From 4900e0a3698b8b80c33df326190976e0cfbc7b91 Mon Sep 17 00:00:00 2001 From: grokbot_ty Date: Thu, 1 Oct 2026 10:15:15 -0700 Subject: [PATCH] Deepen labeling chapter: Bing, Yelp, and data aggregators. MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Give Bing Places and Yelp real weight next to GBP/Apple, note Core 3 richness order, and treat aggregators as a fact-distribution layer for Presence — not a genre parent. --- docs/SELF_SERVE_AI_DISCOVERABILITY_CONCEPT.md | 20 ++++++++++++------- 1 file changed, 13 insertions(+), 7 deletions(-) diff --git a/docs/SELF_SERVE_AI_DISCOVERABILITY_CONCEPT.md b/docs/SELF_SERVE_AI_DISCOVERABILITY_CONCEPT.md index 07991c0..bc0d9fd 100644 --- a/docs/SELF_SERVE_AI_DISCOVERABILITY_CONCEPT.md +++ b/docs/SELF_SERVE_AI_DISCOVERABILITY_CONCEPT.md @@ -60,17 +60,23 @@ So for version one, the highest priority is an **interactive web app** the owner A **taxonomy** here means the set of categories used to say what kind of business something is — plumber versus restaurant versus hotel — so listings, maps, and assistants know what queries it belongs to. -There is no single industry-wide taxonomy that Apple, Google, and Yelp all use. Each platform keeps its own list. +There is no single industry-wide taxonomy that Apple, Google, Bing, Yelp, and the listing aggregators all use. Each keeps its own list (or feeds someone else’s). **NAICS** (North American Industry Classification System) is the U.S. government’s statistical system for classifying businesses by what they produce. It is good for reports and some B2B software. It is not how someone searches “plumber near me” on a map. **SIC** is the older system NAICS replaced for federal stats. -**Google Business Profile** has its own category IDs (often looking like `gcid:…`), available through Google’s Business Information API (`categories.list`, region US / language en). That official list is a **flat catalog of roughly 4,050 leaves** — not a hierarchy that matches our genre parents. Google does not publish a downloadable tree that says “these GCIDs belong under service-area trades.” A public September 2026 compilation of **4,053** US English GCID names (with third-party industry buckets used only for structure) is useful for research; those buckets are **not** Google’s official parents. We use GBP GCIDs as **outbound presence-check maps** and fix suggestions, not as our spine. +**Google Business Profile** has its own category IDs (often looking like `gcid:…`), available through Google’s Business Information API (`categories.list`, region US / language en). That official list is a **flat catalog of roughly 4,050 leaves** — not a hierarchy that matches our genre parents. Google does not publish a downloadable tree that says “these GCIDs belong under service-area trades.” A public September 2026 compilation of **4,053** US English GCID names (with third-party industry buckets used only for structure) is useful for research; those buckets are **not** Google’s official parents. We use GBP GCIDs as **outbound presence-check maps** and fix suggestions, not as our spine. In practice GBP is usually the **richest** owner-facing surface (categories, services, attributes, photos). -**Apple Maps / Business Connect** has its own primary category (one main label) plus optional extras; the public docs have been shifting as Apple folds Connect into a broader “Apple Business” offering. **Yelp** has its own tree of category aliases, published through Yelp’s developer APIs. +**Apple Maps / Business Connect** has its own primary category (one main label) plus optional extras; the public docs have been shifting as Apple folds Connect into a broader “Apple Business” offering. Owner-facing field labels are documented; partner API schemas are often gated. Mid richness versus GBP — good for place card truth, weaker 1:1 parity on things like GBP `serviceItems`. -**schema.org’s LocalBusiness** types are an open vocabulary used widely on the web for structured data (the markup that helps search engines understand a page). That is the best spine for an AI-era product that also wants to publish clear web facts: owner-friendly genres inside our product, keyed to schema.org where they fit, optional NAICS when a statistical code helps, and **outbound maps** — translation tables — from our genres to Google, Apple, and Yelp categories when we check presence or suggest fixes. +**Bing Places for Business** is Microsoft’s local listing surface (feeds Bing / Microsoft local experiences). Categories use Bing’s own IDs (`BPCategoryId` + name); owners can attach multiple categories with one primary. The trusted-partner API is certificate-gated, not a public crawl API — field maps on this branch already treat Bing as the **thinnest** of a “Core 3” with GBP and Apple (`docs/product/genre-packs/`). Bing still matters for Presence: wrong or missing Bing categories are a real “are you on the map?” miss, especially where Copilot / Microsoft surfaces lean on Bing Places data. Do not pretend Bing’s category tree equals Google’s. -We should not treat Apple’s, Google’s, or Yelp’s lists as our internal source of truth. They drift and they disagree. Building those maps ourselves is normal; nobody publishes an official three-way concordance. +**Yelp** keeps its own hierarchy of category **aliases** (developer APIs expose the tree). Yelp is both a discovery surface consumers still use and a signal assistants and third parties often scrape or cite. Alias mismatch (e.g. cuisine or trade labels that do not line up with GBP) is a classic consistency failure. Yelp is not a map pin in the same way as GBP/Apple/Bing, but it belongs in outbound maps when we score “would an AI trust this entity’s type?” + +**Data aggregators / syndicators** sit underneath many of those surfaces. Companies such as **Data Axle** (local listings / formerly Infogroup-class syndication), **Localeze / TransUnion** digital business profiles, **Foursquare** Places (place graph / POI metadata), and similar players push NAP and rich fields out to search engines, directories, navigation apps, and assistants. Owners often never touch them directly — a “listing management” vendor or the platform itself does. For our product that means: Presence is not only “did you claim GBP?” It can also be “does the aggregator-fed copy of you disagree with the claim you just made?” Aggregators are **not** a ninth genre parent; they are a **distribution layer for facts**. Which aggregators we check in v1 (if any) is still open — but ignoring them entirely would understate how local data actually spreads. + +**schema.org’s LocalBusiness** types are an open vocabulary used widely on the web for structured data (the markup that helps search engines understand a page). That is the best spine for an AI-era product that also wants to publish clear web facts: owner-friendly genres inside our product, keyed to schema.org where they fit, optional NAICS when a statistical code helps, and **outbound maps** — translation tables — from our genres to Google, Apple, Bing, Yelp, and (where useful) aggregator category codes when we check presence or suggest fixes. + +We should not treat any single platform or aggregator list as our internal source of truth. They drift and they disagree. Building those maps ourselves is normal; nobody publishes an official multi-way concordance. On this branch, genre-pack work already sketches a **Core 3** field map (GBP richest → Apple mid → Bing thinnest); extend that pattern to Yelp aliases and aggregator feeds only where Presence scoring needs them. This taxonomy approach is a **hypothesis** until we score real businesses and see where the maps break. @@ -144,12 +150,12 @@ This doc’s product flow already assumes many owners **start themselves** (incl ## Decisions still open -Ty still needs to lock: which cluster pack we ship first; whether version one is web-only or also embeds in a chatbot; which providers feed the Presence score; how we measure Recommendability without overclaiming (simple heuristics versus live checks inside assistants); where the “email on file” for verification comes from; free versus paid; what never goes to a human versus when escalation is allowed; whether **veterinary** rides with healthcare/regulated or gets its own call if in scope (GBP research dump: separate Pets bucket, ~59 leaves, not folded into Health & Medical); and whether **v1 demand** is ads/self-start only, intermediate-first (tourism boards / chambers / partners), or both. +Ty still needs to lock: which cluster pack we ship first; whether version one is web-only or also embeds in a chatbot; which providers feed the Presence score (Core 3 GBP/Apple/Bing, plus Yelp and/or aggregators such as Data Axle / Localeze / Foursquare — or claim-only first); how we measure Recommendability without overclaiming (simple heuristics versus live checks inside assistants); where the “email on file” for verification comes from; free versus paid; what never goes to a human versus when escalation is allowed; whether **veterinary** rides with healthcare/regulated or gets its own call if in scope (GBP research dump: separate Pets bucket, ~59 leaves, not folded into Health & Medical); and whether **v1 demand** is ads/self-start only, intermediate-first (tourism boards / chambers / partners), or both. --- ## What we are treating as hypotheses -Until we score real businesses, treat these as educated bets, not finished truth: that eight top-level clusters plus a hybrid flag is the right split (including destination workshop separate from service-area trades, and beauty separate from healthcare); that schema.org plus outbound maps to Google, Apple, and Yelp GCIDs/aliases is the right labeling spine — not GBP’s flat leaf list as internal SoT; that two version-one packs are enough to prove cluster-specific rubrics; and that a web app beats an MCP-first distribution story for owners in the near term (revisit in about three months). +Until we score real businesses, treat these as educated bets, not finished truth: that eight top-level clusters plus a hybrid flag is the right split (including destination workshop separate from service-area trades, and beauty separate from healthcare); that schema.org plus outbound maps to Google, Apple, Bing, Yelp, and selected aggregators is the right labeling spine — not any one platform’s leaf list as internal SoT; that two version-one packs are enough to prove cluster-specific rubrics; and that a web app beats an MCP-first distribution story for owners in the near term (revisit in about three months). Nothing in this doc is locked until Ty says so. Amend this file when decisions land — do not start a second near-named document.