{"slug":"query-classification-content-mapper","title":"Query Classification and Content Mapper — Google Patent Taxonomy","tags":["seo","intent","query-classification","content-strategy","google-patents"],"agent_summary":"Classifies keywords using Google's patent-defined intent taxonomy, maps the ranking signal weights each query class triggers, and generates content strategy aligned to those signals. Grounded in Bill Slawski patent analysis.","trigger_phrases":["query classification","intent mapping","intent taxonomy","Google query types","patent-based intent","classify keywords","content mapper","query taxonomy"],"runnable":true,"markdown":"\n## Philosophy: Signals Before Content\n\nContent strategy fails when it ignores how Google weights ranking signals per query type. A 3,000-word guide is useless for a navigational query where brand signals and CTR history dominate. A thin product page fails for an informational query where topical authority and content depth control rank.\n\nGoogle's ranking is not one algorithm — it is a routing system. The query classifier determines WHICH signals get heavy weight before documents are scored. Your content must be built for the signals that matter for each query's class.\n\n## Patent Foundations\n\n| Patent | Role |\n|--------|------|\n| Query Classification Patent (2011) | Decision tree classifying queries into intent types, routing to different data partitions and signal weightings |\n| Hummingbird Patent (2013) | Full semantic units processed, not individual keywords; conversational queries understood as intent expressions |\n| Synthetic Queries Patent | Google generates artificial queries to understand what content SHOULD rank for |\n| Context Vectors Patent (2016) | Words mean different things in different contexts — same keyword in different topical contexts triggers different intent classes |\n| BERT QA Patent (2021) | Semantic similarity (not keyword matching) determines featured snippet selection |\n\n## The Query Classification Decision Tree\n\nFor each keyword, run through this sequence:\n\n```\nQUERY\n  |\n  +-- Contains location / \"near me\" / city?\n  |     YES --> LOCAL\n  |\n  +-- Contains brand name / specific website?\n  |     YES --> NAVIGATIONAL\n  |\n  +-- Contains buy / price / discount / order / schedule?\n  |     YES --> TRANSACTIONAL\n  |\n  +-- Contains best / review / vs / compare / top?\n  |     YES --> COMMERCIAL\n  |\n  +-- Contains question word / explanation-seeking language?\n  |     YES --> INFORMATIONAL\n  |\n  +-- Contains recent event / \"this week\" / news?\n         YES --> QDF (Query Deserves Freshness) override\n```\n\n## Signal Weight by Query Class\n\n| Query Class | Heavy Weight Signals | Light Weight Signals |\n|-------------|---------------------|---------------------|\n| LOCAL | Proximity, GMB completeness, review count/sentiment, local links, NAP consistency | General domain authority, topical breadth |\n| NAVIGATIONAL | Brand signals, CTR history, sitelinks, Knowledge Graph entity | Content depth, backlink count |\n| TRANSACTIONAL | Page speed, trust signals, reviews, schema (price/availability), CTR | Topical breadth, informational depth |\n| COMMERCIAL | Topical authority, review schema, comparison depth, E-E-A-T | Page speed, local signals |\n| INFORMATIONAL | Topical authority, content depth, featured snippet signals, E-E-A-T | Local signals, CTR from brand queries |\n| QDF | Freshness (recency), update frequency, news authority | Everything else — freshness overrides |\n\n## Content Strategy by Query Class\n\n**LOCAL:** One page per service + location combination. Include NAP, GMB embed, local schema, review aggregate. Optimize for 3-pack first, organic second.\n\n**NAVIGATIONAL:** Cannot be won for competitors' brand terms. For your own brand: ensure Homepage, About, and Contact pages have clear brand signals. Build Knowledge Panel entity through Wikidata + sameAs.\n\n**TRANSACTIONAL:** Product/service pages with price, availability, CTA above fold. Review schema required. Speed under 2.5s LCP required. Trust signals (BBB, license, insurance) visible.\n\n**COMMERCIAL:** Comparison content with clear differentiators. AggregateRating schema. Competitor analysis tables. E-E-A-T signals strong. Content depth exceeds top 5 results.\n\n**INFORMATIONAL:** Comprehensive coverage following topical map. Featured snippet targets via question-format H3s. Internal linking from outer to core section. Author bio with credentials.\n\n**QDF:** Time-stamped content with ISO 8601 dates. Re-publish with updates during active events. Index quickly via GSC URL inspection + sitemaps.\n\n## Ambiguous Queries\n\nSome queries trigger multiple intent classes simultaneously. Strategy for ambiguous queries:\n\n1. Check the SERP — what intent does Google currently resolve to? (Dominant intent = what most users want)\n2. Build content for the dominant intent first\n3. Add secondary intent content lower on the page (serve the minority without confusing the majority)\n4. Do NOT build a page that tries to serve all intents equally — it serves none well\n\n## Cross-References\n\n- `intent-analyzer` — the three-layer hidden intent framework\n- `serp-intent-analyzer` — SERP-level intent classification verification\n- `keyword-researcher` — generates keyword lists this skill classifies\n- `featured-snippet-optimizer` — optimizing informational query content for featured positions\n\n#seo-sop #seo #intent #query-classification #content-strategy #google-patents\n","html":"<h2>Philosophy: Signals Before Content</h2>\n<p>Content strategy fails when it ignores how Google weights ranking signals per query type. A 3,000-word guide is useless for a navigational query where brand signals and CTR history dominate. A thin product page fails for an informational query where topical authority and content depth control rank.</p>\n<p>Google's ranking is not one algorithm — it is a routing system. The query classifier determines WHICH signals get heavy weight before documents are scored. Your content must be built for the signals that matter for each query's class.</p>\n<h2>Patent Foundations</h2>\n<p>| Patent | Role |\n|--------|------|\n| Query Classification Patent (2011) | Decision tree classifying queries into intent types, routing to different data partitions and signal weightings |\n| Hummingbird Patent (2013) | Full semantic units processed, not individual keywords; conversational queries understood as intent expressions |\n| Synthetic Queries Patent | Google generates artificial queries to understand what content SHOULD rank for |\n| Context Vectors Patent (2016) | Words mean different things in different contexts — same keyword in different topical contexts triggers different intent classes |\n| BERT QA Patent (2021) | Semantic similarity (not keyword matching) determines featured snippet selection |</p>\n<h2>The Query Classification Decision Tree</h2>\n<p>For each keyword, run through this sequence:</p>\n<pre><code>QUERY\n  |\n  +-- Contains location / \"near me\" / city?\n  |     YES --> LOCAL\n  |\n  +-- Contains brand name / specific website?\n  |     YES --> NAVIGATIONAL\n  |\n  +-- Contains buy / price / discount / order / schedule?\n  |     YES --> TRANSACTIONAL\n  |\n  +-- Contains best / review / vs / compare / top?\n  |     YES --> COMMERCIAL\n  |\n  +-- Contains question word / explanation-seeking language?\n  |     YES --> INFORMATIONAL\n  |\n  +-- Contains recent event / \"this week\" / news?\n         YES --> QDF (Query Deserves Freshness) override\n</code></pre>\n<h2>Signal Weight by Query Class</h2>\n<p>| Query Class | Heavy Weight Signals | Light Weight Signals |\n|-------------|---------------------|---------------------|\n| LOCAL | Proximity, GMB completeness, review count/sentiment, local links, NAP consistency | General domain authority, topical breadth |\n| NAVIGATIONAL | Brand signals, CTR history, sitelinks, Knowledge Graph entity | Content depth, backlink count |\n| TRANSACTIONAL | Page speed, trust signals, reviews, schema (price/availability), CTR | Topical breadth, informational depth |\n| COMMERCIAL | Topical authority, review schema, comparison depth, E-E-A-T | Page speed, local signals |\n| INFORMATIONAL | Topical authority, content depth, featured snippet signals, E-E-A-T | Local signals, CTR from brand queries |\n| QDF | Freshness (recency), update frequency, news authority | Everything else — freshness overrides |</p>\n<h2>Content Strategy by Query Class</h2>\n<p><strong>LOCAL:</strong> One page per service + location combination. Include NAP, GMB embed, local schema, review aggregate. Optimize for 3-pack first, organic second.</p>\n<p><strong>NAVIGATIONAL:</strong> Cannot be won for competitors' brand terms. For your own brand: ensure Homepage, About, and Contact pages have clear brand signals. Build Knowledge Panel entity through Wikidata + sameAs.</p>\n<p><strong>TRANSACTIONAL:</strong> Product/service pages with price, availability, CTA above fold. Review schema required. Speed under 2.5s LCP required. Trust signals (BBB, license, insurance) visible.</p>\n<p><strong>COMMERCIAL:</strong> Comparison content with clear differentiators. AggregateRating schema. Competitor analysis tables. E-E-A-T signals strong. Content depth exceeds top 5 results.</p>\n<p><strong>INFORMATIONAL:</strong> Comprehensive coverage following topical map. Featured snippet targets via question-format H3s. Internal linking from outer to core section. Author bio with credentials.</p>\n<p><strong>QDF:</strong> Time-stamped content with ISO 8601 dates. Re-publish with updates during active events. Index quickly via GSC URL inspection + sitemaps.</p>\n<h2>Ambiguous Queries</h2>\n<p>Some queries trigger multiple intent classes simultaneously. Strategy for ambiguous queries:</p>\n<ol>\n<li>Check the SERP — what intent does Google currently resolve to? (Dominant intent = what most users want)</li>\n<li>Build content for the dominant intent first</li>\n<li>Add secondary intent content lower on the page (serve the minority without confusing the majority)</li>\n<li>Do NOT build a page that tries to serve all intents equally — it serves none well</li>\n</ol>\n<h2>Cross-References</h2>\n<ul>\n<li><code>intent-analyzer</code> — the three-layer hidden intent framework</li>\n<li><code>serp-intent-analyzer</code> — SERP-level intent classification verification</li>\n<li><code>keyword-researcher</code> — generates keyword lists this skill classifies</li>\n<li><code>featured-snippet-optimizer</code> — optimizing informational query content for featured positions</li>\n</ul>\n<p>#seo-sop #seo #intent #query-classification #content-strategy #google-patents</p>\n"}