enough for AI Overviews to repeat the claim. In February 2026, she measured the fall: from late January, seven SaaS publishers that had published dozens of these rankings lost 29% to 49% of their organic visibility.
Was Lily heard in Mountain View? 😉 One thing is certain: it is an amusing twist to find the SEO trade’s own jargon, LISTICLE, in Google’s internal schemas.
On [best mercury-free thermometer], the top rankings test
The google.com top 10 has Popular Science, CNN Underscored and Consumer Reports next to Walmart and Target, and Google adds lists of its own: several product blocks and suggestion chips by use under the search bar (oral, temple, in-ear, no touch…). On google.fr, the tests of Que Choisir and Les Numériques sit next to a product block titled “Comparateurs” and merchant pages. The rankings that hold the top of these SERPs come from publishers that test the products.
In the schemas
LISTICLElist-format article · measured in the logsLISTICLE_OR_AGGREGATORlist or aggregator · measuredAGGREGATORaggregator of content from elsewhere · measuredLISTICLE_EXPexperimental listicle variant · measuredPRODUCT_TOPNselection of N products · filterable and measuredRANKINGranking · filterable
What Google filters, what it measures
Orbit, the system that sorts pages in the index into categories, can attach two options to each category:
add_restrictmakes the category filterable: Google can restrict a search to that category’s pages, as the Forums filter does. 35 categories in service have it.should_logmakes the category measurable: Google tracks it in the statistics drawn from its logs, under the name “Orbit Doc Intents”. 19 categories have it.
The two lists barely overlap. Formats and uses (tutorial, recipe, news, booking…) serve as filters; sources and listicles are measured without serving as filters.
Seven categories have both options: the five shopping roles, discussion between users and lived experience. These are the two topics Google has been communicating about for several years: the product reviews updates and the place of forums in the SERP. Google can isolate these pages and track how they perform in its statistics.
In the schemas
Filterable and measured: 7 categories
SHOPPING_MERCHANT_PRODUCTmerchant product pagePRODUCT_REVIEWproduct reviewPRODUCT_COMPARISONproduct comparisonPRODUCT_BUYING_GUIDEbuying guidePRODUCT_TOPNtop N productsUGC_DISCUSSIONdiscussion between usersAUTHENTICITYlived experience
Measured without serving as a filter: 12 categories
The six source types that match Intent Brain’s broad intents, the four listicles, shopping in the broad sense and time sensitivity.
INFORMATION_SOURCE_*government, encyclopedia, news, merchant, users, otherLISTICLE · LISTICLE_OR_AGGREGATOR · LISTICLE_EXP · AGGREGATORthe listicle familySHOPPINGshopping, general labelTIME_SENSITIVITYtime sensitivity
The query and the page meet before ranking
Everything is settled before pages are ranked. When Google understands a query, it attaches several pieces of information to it: the words that characterize it, its own Orbit category (Orbit classifies queries too) and Intent Brain’s output. Ranking systems therefore know which answer format clicks have validated before they compare pages. Take [mouse]: the animal or the computer device?
- The querymousetyped on google.com
- The meaningKScorerpicks the computer device, not the animal
- The formatIntent Brainexpects products to buy:
SHOPPING, with images - The pageOrbitfiles Target, Walmart, Amazon and eBay as merchants:
INFORMATION_SOURCE_ MERCHANT - The SERPSuperrootassembles the page: images, a popular products block, then the merchants; the animal only comes up in one “People also ask” question
Categories follow every result to the SERP
Orbit scores travel with every result to Superroot, the system that assembles the results page. They also enter RankLab, the environment where Google measures its ranking signals, with a yes or a no for each category: a score is not enough, the category has to be retained for the page. AI search uses these categories too: the search response receives Orbit categories from Mars, the internal name of the AI search servers.
Orbit also helps KScorer decide
KScorer consults Orbit to judge whether the top 10 pages are reliable enough to rule out a meaning of the query. The signal is called orbit_results_trusted; the salient terms in the comment are the words that characterize a page.
Engineers’ commentOrbit produces this feature to decide whether a result set can be "trusted" for making a suppression decision. This is a function of result document trust, language, presence of salient term vectors.
For SEO: aim for the format the SERP has validated, in every country
Read the SERP as a measurement, country by country
The blocks that dominate a SERP and the order of the filters under the search bar reflect what clicks have validated, query by query: a hotel pack for [mercure hotel london], videos for [mercury planet], forums for [broken mercury thermometer]. Aim for the format they show: captioned images, an up-to-date Google Business Profile, product pages with their merchant data, an answer drawn from experience. And check every market separately: [mercury] and [mercure] share neither the dominant meaning nor the blocks.
Pick the page category before writing
Review, comparison, buying guide, top N and merchant page are five distinct categories, each measured separately. On a query that expects an official source, like [mercury in fish pregnancy], a merchant page starts at a disadvantage; on an experience query, like [broken mercury thermometer], first-hand accounts and forums answer better than a generic article.
Justify every listicle
Google labels and measures listicles. A ranking that sets out its criteria, its tests and its selection method follows Google’s guidance on reviews. The ranking where the publisher puts itself first is the format Lily Ray saw fall.
Vendors, fire up the JEV
While rank trackers can still capture SERPs (Google is making life hard for scrapers), they have what it takes to turn these schemas into reports. Three projects:
- show for every keyword the number of dated snippets and the average age of their dates;
- sort every top 10 result into Orbit’s categories (merchant page, review, comparison, forum, official site, listicle…);
- map the blocks shown and the order of filters to Intent Brain’s broad intents (
IMAGE,LOCAL,SHORT_VIDEO,UGC_DISCUSSION…), country by country.
An SEO would then see at a glance which format and which source a query expects.
The meaning with KScorer, the format and the source with Intent Brain, the page category with Orbit: three decisions made before pages are compared, and all of them visible in the SERP.
A closer look at the mechanisms
The schemas, field by field
The Intent Brain and Orbit schemas, to browse here or download as a single file.
The .proto files6 files · 15 types · 58 fields · 124 values
gws/shared/mode_promotion.proto1 type · 6 values
Themes: What a broad intent triggers
knowledge/answers/interpretation_ranking/proto/kscorer_feature.proto1 type · 5 fields
Themes: KScorer consults Orbit
quality/intentbrain/proto/query_intents.proto8 types · 34 fields · 25 values
Themes: Intent Brain: a query’s broad intents
- The 20 broad intents
intent_brain.BroadIntent - A query’s intents
intent_brain.QueryIntentData - One broad intent of the query
intent_brain.QueryIntentData.BroadIntentData - Probability and satisfaction of a broad intent
intent_brain.IntentStats - Satisfaction by page age
intent_brain.IntentStats.FreshnessCounters - Predicted signals
intent_brain.PredictedSignal - The people behind a query
intent_brain.QueryPopularity - Salient terms (QBST)
intent_brain.QBSTTermStats
quality/navboost/proto/intent_brain_signals.proto3 types · 19 fields
quality/orbit/asteroid_belt/proto/document_intent.proto1 type · 86 values
Themes: Orbit: page categories
quality/result_filtering/protos/result_filter_id.proto1 type · 7 values
Themes: What a broad intent triggers