{"number":"03","slug":"volumetric-seo-engine","filename":"03-VOLUMETRIC-SEO-ENGINE.md","title":"Volumetric SEO Engine","bytes":14860,"section_count":56,"purpose":"Combinatorial opportunity and pruning engine","outline":[{"heading":"03 — Volumetric SEO Engine","anchor":"03-volumetric-seo-engine","depth":1},{"heading":"1. Definition","anchor":"1-definition","depth":2},{"heading":"2. Opportunity dimensions","anchor":"2-opportunity-dimensions","depth":2},{"heading":"3. The theoretical opportunity volume","anchor":"3-the-theoretical-opportunity-volume","depth":2},{"heading":"4. Candidate generation","anchor":"4-candidate-generation","depth":2},{"heading":"5. Candidate normalization","anchor":"5-candidate-normalization","depth":2},{"heading":"6. Intent equivalence test","anchor":"6-intent-equivalence-test","depth":2},{"heading":"7. Boolean publication gates","anchor":"7-boolean-publication-gates","depth":2},{"heading":"8. Soft scoring model","anchor":"8-soft-scoring-model","depth":2},{"heading":"9. Redundancy compression","anchor":"9-redundancy-compression","depth":2},{"heading":"10. Page-volume governance","anchor":"10-page-volume-governance","depth":2},{"heading":"11. Volumetric content architecture","anchor":"11-volumetric-content-architecture","depth":2},{"heading":"12. LAKA volumetric expansion","anchor":"12-laka-volumetric-expansion","depth":2},{"heading":"13. Volumetric experiment design","anchor":"13-volumetric-experiment-design","depth":2},{"heading":"14. Feedback-driven generation","anchor":"14-feedback-driven-generation","depth":2},{"heading":"15. Output types","anchor":"15-output-types","depth":2},{"heading":"16. Minimum volumetric workflow","anchor":"16-minimum-volumetric-workflow","depth":2}],"sections":[{"heading":"03 — Volumetric SEO Engine","depth":1,"anchor":"03-volumetric-seo-engine","path":["03 — Volumetric SEO Engine"],"prose":[],"bullets":[],"blocks":[],"tables":[]},{"heading":"1. Definition","depth":2,"anchor":"1-definition","path":["03 — Volumetric SEO Engine","1. Definition"],"prose":["The Volumetric SEO Engine expands an opportunity across independent dimensions, then compresses that opportunity space into a small set of high-value canonical assets.","The engine is a **generator + constraint solver + portfolio allocator**."],"bullets":[],"blocks":[{"lang":"text","code":"VOLUME ≠ PAGE COUNT\n\nVOLUME\n=\nnumber of meaningful combinations inspected\n× number of evidence sources\n× number of viable solution forms\n× number of measurable learning cycles"},{"lang":"text","code":"INPUTS\n→ DIMENSIONAL EXPANSION\n→ NORMALIZATION\n→ INTENT CLUSTERING\n→ BOOLEAN GATES\n→ REDUNDANCY COMPRESSION\n→ VALUE SCORING\n→ PORTFOLIO SELECTION\n→ ASSET PRODUCTION\n→ OBSERVATION\n→ MODEL UPDATE"}],"tables":[]},{"heading":"2. Opportunity dimensions","depth":2,"anchor":"2-opportunity-dimensions","path":["03 — Volumetric SEO Engine","2. Opportunity dimensions"],"prose":[],"bullets":[],"blocks":[],"tables":[]},{"heading":"2.1 Business dimensions","depth":3,"anchor":"2-1-business-dimensions","path":["03 — Volumetric SEO Engine","2. Opportunity dimensions","2.1 Business dimensions"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"offer\nrevenue model\nmargin\ncapacity\nsales cycle\nqualification threshold\nretention value\nrisk\nstrategic priority"}],"tables":[]},{"heading":"2.2 Audience dimensions","depth":3,"anchor":"2-2-audience-dimensions","path":["03 — Volumetric SEO Engine","2. Opportunity dimensions","2.2 Audience dimensions"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"segment\nrole\nindustry\norganization size\nexperience\nproblem awareness\nsolution awareness\nurgency\nbudget\ngeography\nlanguage\ndevice/context\naccessibility need"}],"tables":[]},{"heading":"2.3 Task dimensions","depth":3,"anchor":"2-3-task-dimensions","path":["03 — Volumetric SEO Engine","2. Opportunity dimensions","2.3 Task dimensions"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"define\nlearn\ndiscover\ndiagnose\ncompare\ncalculate\nlocate\nverify\nplan\nimplement\ntroubleshoot\nbuy\nuse\nmaintain\nrenew\nrefer"}],"tables":[]},{"heading":"2.4 Intent dimensions","depth":3,"anchor":"2-4-intent-dimensions","path":["03 — Volumetric SEO Engine","2. Opportunity dimensions","2.4 Intent dimensions"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"informational\ncomparative\ncommercial investigation\ntransactional\nnavigational\nlocal\nsupport\nretention\nreputation"}],"tables":[]},{"heading":"2.5 Semantic dimensions","depth":3,"anchor":"2-5-semantic-dimensions","path":["03 — Volumetric SEO Engine","2. Opportunity dimensions","2.5 Semantic dimensions"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"parent concept\nsubtype\nsynonym\nentity\nattribute\nattribute value\nprocess\nprerequisite\nproblem\ncause\nconsequence\nsolution\nalternative\ncomparison\nobjection\nrisk\nevidence\nquestion"}],"tables":[]},{"heading":"2.6 Modifier dimensions","depth":3,"anchor":"2-6-modifier-dimensions","path":["03 — Volumetric SEO Engine","2. Opportunity dimensions","2.6 Modifier dimensions"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"who\nwhat\nwhere\nwhen\nwhy\nhow\nbest\ncost\nprice\ncheap/premium\nnear me\nreviews\nversus\nalternative\nfor [audience]\nwith [attribute]\nwithout [constraint]\nunder/over [value]\nbefore/after\ncurrent/year\nbeginner/advanced"}],"tables":[]},{"heading":"2.7 Asset dimensions","depth":3,"anchor":"2-7-asset-dimensions","path":["03 — Volumetric SEO Engine","2. Opportunity dimensions","2.7 Asset dimensions"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"service page\nproduct page\ncategory\nguide\ncomparison\ncalculator\ndiagnostic\ntemplate\nchecklist\ndirectory\nlocation page\ncase study\ndataset\nbenchmark\nglossary\nFAQ\nvideo\nimage series\ninteractive\nAPI/data feed"}],"tables":[]},{"heading":"2.8 Evidence dimensions","depth":3,"anchor":"2-8-evidence-dimensions","path":["03 — Volumetric SEO Engine","2. Opportunity dimensions","2.8 Evidence dimensions"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"firsthand experience\noriginal data\ncontrolled test\nfield observation\ncustomer evidence\nexpert review\ndocumented case study\nprimary-source citation\nmethodology\nscreenshots\ndemonstration\nlimitations"}],"tables":[]},{"heading":"2.9 Search-surface dimensions","depth":3,"anchor":"2-9-search-surface-dimensions","path":["03 — Volumetric SEO Engine","2. Opportunity dimensions","2.9 Search-surface dimensions"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"web results\nimages\nvideo\nlocal\nshopping/product\nnews\nDiscover\ngenerative AI features\nsite search\nthird-party marketplace"}],"tables":[]},{"heading":"2.10 Journey and conversion dimensions","depth":3,"anchor":"2-10-journey-and-conversion-dimensions","path":["03 — Volumetric SEO Engine","2. Opportunity dimensions","2.10 Journey and conversion dimensions"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"awareness → related content\nevaluation → tool/comparison\ndecision → assessment/demo/quote\ntransaction → purchase/signup\nuse → successful implementation\nretention → renewal/expansion\nadvocacy → review/referral/citation"}],"tables":[]},{"heading":"2.11 Time dimensions","depth":3,"anchor":"2-11-time-dimensions","path":["03 — Volumetric SEO Engine","2. Opportunity dimensions","2.11 Time dimensions"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"evergreen\nseasonal\nevent-driven\nnewly changed\nperiodic\ndecaying\nhistorical\nreal-time\nforecast"}],"tables":[]},{"heading":"2.12 Measurement dimensions","depth":3,"anchor":"2-12-measurement-dimensions","path":["03 — Volumetric SEO Engine","2. Opportunity dimensions","2.12 Measurement dimensions"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"query\npage\ncluster\ncountry\ndevice\nsearch appearance\naudience\noffer\nchange ID\ndate\ncohort\nvalue event"}],"tables":[]},{"heading":"3. The theoretical opportunity volume","depth":2,"anchor":"3-the-theoretical-opportunity-volume","path":["03 — Volumetric SEO Engine","3. The theoretical opportunity volume"],"prose":["A modest generator with:","creates:","This is not a publishing target. It demonstrates why SEO needs a grammar and constraint system. Without compression, “programmatic SEO” easily becomes duplication, thin content, maintenance debt, and measurement noise.","The desired outcome might be only 20, 100, or 1,000 canonical assets depending on the business—even though the system evaluated a much larger possibility space."],"bullets":[],"blocks":[{"lang":"text","code":"8 audience states\n× 12 tasks\n× 8 intents\n× 12 semantic node types\n× 10 modifier families\n× 12 asset formats\n× 6 search surfaces\n× 8 journey states\n× 8 evidence modes\n× 6 geographies\n× 6 next actions"},{"lang":"text","code":"15,288,238,080 theoretical combinations"}],"tables":[]},{"heading":"4. Candidate generation","depth":2,"anchor":"4-candidate-generation","path":["03 — Volumetric SEO Engine","4. Candidate generation"],"prose":[],"bullets":[],"blocks":[],"tables":[]},{"heading":"4.1 Candidate sentence","depth":3,"anchor":"4-1-candidate-sentence","path":["03 — Volumetric SEO Engine","4. Candidate generation","4.1 Candidate sentence"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"CANDIDATE\n=\nAUDIENCE\n× CONDITION\n× TASK\n× INTENT\n× CONCEPT\n× MODIFIER_SET\n× GEOGRAPHY\n× TIME_STATE\n× ASSET_FORM\n× EVIDENCE_MODE\n× NEXT_ACTION"}],"tables":[]},{"heading":"4.2 Generation pseudocode","depth":3,"anchor":"4-2-generation-pseudocode","path":["03 — Volumetric SEO Engine","4. Candidate generation","4.2 Generation pseudocode"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"FOR EACH approved offer:\n  FOR EACH plausible audience:\n    FOR EACH observed problem or desire:\n      FOR EACH task:\n        FOR EACH semantic relation:\n          GENERATE query hypotheses\n          ATTACH possible formats\n          ATTACH possible evidence\n          ATTACH next actions\n          ATTACH measurement plan"}],"tables":[]},{"heading":"4.3 Evidence enrichment","depth":3,"anchor":"4-3-evidence-enrichment","path":["03 — Volumetric SEO Engine","4. Candidate generation","4.3 Evidence enrichment"],"prose":["Each hypothesis must be enriched with observations:","The more sources agree, the higher the demand confidence."],"bullets":[],"blocks":[{"lang":"text","code":"first-party query data\nOR customer language\nOR result-page evidence\nOR competitor visibility\nOR sales/support evidence\nOR market data\nOR paid-search evidence"}],"tables":[]},{"heading":"5. Candidate normalization","depth":2,"anchor":"5-candidate-normalization","path":["03 — Volumetric SEO Engine","5. Candidate normalization"],"prose":["Before clustering:","Do not erase meaningful distinctions. “Audit” as a noun, “audit software,” and “hire an auditor” may belong to different tasks."],"bullets":[],"blocks":[{"lang":"text","code":"lowercase for comparison\nnormalize punctuation\nnormalize singular/plural where meaning is stable\nexpand or resolve abbreviations\nmap synonyms to concepts\nidentify named entities\nidentify geography and time\nidentify modifiers\ndetect language\ndetect likely sense\nextract task verb\nextract transaction state\nattach exclusions"}],"tables":[]},{"heading":"6. Intent equivalence test","depth":2,"anchor":"6-intent-equivalence-test","path":["03 — Volumetric SEO Engine","6. Intent equivalence test"],"prose":["Calculate a conceptual equivalence vector:"],"bullets":[],"blocks":[{"lang":"text","code":"EQUIVALENCE =\nsense_match\n+ task_match\n+ result_type_match\n+ answer_structure_match\n+ audience_state_match\n+ next_action_match\n+ current_SERP_overlap"}],"tables":[]},{"heading":"Merge gate","depth":3,"anchor":"merge-gate","path":["03 — Volumetric SEO Engine","6. Intent equivalence test","Merge gate"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"IF sense_match = true\nAND task_match = true\nAND answer_structure_compatible = true\nAND next_action_compatible = true\nAND separate_page_value = low\nTHEN assign to same cluster."}],"tables":[]},{"heading":"Split gate","depth":3,"anchor":"split-gate","path":["03 — Volumetric SEO Engine","6. Intent equivalence test","Split gate"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"IF sense differs\nOR task differs\nOR result class differs\nOR local/product inventory differs\nOR legal context differs\nOR combined answer harms usability\nTHEN create separate cluster candidate."}],"tables":[]},{"heading":"Test gate","depth":3,"anchor":"test-gate","path":["03 — Volumetric SEO Engine","6. Intent equivalence test","Test gate"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"IF evidence is ambiguous\nTHEN:\n  keep one provisional cluster\n  AND observe query/page behavior\n  OR run a controlled asset-format test\n  BEFORE multiplying pages."}],"tables":[]},{"heading":"7. Boolean publication gates","depth":2,"anchor":"7-boolean-publication-gates","path":["03 — Volumetric SEO Engine","7. Boolean publication gates"],"prose":["A candidate proceeds only if it passes all hard gates."],"bullets":[],"blocks":[{"lang":"text","code":"APPROVE\n=\nDEMAND\nAND DISTINCTNESS\nAND BUSINESS VALUE\nAND INFORMATION ADVANTAGE\nAND TECHNICAL FEASIBILITY\nAND MAINTAINABILITY\nAND MEASURABILITY\nAND POLICY / ETHICAL COMPLIANCE"}],"tables":[]},{"heading":"Demand gate","depth":3,"anchor":"demand-gate","path":["03 — Volumetric SEO Engine","7. Boolean publication gates","Demand gate"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"PASS IF:\nobserved impressions\nOR customer evidence\nOR sales/support frequency\nOR stable result ecosystem\nOR defensible emerging-demand thesis"}],"tables":[]},{"heading":"Distinctness gate","depth":3,"anchor":"distinctness-gate","path":["03 — Volumetric SEO Engine","7. Boolean publication gates","Distinctness gate"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"PASS IF:\nthe candidate owns a distinct task\nOR needs a materially different answer\nOR has real local/product data\nOR requires a different conversion path"}],"tables":[]},{"heading":"Value gate","depth":3,"anchor":"value-gate","path":["03 — Volumetric SEO Engine","7. Boolean publication gates","Value gate"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"PASS IF:\ndirect conversion value\nOR assisted conversion value\nOR retention value\nOR authority value\nOR strategic learning value"}],"tables":[]},{"heading":"Information-advantage gate","depth":3,"anchor":"information-advantage-gate","path":["03 — Volumetric SEO Engine","7. Boolean publication gates","Information-advantage gate"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"PASS IF at least one:\noriginal experience\nOR proprietary data\nOR better methodology\nOR better utility\nOR stronger evidence\nOR clearer decision support\nOR unique local coverage\nOR better accessibility"}],"tables":[]},{"heading":"Maintainability gate","depth":3,"anchor":"maintainability-gate","path":["03 — Volumetric SEO Engine","7. Boolean publication gates","Maintainability gate"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"PASS IF:\nowner exists\nAND refresh triggers are defined\nAND data can be kept accurate\nAND total approved volume fits capacity"}],"tables":[]},{"heading":"Measurement gate","depth":3,"anchor":"measurement-gate","path":["03 — Volumetric SEO Engine","7. Boolean publication gates","Measurement gate"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"PASS IF:\nprimary outcome\nAND baseline\nAND change ID\nAND observation method\nAND decision rule\nare defined."}],"tables":[]},{"heading":"8. Soft scoring model","depth":2,"anchor":"8-soft-scoring-model","path":["03 — Volumetric SEO Engine","8. Soft scoring model"],"prose":["Candidates that pass the gates are prioritized.","Use a 0–5 rating or calibrated probability for each factor.","Avoid zero in a multiplicative score by using a minimum floor such as 0.2 for uncertain but nonzero factors, or use a weighted log model."],"bullets":[],"blocks":[{"lang":"text","code":"VALUE NUMERATOR =\nDemandConfidence\n× BusinessFit\n× TaskValue\n× InformationAdvantage\n× ConversionValue\n× Attainability\n× ReusePotential\n× LearningValue\n\nCOST DENOMINATOR =\nProductionEffort\n× TechnicalRisk\n× MaintenanceBurden\n× TimeToLearning\n× OpportunityCost\n\nPRIORITY SCORE =\nVALUE NUMERATOR / COST DENOMINATOR"}],"tables":[]},{"heading":"Confidence adjustment","depth":3,"anchor":"confidence-adjustment","path":["03 — Volumetric SEO Engine","8. Soft scoring model","Confidence adjustment"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"ADJUSTED SCORE =\nPRIORITY SCORE\n× EvidenceConfidence\n× MeasurementConfidence"}],"tables":[]},{"heading":"Existing-asset multiplier","depth":3,"anchor":"existing-asset-multiplier","path":["03 — Volumetric SEO Engine","8. Soft scoring model","Existing-asset multiplier"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"IF existing URL has:\nimpressions\nOR links\nOR conversions\nOR stable indexing\nOR strong internal position\nTHEN multiply by ExistingSignalFactor."}],"tables":[]},{"heading":"9. Redundancy compression","depth":2,"anchor":"9-redundancy-compression","path":["03 — Volumetric SEO Engine","9. Redundancy compression"],"prose":["The goal is **maximum demand coverage with minimum canonical assets**."],"bullets":[],"blocks":[],"tables":[]},{"heading":"Compression steps","depth":3,"anchor":"compression-steps","path":["03 — Volumetric SEO Engine","9. Redundancy compression","Compression steps"],"prose":["1. Group lexical variants.","2. Merge same-sense queries.","3. Group same-task queries.","4. inspect result-format compatibility.","5. assign one canonical owner.","6. place remaining questions as:","- sections;","- FAQs;","- supporting assets;","- exclusions;","- future experiments."],"bullets":["Group lexical variants.","Merge same-sense queries.","Group same-task queries.","inspect result-format compatibility.","assign one canonical owner.","place remaining questions as:"],"blocks":[],"tables":[]},{"heading":"Compression ratio","depth":3,"anchor":"compression-ratio","path":["03 — Volumetric SEO Engine","9. Redundancy compression","Compression ratio"],"prose":["A high ratio can be healthy when it reflects disciplined clustering. It is unhealthy if valid distinct tasks are being forced into bloated pages."],"bullets":[],"blocks":[{"lang":"text","code":"COMPRESSION RATIO =\ngenerated candidates / approved canonical assets"}],"tables":[]},{"heading":"Coverage ratio","depth":3,"anchor":"coverage-ratio","path":["03 — Volumetric SEO Engine","9. Redundancy compression","Coverage ratio"],"prose":["Optimize both compression and coverage—not one alone."],"bullets":[],"blocks":[{"lang":"text","code":"VALUABLE DEMAND COVERAGE =\nvalue-weighted approved cluster demand\n/\nvalue-weighted validated demand"}],"tables":[]},{"heading":"10. Page-volume governance","depth":2,"anchor":"10-page-volume-governance","path":["03 — Volumetric SEO Engine","10. Page-volume governance"],"prose":[],"bullets":[],"blocks":[],"tables":[]},{"heading":"Capacity formula","depth":3,"anchor":"capacity-formula","path":["03 — Volumetric SEO Engine","10. Page-volume governance","Capacity formula"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"SUSTAINABLE PAGE VOLUME\n≤\n(editorial capacity × quality throughput × refresh capacity)\n/\n(average maintenance burden × volatility)"}],"tables":[]},{"heading":"Scale rules","depth":3,"anchor":"scale-rules","path":["03 — Volumetric SEO Engine","10. Page-volume governance","Scale rules"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"IF approved_page_count exceeds maintenance capacity\nTHEN:\n  raise value threshold\n  OR consolidate clusters\n  OR automate data quality\n  OR reduce geography/product scope\n  OR stage publication.\n\nIF a template produces mostly repeated text\nTHEN the template is not a sufficient information product.\n\nIF local pages lack unique local proof\nTHEN consolidate to a broader service-area asset\nOR collect valid local data first.\n\nIF generated assets cannot be individually measured\nTHEN use representative cohorts\nAND prevent uncontrolled expansion.\n\nIF pages decay faster than they can be refreshed\nTHEN reduce scope\nOR change the asset class."}],"tables":[]},{"heading":"11. Volumetric content architecture","depth":2,"anchor":"11-volumetric-content-architecture","path":["03 — Volumetric SEO Engine","11. Volumetric content architecture"],"prose":[],"bullets":[],"blocks":[],"tables":[]},{"heading":"11.1 Parent–subtype volume","depth":3,"anchor":"11-1-parent-subtype-volume","path":["03 — Volumetric SEO Engine","11. Volumetric content architecture","11.1 Parent–subtype volume"],"prose":["Example:"],"bullets":[],"blocks":[{"lang":"text","code":"PARENT\n→ SUBTYPE\n→ ATTRIBUTE\n→ VALUE\n→ TASK"},{"lang":"text","code":"WEB DESIGN\n→ ECOMMERCE WEB DESIGN\n→ PLATFORM\n→ SHOPIFY\n→ COMPARE / HIRE / PRICE / MIGRATE"}],"tables":[]},{"heading":"11.2 Entity–relation volume","depth":3,"anchor":"11-2-entity-relation-volume","path":["03 — Volumetric SEO Engine","11. Volumetric content architecture","11.2 Entity–relation volume"],"prose":["Examples:"],"bullets":[],"blocks":[{"lang":"text","code":"ENTITY A\n→ RELATION\n→ ENTITY B"},{"lang":"text","code":"WORDPRESS → COMPARED_WITH → WEBFLOW\nWCAG → APPLIES_TO → ECOMMERCE\nCALGARY → CONTAINS → SERVICE AREAS\nPAGE SPEED → AFFECTS → CONVERSION"}],"tables":[]},{"heading":"11.3 Problem–solution volume","depth":3,"anchor":"11-3-problem-solution-volume","path":["03 — Volumetric SEO Engine","11. Volumetric content architecture","11.3 Problem–solution volume"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"AUDIENCE\n→ PROBLEM\n→ CAUSE\n→ DIAGNOSTIC\n→ SOLUTION\n→ PROOF\n→ OFFER"}],"tables":[]},{"heading":"11.4 Journey volume","depth":3,"anchor":"11-4-journey-volume","path":["03 — Volumetric SEO Engine","11. Volumetric content architecture","11.4 Journey volume"],"prose":["One cluster system should cover the journey without forcing a linear user path."],"bullets":[],"blocks":[{"lang":"text","code":"PROBLEM AWARENESS\n→ DIAGNOSIS\n→ OPTIONS\n→ COMPARISON\n→ COST\n→ PROOF\n→ SELECTION\n→ IMPLEMENTATION\n→ MAINTENANCE"}],"tables":[]},{"heading":"11.5 Format volume","depth":3,"anchor":"11-5-format-volume","path":["03 — Volumetric SEO Engine","11. Volumetric content architecture","11.5 Format volume"],"prose":["For each approved task, test alternate information products:","The best format is the one that completes the task and creates measurable value—not the one easiest to publish."],"bullets":[],"blocks":[{"lang":"text","code":"article\nOR table\nOR video\nOR calculator\nOR template\nOR map\nOR dataset\nOR interactive"}],"tables":[]},{"heading":"12. LAKA volumetric expansion","depth":2,"anchor":"12-laka-volumetric-expansion","path":["03 — Volumetric SEO Engine","12. LAKA volumetric expansion"],"prose":["For every approved opportunity, generate five change classes.","Then apply the ten internal variables to each level:","Then attach the fourteen change descriptors:","This is a volumetric **analysis space**, not a requirement to execute 700 actions."],"bullets":[],"blocks":[{"lang":"text","code":"5 change levels × 10 internal variables = 50-cell intervention map"},{"lang":"text","code":"50 cells × 14 descriptors = 700 analytical observations per opportunity"}],"tables":[{"headers":["Level","Expansion question","Typical candidates"],"rows":[["Baseline","What is happening now?","measurement, inventory, diagnosis"],["Minor","What small reversible change can improve response?","title, intro, CTA, link"],["Major","What richer answer or format would serve the task?","rewrite, tool, video, evidence"],["Structural","What relationships or systems cause the limitation?","merge, graph, template, pipeline"],["Paradigm","What new solution class could redefine the result?","data product, diagnostic, agent, benchmark"]]}]},{"heading":"13. Volumetric experiment design","depth":2,"anchor":"13-volumetric-experiment-design","path":["03 — Volumetric SEO Engine","13. Volumetric experiment design"],"prose":[],"bullets":[],"blocks":[],"tables":[]},{"heading":"Variation dimensions","depth":3,"anchor":"variation-dimensions","path":["03 — Volumetric SEO Engine","13. Volumetric experiment design","Variation dimensions"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"query cluster\ntitle proposition\nsearch snippet\ndirect-answer style\ninformation depth\nformat\nevidence\nvisuals\ninternal links\nnext action\noffer\ntechnical implementation"}],"tables":[]},{"heading":"Controlled generation","depth":3,"anchor":"controlled-generation","path":["03 — Volumetric SEO Engine","13. Volumetric experiment design","Controlled generation"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"FOR EACH high-value cluster:\n  GENERATE minor, major, structural, paradigm hypotheses\n  SCORE by mechanism, value, risk, reversibility, learning\n  SELECT a non-confounded test\n  ASSIGN change_id\n  OBSERVE primary metric + guardrails\n  UPDATE priors"}],"tables":[]},{"heading":"Rule against combinatorial confusion","depth":3,"anchor":"rule-against-combinatorial-confusion","path":["03 — Volumetric SEO Engine","13. Volumetric experiment design","Rule against combinatorial confusion"],"prose":[],"bullets":[],"blocks":[{"lang":"text","code":"IF multiple high-impact variables change simultaneously\nAND the goal is causal learning\nTHEN split the change\nOR explicitly classify it as a package test.\n\nIF the goal is simply recovery\nAND delay has high business cost\nTHEN a package intervention may be valid,\nbut causal attribution will be lower."}],"tables":[]},{"heading":"14. Feedback-driven generation","depth":2,"anchor":"14-feedback-driven-generation","path":["03 — Volumetric SEO Engine","14. Feedback-driven generation"],"prose":["The engine updates its weights based on outcomes."],"bullets":[],"blocks":[{"lang":"text","code":"IF a task family produces qualified value repeatedly\nTHEN increase its business-fit prior.\n\nIF a format improves task completion across clusters\nTHEN increase its format prior for similar tasks.\n\nIF a query family generates traffic but poor qualification\nTHEN lower its value prior\nAND inspect audience/intent classification.\n\nIF generated local pages decay or duplicate\nTHEN tighten local distinctness gates.\n\nIF original data earns relevant citations\nTHEN increase evidence and reuse scores for related assets.\n\nIF a paradigm asset creates branded demand\nTHEN create supporting and conversion pathways around it."}],"tables":[]},{"heading":"15. Output types","depth":2,"anchor":"15-output-types","path":["03 — Volumetric SEO Engine","15. Output types"],"prose":["The engine should generate these outputs, not merely pages:"],"bullets":[],"blocks":[{"lang":"text","code":"opportunity inventory\nsemantic graph\nintent clusters\ncanonical registry\npage specifications\ninternal-link graph\ntechnical requirements\nevidence backlog\nauthority campaigns\nexperiment queue\nmeasurement plan\nrefresh calendar\nretirement/merge queue"}],"tables":[]},{"heading":"16. Minimum volumetric workflow","depth":2,"anchor":"16-minimum-volumetric-workflow","path":["03 — Volumetric SEO Engine","16. Minimum volumetric workflow"],"prose":["This produces scale through disciplined thought, not indiscriminate publishing."],"bullets":[],"blocks":[{"lang":"text","code":"1. Generate 100–1,000 candidates internally.\n2. Normalize and cluster them.\n3. Apply eight hard publication gates.\n4. Score survivors.\n5. Select the top portfolio under capacity.\n6. Assign one canonical owner per dominant intent.\n7. generate five LAKA intervention levels.\n8. execute the smallest intervention capable of affecting the diagnosed mechanism.\n9. measure business and diagnostic outcomes.\n10. update the generator."}],"tables":[]}]}