# SEO LAKA Complete Guide **Version 1.0** This single file combines the human-readable core of the package. Machine-readable files, standalone templates, code, and the technical appendix remain separate. ## Contents 1. [01 — SEO LAKA Grammar](#01--seo-laka-grammar) 2. [02 — LAKA SEO Strategy Guide](#02--laka-seo-strategy-guide) 3. [03 — Volumetric SEO Engine](#03--volumetric-seo-engine) 4. [04 — IF / ELSE / AND / OR SEO Rulebook](#04--if--else--and--or-seo-rulebook) 5. [05 — Measurement and Experiment System](#05--measurement-and-experiment-system) 6. [06 — Audit and Execution SOPs](#06--audit-and-execution-sops) 7. [07 — Page and Cluster Templates](#07--page-and-cluster-templates) 8. [08 — Agent Operating Prompt](#08--agent-operating-prompt) 9. [09 — Implementation Backlog](#09--implementation-backlog) 10. [10 — Course Crosswalk and Sources](#10--course-crosswalk-and-sources) 11. [Worked Example — WebDevCalgary.com](#worked-example--webdevcalgarycom) --- --- # 01 — SEO LAKA Grammar ## 1. Purpose A grammar defines the valid parts of a language and the rules for combining them. The SEO LAKA Grammar defines: - what an SEO object is; - which properties must be attached to it; - which relationships can connect objects; - which logical operations create valid decisions; - how a strategy changes across the five LAKA levels; - how every action becomes measurable. SEO work is treated as a language that produces **retrieval systems, information products, customer journeys, and business outcomes**. --- ## 2. The seven layers of the language ```text LAYER 1 — BUSINESS LANGUAGE Goal, value, offer, margin, risk, capacity LAYER 2 — AUDIENCE LANGUAGE Segment, role, awareness, sophistication, urgency, constraints LAYER 3 — SEMANTIC LANGUAGE Concept, entity, attribute, relation, question, query, intent, task LAYER 4 — DOCUMENT LANGUAGE Asset, page type, answer structure, evidence, media, canonical destination LAYER 5 — GRAPH LANGUAGE Internal link, external citation, parent, child, sibling, hub, pathway LAYER 6 — RETRIEVAL LANGUAGE Discover, crawl, render, canonicalize, index, retrieve, display LAYER 7 — OUTCOME LANGUAGE Impression, click, task completion, lead, sale, margin, retention, learning ``` A valid strategy must connect all seven layers. A keyword list that does not connect to an audience, asset, graph position, and outcome is an incomplete sentence. --- ## 3. Primitive object classes ### 3.1 Business objects | Primitive | Meaning | Required properties | |---|---|---| | `BUSINESS` | Organization receiving value | model, geography, capacity | | `GOAL` | Desired business state | metric, baseline, target, horizon | | `OFFER` | Exchange presented to a user | audience, price/value, margin | | `VALUE_EVENT` | Event that produces measurable value | event name, value, qualification rule | | `CONSTRAINT` | Limit on valid strategies | budget, policy, capacity, risk | | `RESOURCE` | Asset available to execute | people, data, technology, time | ### 3.2 Audience objects | Primitive | Meaning | Required properties | |---|---|---| | `AUDIENCE` | A meaningful user segment | need, language, geography | | `PERSONA` | Operational representation of a segment | context, goal, barriers | | `JOURNEY_STATE` | Relationship state with the business | awareness, evaluation, decision, use, retention | | `PROBLEM` | Undesired state | severity, urgency, frequency | | `DESIRE` | Desired state | value, urgency, evidence of demand | | `TASK` | What the user is trying to accomplish | verb, object, completion condition | | `INTENT` | Why the task is being performed now | informational, comparative, transactional, navigational, local, support | ### 3.3 Semantic objects | Primitive | Meaning | Example | |---|---|---| | `CONCEPT` | General idea or class | web design | | `ENTITY` | Distinct named thing | Calgary, WordPress, Google | | `PARENT` | Broader concept | digital marketing | | `SUBTYPE` | Narrower type | ecommerce web design | | `SYNONYM` | Near-equivalent expression | website designer / web designer | | `VARIANT` | Morphological or orthographic form | website / web site | | `ATTRIBUTE` | Descriptive dimension | price, speed, accessibility | | `VALUE` | Attribute state | under $5,000, fast, WCAG conformant | | `RELATION` | Typed connection | service LOCATED-IN Calgary | | `QUESTION` | Explicit information gap | how much does a website cost? | | `QUERY` | Observed search expression | Calgary web design prices | | `QUERY_CLUSTER` | Queries sharing one dominant task | cost-intent cluster | | `EXCLUSION` | Wrong sense, audience, or task | jobs, salary, course | ### 3.4 Document objects | Primitive | Meaning | |---|---| | `ASSET` | Any retrievable content or tool | | `CANONICAL_ASSET` | Intended primary destination for an intent cluster | | `SUPPORTING_ASSET` | Asset answering an adjacent task and supporting a canonical asset | | `PAGE_TYPE` | Service, product, category, guide, comparison, calculator, template, location, case study, glossary, FAQ | | `FORMAT` | Text, table, video, image, tool, dataset, map, interactive, downloadable | | `EVIDENCE` | Firsthand experience, data, test, citation, case study, demonstration | | `NEXT_ACTION` | Logical transition after the task is served | | `SEARCH_APPEARANCE` | Web result, image, video, local result, product result, rich result, generative citation | ### 3.5 Graph objects | Primitive | Meaning | |---|---| | `NODE` | A page, entity, cluster, or asset in a graph | | `EDGE` | A typed connection between nodes | | `INTERNAL_LINK` | Crawlable relationship between owned pages | | `EXTERNAL_LINK` | Citation or navigation to another site | | `BACKLINK` | External edge pointing to an owned asset | | `HUB` | Page that organizes a coherent topic or task family | | `PATH` | Ordered sequence from entry to task completion or conversion | | `ORPHAN` | Important page without a useful internal path | | `CANONICAL_SET` | Duplicate or near-duplicate URLs represented by one preferred URL | ### 3.6 Retrieval states ```text DISCOVERED → FETCHED → RENDERED → CANONICALIZED → INDEXED → RETRIEVED → DISPLAYED → VISITED → COMPLETED → CONVERTED ``` These are separate states. “Indexed” must never be used as a synonym for all of them. --- ## 4. Relation vocabulary Use typed relations rather than a flat bag of keywords. ```text IS_A PART_OF HAS_ATTRIBUTE HAS_VALUE LOCATED_IN USED_BY REQUIRES CAUSES PREVENTS SOLVES PRODUCES MEASURED_BY COMPARED_WITH ALTERNATIVE_TO COMPATIBLE_WITH INCOMPATIBLE_WITH EVIDENCED_BY AUTHORED_BY OFFERED_BY PRECEDES FOLLOWS LINKS_TO SUPPORTS CANONICALIZES_TO CONVERTS_TO RETAINS EXCLUDES ``` Examples: ```text WEB_DESIGN IS_A PROFESSIONAL_SERVICE WEB_DESIGN HAS_ATTRIBUTE PRICE CALGARY_WEB_DESIGN LOCATED_IN CALGARY WCAG_AUDIT PREVENTS ACCESSIBILITY_RISK CASE_STUDY EVIDENCED_BY FIRST_PARTY_ANALYTICS COST_GUIDE SUPPORTS CALGARY_WEB_DESIGN_SERVICE FILTER_URL CANONICALIZES_TO CATEGORY_URL ORGANIC_SESSION CONVERTS_TO QUALIFIED_ASSESSMENT ``` The relation determines the needed content structure. `COMPARED_WITH` often requires a comparison table. `HOW_TO` requires an ordered procedure. `LOCATED_IN` may require local evidence. `EVIDENCED_BY` requires visible proof. --- ## 5. Logical operators ### 5.1 AND — mandatory conjunction Use `AND` when all conditions are necessary. ```text PUBLISH IF demand_is_evidenced AND intent_is_distinct AND business_fit_is_positive AND information_advantage_exists AND asset_is_maintainable AND measurement_is_installed ``` A failed mandatory condition blocks publication or sends the candidate to research. ### 5.2 OR — valid alternatives Use `OR` when several different forms can satisfy the same requirement. ```text EVIDENCE = firsthand_experience OR original_data OR reproducible_test OR qualified_expert_review OR documented_case_study ``` `OR` does not mean “include everything.” It means choose one or more valid alternatives according to the task. ### 5.3 XOR — exactly one Use `XOR` when only one choice can be canonical. ```text FOR EACH dominant_intent_cluster: existing_url XOR new_url XOR merged_url MUST be the intended canonical destination ``` ### 5.4 NOT — explicit exclusion ```text TARGET_CLUSTER = candidate_queries NOT jobs NOT salaries NOT unrelated_brand NOT wrong_geography NOT wrong_language ``` ### 5.5 IF / THEN / ELSE — branching decision ```text IF same_task AND same_answer_structure AND same_result_format AND same_next_action THEN merge_into_one_canonical_asset ELSE split_or_test ``` ### 5.6 FOR EACH — controlled scale ```text FOR EACH approved_location AND FOR EACH approved_service GENERATE candidate_location_service_page ``` This creates candidates, not automatic publication. ### 5.7 UNTIL — optimization loop ```text REPEAT diagnose → change → observe → decide UNTIL: target_is_reached OR expected_value_falls_below_cost OR constraint_is_triggered ``` ### 5.8 AT LEAST / AT MOST / EXACTLY ```text AT_LEAST 1 useful internal link points to every priority canonical page AT_MOST 1 dominant intent owns a canonical URL EXACTLY 1 primary KPI governs an experiment ``` --- ## 6. The canonical SEO sentence ```text SEO_SENTENCE ::= GOAL FOR AUDIENCE IN JOURNEY_STATE UNDER CONDITIONS SEEKING TASK WITH INTENT ABOUT CONCEPT_OR_ENTITY USING QUERY_CLUSTER SERVED_BY CANONICAL_ASSET IN FORMAT SUPPORTED_BY EVIDENCE CONNECTED_BY GRAPH LEADING_TO NEXT_ACTION MEASURED_BY PRIMARY_METRIC GUARDED_BY CONSTRAINTS ``` ### Compact notation ```text G → A:C:T:I:Q → D:F:E → L → N → M | X ``` Where: - `G` = goal - `A` = audience - `C` = conditions - `T` = task - `I` = intent - `Q` = query cluster - `D` = document - `F` = format - `E` = evidence - `L` = link graph - `N` = next action - `M` = metric - `X` = constraints Example: ```text Increase qualified assessments FOR Calgary small-business owners UNDER active website redesign consideration SEEKING compare-agencies WITH commercial-investigation intent ABOUT Calgary web design providers USING the agency-comparison query cluster SERVED BY /calgary-web-design-companies/ IN a scored comparison + decision guide SUPPORTED BY disclosed criteria + firsthand audits CONNECTED BY links from cost, process, and case-study nodes LEADING TO a website assessment MEASURED BY qualified assessment contribution margin GUARDED BY neutrality, disclosure, and lead-quality constraints. ``` --- ## 7. Query-cluster grammar A query is decomposed into semantic slots: ```text QUERY = [ACTOR?] + [TASK_VERB?] + [OBJECT] + [RELATION?] + [ATTRIBUTE?] + [ATTRIBUTE_VALUE?] + [GEOGRAPHY?] + [TIME?] + [FORMAT?] + [TRANSACTION_MODIFIER?] ``` Examples: ```text small business + hire + web designer + in + Calgary compare + WordPress + with + Webflow + for + consultants calculate + website cost + in + Canada + 2026 fix + slow WordPress site + without + changing host ``` ### Query normalization ```text NORMALIZED_QUERY_CLUSTER = same sense AND same dominant task AND compatible answer structure AND compatible journey state AND compatible next action ``` Synonyms, word order, pluralization, abbreviations, and stems are usually lexical variants within one cluster—not separate pages. ### Split rule Split a cluster when one or more of the following is materially different: ```text different task OR different sense OR different audience constraint OR different geography with real local evidence OR different product/service OR different expected result type OR different answer structure OR different conversion path OR different legal/risk context ``` ### Merge rule Merge pages when: ```text same dominant task AND substantial result overlap AND no independently valuable answer AND combined asset improves completeness AND redirect/canonical migration risk is acceptable ``` --- ## 8. Page grammar ```text PAGE = PROMISE + DIRECT_ANSWER + TASK_STRUCTURE + EVIDENCE + DECISION_SUPPORT + NEXT_ACTION + MACHINE_SIGNALS + GRAPH_CONNECTIONS ``` ### Required page clauses 1. **Promise:** What task will this page help complete? 2. **Direct answer:** Give the essential answer early. 3. **Task structure:** Use the form the task requires. 4. **Evidence:** Show why the answer should be trusted. 5. **Decision support:** Resolve trade-offs, objections, and edge cases. 6. **Next action:** Offer the next logical state, not an unrelated conversion. 7. **Machine signals:** Clear title, headings, canonical, status, metadata, and structured data when eligible. 8. **Graph connections:** Link to prerequisite, supporting, alternative, and next-step nodes. ### Format-selection grammar ```text IF intent = compare THEN use table OR matrix OR scored decision framework IF intent = calculate THEN use calculator OR formula + worked examples IF intent = locate THEN use map OR directory OR location page with verifiable local evidence IF intent = learn_process THEN use ordered steps + prerequisites + checkpoints IF intent = diagnose THEN use symptom → cause → test → remedy decision tree IF intent = choose THEN use criteria → options → trade-offs → recommendation IF intent = verify THEN use claim → evidence → source → limitation IF intent = transact THEN use offer → proof → scope → price/process → action IF intent = explore THEN use hub → categories → paths → filters ``` --- ## 9. Internal-link grammar An internal link is a typed edge, not decoration. ```text INTERNAL_LINK = SOURCE_NODE + RELATION + DESCRIPTIVE_ANCHOR + TARGET_NODE + USER_REASON ``` Valid edge types: ```text prerequisite_of definition_of example_of evidence_for comparison_to alternative_to step_before step_after supports converts_to location_variant_of service_variant_of ``` Rules: ```text IF target_is_priority THEN at_least_one crawlable_contextual_internal_link MUST exist IF source_context_does_not_help_user_understand_target THEN do_not_add_link IF anchor_is_generic AND a descriptive phrase is natural THEN replace anchor IF multiple_pages_compete_for_same_anchor_and_intent THEN inspect canonical ownership before adding more links ``` --- ## 10. The five LAKA change levels ### 10.1 Baseline The system is observed without changing its structure. ```text OBJECT: existing query, page, cluster, or site ACTION: measure, inventory, classify OUTCOME: trustworthy baseline ``` Typical SEO work: - verify analytics and Search Console; - map queries to URLs; - record technical states; - calculate current funnel and business value; - identify uncertainty and missing data. ### 10.2 Minor change Surface elements change while the object and mechanism stay mostly stable. ```text Examples: title wording meta description opening answer anchor text image compression small internal-link addition CTA wording ``` Primary question: ```text Can a low-cost, reversible change improve response without changing intent? ``` ### 10.3 Major change The document or campaign is substantially improved, but its role remains stable. ```text Examples: rewrite the page add original evidence change format from prose to comparison table build a video or calculator into the page consolidate weak sections launch a focused outreach campaign ``` ### 10.4 Structural change Relationships, architecture, ownership, or workflow change. ```text Examples: merge cannibalizing pages redesign cluster architecture change templates repair faceted navigation move from isolated pages to a hub graph connect CRM value data to SEO reporting ``` ### 10.5 Paradigm change The class of solution changes. ```text Examples: replace a blog post with a free diagnostic tool replace a static directory with a verified data product turn service research into a benchmark index build a proprietary dataset competitors cannot reproduce make the website agent-operable, not merely readable create demand rather than only capture existing demand ``` ### Escalation rule ```text START at Baseline. IF diagnosis is high-confidence AND minor intervention can affect the mechanism THEN test Minor. ELSE IF page value exists AND information or format is inadequate THEN apply Major. ELSE IF multiple assets or systems create the failure THEN apply Structural. ELSE IF the result class itself cannot satisfy the task OR a new information product creates a defensible advantage THEN test Paradigm. ``` --- ## 11. LAKA internal-variable sentence Every proposed change must fill all ten variables. | Variable | Required question | |---|---| | Object | What exactly is being changed? | | Conditions | Under what audience, device, location, time, and competitive conditions? | | Actions | What intervention will occur? | | Tools | What mechanisms execute and observe it? | | Resources | What data, people, systems, budget, and evidence are needed? | | Outcomes | What immediate and downstream states should change? | | Feedback | What evidence determines continue, revise, reverse, or escalate? | | Constraints | What legal, quality, technical, capacity, and brand limits apply? | | Value | For whom is value created, and how is it quantified? | | Failure Mode | How can this intervention fail or create harm? | Formal form: ```text CHANGE = OBJECT UNDER CONDITIONS PERFORMS ACTION USING TOOLS WITH RESOURCES TO PRODUCE OUTCOMES OBSERVED_BY FEEDBACK LIMITED_BY CONSTRAINTS CREATING VALUE WHILE MONITORING FAILURE_MODE ``` --- ## 12. Fourteen-variable change descriptor Attach these variables to every experiment or program. | Variable | Suggested states | |---|---| | Magnitude | negligible, small, medium, large, transformational | | Rate | immediate, fast, gradual, slow, unknown | | Direction | positive, negative, mixed, neutral | | Scope | element, page, cluster, template, site, market | | Depth | copy, behavior, document, architecture, business model | | Duration | transient, campaign, persistent, permanent | | Frequency | once, periodic, event-driven, continuous | | Acceleration | decaying, linear, compounding, volatile | | Variability | low, moderate, high, unknown | | Detectability | direct, proxy, modeled, latent | | Reversibility | easy, moderate, difficult, irreversible | | Propagation | isolated, linked, template-wide, site-wide, ecosystem | | Amplification | none, internal graph, external citations, brand, network | | Accumulation | none, episodic, stock-building, compounding | Compact change signature: ```text ΔSEO[ M=medium, R=gradual, D=positive, S=cluster, Dp=architecture, Du=persistent, F=once, A=compounding, V=moderate, De=direct, Re=moderate, P=linked, Am=internal_graph, Ac=stock_building ] ``` --- ## 13. Validity grammar A candidate is valid only when: ```text VALID_CANDIDATE = DEMAND_EVIDENCE AND DISTINCT_TASK AND BUSINESS_FIT AND UNIQUE_OR_SUPERIOR_VALUE AND TECHNICAL_FEASIBILITY AND MAINTAINABILITY AND MEASURABILITY AND POLICY_COMPLIANCE ``` A page is valid only when: ```text VALID_PAGE = ONE_DOMINANT_INTENT AND ONE_INTENDED_CANONICAL AND TASK_APPROPRIATE_FORMAT AND VISIBLE_EVIDENCE AND CLEAR_NEXT_ACTION AND CRAWLABLE_PATH AND INDEXABLE_WHEN_INTENDED AND NO_MATERIAL_DUPLICATION ``` An experiment is valid only when: ```text VALID_EXPERIMENT = HYPOTHESIS AND MECHANISM AND PRIMARY_METRIC AND BASELINE AND TREATMENT_SCOPE AND OBSERVATION_WINDOW AND DECISION_RULE AND GUARDRAILS ``` --- ## 14. Anti-grammar: invalid constructions ```text keyword + keyword + keyword → page ``` Invalid because it omits audience, task, intent, value, format, and measurement. ```text publish every location × service permutation ``` Invalid unless every approved page has distinct demand, accurate local evidence, useful content, maintainability, and a valid canonical role. ```text rankings increased → SEO succeeded ``` Invalid unless the increase leads to valuable, qualified outcomes without unacceptable guardrail damage. ```text tool score improved → user experience improved ``` Invalid unless field data or user/business outcomes confirm the mechanism. ```text more pages OR more links OR more schema = better ``` Invalid. Volume without fit can increase cost, duplication, risk, and measurement noise. --- ## 15. The shortest complete command ```text /seo goal="" audience="" task="" intent="" cluster="" canonical="" format="" evidence="" next="" metric="" laka="" logic="" ``` This command can be used by a human, automation, or agent. --- # 02 — LAKA SEO Strategy Guide ## 1. Strategy thesis The best SEO strategy is not “produce more content.” It is to construct a measurable system that repeatedly does five things: 1. identifies valuable unresolved demand; 2. assigns each meaningful task to one intended canonical asset; 3. creates a superior information product for that task; 4. makes the asset discoverable, interpretable, credible, and connected; 5. learns from business outcomes and reallocates effort. The operating loop is: ```text OBSERVE → MODEL → GENERATE → FILTER → BUILD → CONNECT → PROMOTE → MEASURE → LEARN → ESCALATE OR STOP ``` --- ## 2. North-star model ```text INCREMENTAL ORGANIC CONTRIBUTION MARGIN = incremental qualified organic conversions × average contribution margin − attributable SEO operating cost ``` Rankings, impressions, clicks, links, and indexed pages are diagnostic states. They are not the final business result. Use a small executive scorecard: 1. Incremental organic contribution margin 2. Qualified organic conversions 3. Value-weighted non-brand clicks 4. Value-weighted target-cluster visibility 5. Eligible canonical coverage Everything else belongs to diagnostic dashboards. --- ## 3. Stage 0 — Define the business grammar Before keyword research, define: ```text WHO receives value? WHAT outcome matters? WHICH offer converts that value? WHAT counts as qualified? WHAT is one conversion worth in contribution margin? WHAT capacity limits growth? WHAT outcomes must not worsen? ``` ### Business object card ```text Business: Offer: Audience: Geography: Average contribution margin: Qualified conversion event: Capacity per month: Primary constraint: Primary guardrail: ``` ### IF / ELSE rules ```text IF value_event is undefined THEN do not use traffic as the north-star metric. IF contribution_margin is unknown THEN use a provisional value band AND mark all ROI outputs as forecasts. IF fulfillment_capacity is constrained THEN prioritize query clusters with higher lead quality OR higher margin rather than maximum traffic. IF several offers serve different audiences THEN create separate value models ELSE aggregate reporting will hide quality differences. ``` --- ## 4. Stage 1 — Establish measurement and eligibility ### Required measurement chain ```text QUERY → IMPRESSION → CLICK → LANDING PAGE → TASK EVENT → NEXT ACTION → QUALIFIED LEAD → SALE → MARGIN ``` ### Required technical chain ```text DISCOVERY → CRAWL → RENDER → CANONICAL SELECTION → INDEX → RETRIEVAL → SEARCH APPEARANCE ``` ### Baseline outputs - Search Console property and data access - analytics with defined organic conversion events - CRM or commerce value linkage - canonical URL inventory - crawl/index state inventory - query-to-URL table - branded/non-branded classification - country/device/search-appearance dimensions - baseline date and change log ### Gate ```text IF priority_pages cannot be measured OR conversion events cannot be trusted THEN measurement repair outranks content production. ``` --- ## 5. Stage 2 — Build the audience–task map Do not begin with a keyword tool. Begin with the user’s world. ### Audience dimensions ```text role industry organization size experience problem awareness solution awareness urgency budget risk tolerance geography language device/context accessibility needs ``` ### Task families ```text LEARN DEFINE DISCOVER DIAGNOSE COMPARE CALCULATE LOCATE VERIFY PLAN IMPLEMENT TROUBLESHOOT BUY USE MAINTAIN RENEW REFER ``` ### Journey states ```text UNAWARE PROBLEM_AWARE SOLUTION_AWARE OPTION_EVALUATION DECISION IMPLEMENTATION USE RETENTION ADVOCACY ``` The funnel is a graph, not a one-way pipe. Users can enter, leave, return, skip stages, or move backward. ### Output Create an audience–task matrix: | Audience | Condition | Task | Intent | Journey state | Value event | |---|---|---|---|---|---| ### Gate ```text IF a query cannot be associated with a plausible audience and task THEN classify it as uncertain AND do not publish from it yet. ``` --- ## 6. Stage 3 — Build the semantic demand graph ### 6.1 Start with concept families For every offer, map: ```text PARENT CONCEPTS SUBTYPES SYNONYMS / PARAPHRASES ENTITIES ATTRIBUTES ATTRIBUTE VALUES PROCESSES PREREQUISITES PROBLEMS CAUSES CONSEQUENCES SOLUTIONS ALTERNATIVES COMPARISONS OBJECTIONS RISKS LOCATIONS TIME STATES EVIDENCE TYPES QUESTIONS ``` ### 6.2 Add observed demand Sources may include: - Search Console queries; - customer calls and emails; - site search; - sales objections; - support tickets; - search suggestions and result patterns; - competitor visibility; - forums and communities; - first-party surveys; - paid-search terms; - analytics and CRM outcomes. ### 6.3 Separate semantic similarity from intent equivalence Two phrases can be semantically close but require different pages. Two phrases can look different but belong to one task. ```text "web design Calgary" "Calgary website designer" ``` Likely one service intent. ```text "web design Calgary" "how much does web design cost in Calgary" ``` Related topic, different task and likely different document role. ### 6.4 Cluster test ```text SAME PAGE IF: same sense AND same dominant task AND same answer structure AND same expected result class AND compatible next action SPLIT IF: different task OR different decision stage OR different local/product eligibility OR different format is necessary OR the combined answer would become confusing ``` ### Output A canonical intent registry: | Cluster ID | Representative query | Task | Intent | Variants | Exclusions | Intended URL | Status | |---|---|---|---|---|---|---|---| --- ## 7. Stage 4 — Quantify opportunities ### Opportunity scoring model ```text OPPORTUNITY SCORE = ( demand evidence × business fit × task-value fit × information advantage × conversion value × attainability × confidence × reuse potential ) ÷ ( effort × risk × maintenance burden × time to learning ) ``` Use 0–5 values or calibrated probabilities. Do not pretend the result is exact; it is a transparent prioritization model. ### Existing-opportunity multiplier Add a multiplier when an existing page already has: - impressions; - positions near useful visibility; - links; - conversions; - brand recognition; - stable indexing; - strong internal graph position. ```text IF existing_asset_has_signal THEN prefer improve/merge/reposition BEFORE creating a new asset, unless intent ownership is fundamentally wrong. ``` ### Priority bands ```text P0 — eligibility or measurement failure blocking value P1 — existing high-value opportunity with low/moderate effort P2 — core commercial or decision cluster P3 — supporting informational or authority asset P4 — experimental or speculative demand P5 — reject, defer, or monitor ``` --- ## 8. Stage 5 — Choose the information product A page should be designed as a product that completes a task. ### Information-product selector | Task | Preferred product forms | |---|---| | Define | concise definition, examples, boundaries | | Learn | guide, lesson, demonstration, video | | Compare | table, matrix, benchmark, decision tree | | Calculate | calculator, estimator, formula, worksheet | | Diagnose | checklist, test, decision tree, audit | | Locate | verified directory, map, location page | | Plan | roadmap, template, calendar, framework | | Implement | SOP, code, configuration, download | | Verify | evidence review, source map, methodology | | Choose | scored criteria, trade-offs, recommendations | | Buy | service/product page, proof, scope, process, action | | Maintain | monitoring guide, alert, checklist, dashboard | ### Information advantage Approve at least one defensible advantage: ```text firsthand experience OR proprietary data OR original test OR better synthesis OR better visualization OR better interaction OR more current verified information OR stronger local evidence OR clearer decision support OR useful tool/template OR accessibility advantage OR faster task completion ``` ### Gate ```text IF the proposed page merely restates common information AND has no meaningful experience, evidence, utility, or synthesis advantage THEN redesign the asset OR reject it. ``` --- ## 9. Stage 6 — Write the page specification Every page brief must define: ```text Cluster ID Audience Task Intent Journey state Canonical URL Page type Expected result formats Direct answer Required entities and relations Required attributes Evidence plan Media plan Internal links in Internal links out Next action Primary metric Guardrails Refresh trigger Owner ``` ### On-page logic ```text IF title accurately represents the task AND distinguishes the result AND creates a truthful reason to click THEN test it against current CTR expectations. IF title change improves clicks BUT lowers qualified conversion rate materially THEN revert or refine. IF page has impressions but poor rank THEN diagnose intent, format, information advantage, authority, and internal graph BEFORE repeating keywords. IF page ranks but does not convert THEN inspect audience quality, answer-to-offer continuity, and next action. IF page converts but lacks impressions THEN prioritize discoverability, internal links, authority, and search appearance. ``` --- ## 10. Stage 7 — Design the internal information graph ### Four edge classes 1. **Understanding edges** — definition, prerequisite, evidence, example 2. **Choice edges** — comparison, alternative, trade-off 3. **Journey edges** — next step, assessment, service, product 4. **Authority edges** — supporting research to core asset ### Hub rule Create a hub when it helps a user choose a path across a coherent set of tasks. Do not create a hub solely to insert links. ### Supporting-asset rule ```text IF an adjacent task has independent demand AND can provide a complete useful answer AND supports a valuable canonical asset THEN create supporting_asset AND link contextually toward the relevant core asset. ELSE include the answer as a section OR do not create it. ``` ### Orphan rule ```text IF page_is_priority AND no crawlable internal link exists THEN add at least one contextually useful link OR remove the page from the priority set. ``` --- ## 11. Stage 8 — Build external evidence and prominence Authority is not only “link quantity.” Treat it as independent evidence and graph prominence. ### Authority program components ```text LINKABLE_REASON + RELEVANT_PROSPECT + EVIDENCE_ASSET + RELATIONSHIP / OUTREACH + PLACEMENT + RETENTION + BUSINESS IMPACT ``` ### Linkable reasons - original data; - benchmark; - free tool; - template; - definitive reference; - newsworthy change; - expert collaboration; - unique local resource; - visual explanation; - case study; - correction or replacement for a broken resource. ### Rules ```text IF a page is purely commercial AND difficult to cite THEN create a genuinely useful evidence asset OR supporting resource that can earn attention without disguising its purpose. IF a prospect is irrelevant OR placement is paid/sponsored without appropriate treatment OR outreach claim is misleading THEN reject the opportunity. IF acquired link disappears THEN classify cause AND recover only when the relationship and value remain valid. ``` Measure qualified referring domains, target-page lift, branded demand, assisted conversion, and retained placements—not tool scores alone. --- ## 12. Stage 9 — Technical eligibility and search appearance ### Technical priority order ```text 1. Accessibility to users and crawlers 2. Correct status and destination 3. Rendered main content 4. Canonical ownership 5. Index eligibility 6. Internal discovery 7. Duplicate/facet control 8. Sitemap freshness 9. Mobile and real-user performance 10. Structured data eligibility 11. International/local correctness ``` ### Technical decision rules ```text IF URL should appear in Search THEN it must be accessible AND return an appropriate successful response AND expose indexable content AND not carry conflicting exclusion signals. IF page must disappear for users and search THEN use removal or redirect logic appropriate to the business case, not robots.txt alone. IF duplicate URLs must remain accessible THEN use coherent canonical signals AND consistent internal links AND sitemap preference. IF content is generated by JavaScript THEN validate rendered content and crawlable links. IF structured data type is not relevant to visible page content THEN do not add it. IF Core Web Vitals are poor THEN prioritize fixes by real-user exposure and business impact rather than chasing a perfect laboratory score. ``` --- ## 13. Stage 10 — Match the next action to the journey ### Transition grammar ```text UNAWARE → understand problem PROBLEM_AWARE → explore solution class SOLUTION_AWARE → compare approaches OPTION_EVALUATION → inspect proof, scope, cost DECISION → transact or contact USE → implement successfully RETENTION → renew, expand, repeat ADVOCACY → review, refer, cite ``` ### Nudge rule ```text NEXT_ACTION must be: logically adjacent AND proportionate to trust AND useful without coercion AND measurable ``` Examples: ```text guide → related guide OR diagnostic comparison → calculator OR assessment calculator → saved result OR consultation service page → qualification form customer guide → support action OR upgrade case study → relevant service page ``` --- ## 14. Stage 11 — Experiment with LAKA ### Experiment ladder ```text BASELINE: observe and diagnose MINOR: change presentation or a single local variable MAJOR: change the asset’s answer, evidence, or format STRUCTURAL: change cluster ownership, templates, graph, or data flow PARADIGM: change the solution class or create a new information product ``` ### Escalation logic ```text IF baseline data is unreliable THEN do not escalate; repair measurement. IF a minor test fails AND diagnosis indicates a content/format problem THEN move to Major. IF several pages share the same failure THEN move to Structural. IF competitors all solve the wrong problem OR no existing result class can complete the task THEN consider Paradigm. IF expected incremental value < expected cost THEN stop, defer, or monitor. ``` --- ## 15. Stage 12 — Continuous allocation At a fixed review cadence: 1. update demand and value data; 2. detect query, URL, and conversion shifts; 3. recalculate opportunity scores; 4. separate noise from sustained change; 5. continue, expand, revise, reverse, or retire; 6. record what the system learned. ### Portfolio allocation A balanced portfolio may include: ```text 40% existing-page and conversion improvements 25% core commercial/decision assets 15% supporting authority assets 10% technical/structural work 10% paradigm experiments ``` This is a starting heuristic, not a universal rule. Reallocate according to measured marginal value, constraints, and learning velocity. --- ## 16. Failure diagnosis tree ```text NO IMPRESSIONS? → discovery / crawl / index / demand / cluster mismatch IMPRESSIONS BUT LOW VISIBILITY? → intent / format / information value / internal graph / authority VISIBILITY BUT LOW CTR? → title / snippet / result type / brand / mismatch / SERP crowding CLICKS BUT LOW TASK COMPLETION? → weak answer / poor format / slow or confusing experience / wrong query TASK COMPLETION BUT LOW NEXT ACTION? → journey discontinuity / weak offer / wrong CTA / trust gap LEADS BUT LOW QUALIFICATION? → wrong audience / misleading promise / broad intent / form design SALES BUT LOW MARGIN OR RETENTION? → offer economics / fulfillment / customer fit / expectation mismatch METRICS IMPROVE BUT BUSINESS DOES NOT? → proxy optimization; redefine the primary outcome ``` --- ## 17. Strategy completion test The strategy is ready only when every priority cluster answers: ```text Who is the user? What are they trying to do? Why now? What observed demand supports it? Which queries represent the task? Which single asset owns the intent? What form best completes the task? What makes the asset meaningfully better? How will users and crawlers find it? What independent evidence supports it? What is the next logical action? What event creates business value? How will success and failure be distinguished? What is the LAKA escalation path? ``` --- # 03 — Volumetric SEO Engine ## 1. Definition The Volumetric SEO Engine expands an opportunity across independent dimensions, then compresses that opportunity space into a small set of high-value canonical assets. ```text VOLUME ≠ PAGE COUNT VOLUME = number of meaningful combinations inspected × number of evidence sources × number of viable solution forms × number of measurable learning cycles ``` The engine is a **generator + constraint solver + portfolio allocator**. ```text INPUTS → DIMENSIONAL EXPANSION → NORMALIZATION → INTENT CLUSTERING → BOOLEAN GATES → REDUNDANCY COMPRESSION → VALUE SCORING → PORTFOLIO SELECTION → ASSET PRODUCTION → OBSERVATION → MODEL UPDATE ``` --- ## 2. Opportunity dimensions ### 2.1 Business dimensions ```text offer revenue model margin capacity sales cycle qualification threshold retention value risk strategic priority ``` ### 2.2 Audience dimensions ```text segment role industry organization size experience problem awareness solution awareness urgency budget geography language device/context accessibility need ``` ### 2.3 Task dimensions ```text define learn discover diagnose compare calculate locate verify plan implement troubleshoot buy use maintain renew refer ``` ### 2.4 Intent dimensions ```text informational comparative commercial investigation transactional navigational local support retention reputation ``` ### 2.5 Semantic dimensions ```text parent concept subtype synonym entity attribute attribute value process prerequisite problem cause consequence solution alternative comparison objection risk evidence question ``` ### 2.6 Modifier dimensions ```text who what where when why how best cost price cheap/premium near me reviews versus alternative for [audience] with [attribute] without [constraint] under/over [value] before/after current/year beginner/advanced ``` ### 2.7 Asset dimensions ```text service page product page category guide comparison calculator diagnostic template checklist directory location page case study dataset benchmark glossary FAQ video image series interactive API/data feed ``` ### 2.8 Evidence dimensions ```text firsthand experience original data controlled test field observation customer evidence expert review documented case study primary-source citation methodology screenshots demonstration limitations ``` ### 2.9 Search-surface dimensions ```text web results images video local shopping/product news Discover generative AI features site search third-party marketplace ``` ### 2.10 Journey and conversion dimensions ```text awareness → related content evaluation → tool/comparison decision → assessment/demo/quote transaction → purchase/signup use → successful implementation retention → renewal/expansion advocacy → review/referral/citation ``` ### 2.11 Time dimensions ```text evergreen seasonal event-driven newly changed periodic decaying historical real-time forecast ``` ### 2.12 Measurement dimensions ```text query page cluster country device search appearance audience offer change ID date cohort value event ``` --- ## 3. The theoretical opportunity volume A modest generator with: ```text 8 audience states × 12 tasks × 8 intents × 12 semantic node types × 10 modifier families × 12 asset formats × 6 search surfaces × 8 journey states × 8 evidence modes × 6 geographies × 6 next actions ``` creates: ```text 15,288,238,080 theoretical combinations ``` 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. --- ## 4. Candidate generation ### 4.1 Candidate sentence ```text CANDIDATE = AUDIENCE × CONDITION × TASK × INTENT × CONCEPT × MODIFIER_SET × GEOGRAPHY × TIME_STATE × ASSET_FORM × EVIDENCE_MODE × NEXT_ACTION ``` ### 4.2 Generation pseudocode ```text FOR EACH approved offer: FOR EACH plausible audience: FOR EACH observed problem or desire: FOR EACH task: FOR EACH semantic relation: GENERATE query hypotheses ATTACH possible formats ATTACH possible evidence ATTACH next actions ATTACH measurement plan ``` ### 4.3 Evidence enrichment Each hypothesis must be enriched with observations: ```text first-party query data OR customer language OR result-page evidence OR competitor visibility OR sales/support evidence OR market data OR paid-search evidence ``` The more sources agree, the higher the demand confidence. --- ## 5. Candidate normalization Before clustering: ```text lowercase for comparison normalize punctuation normalize singular/plural where meaning is stable expand or resolve abbreviations map synonyms to concepts identify named entities identify geography and time identify modifiers detect language detect likely sense extract task verb extract transaction state attach exclusions ``` Do not erase meaningful distinctions. “Audit” as a noun, “audit software,” and “hire an auditor” may belong to different tasks. --- ## 6. Intent equivalence test Calculate a conceptual equivalence vector: ```text EQUIVALENCE = sense_match + task_match + result_type_match + answer_structure_match + audience_state_match + next_action_match + current_SERP_overlap ``` ### Merge gate ```text IF sense_match = true AND task_match = true AND answer_structure_compatible = true AND next_action_compatible = true AND separate_page_value = low THEN assign to same cluster. ``` ### Split gate ```text IF sense differs OR task differs OR result class differs OR local/product inventory differs OR legal context differs OR combined answer harms usability THEN create separate cluster candidate. ``` ### Test gate ```text IF evidence is ambiguous THEN: keep one provisional cluster AND observe query/page behavior OR run a controlled asset-format test BEFORE multiplying pages. ``` --- ## 7. Boolean publication gates A candidate proceeds only if it passes all hard gates. ```text APPROVE = DEMAND AND DISTINCTNESS AND BUSINESS VALUE AND INFORMATION ADVANTAGE AND TECHNICAL FEASIBILITY AND MAINTAINABILITY AND MEASURABILITY AND POLICY / ETHICAL COMPLIANCE ``` ### Demand gate ```text PASS IF: observed impressions OR customer evidence OR sales/support frequency OR stable result ecosystem OR defensible emerging-demand thesis ``` ### Distinctness gate ```text PASS IF: the candidate owns a distinct task OR needs a materially different answer OR has real local/product data OR requires a different conversion path ``` ### Value gate ```text PASS IF: direct conversion value OR assisted conversion value OR retention value OR authority value OR strategic learning value ``` ### Information-advantage gate ```text PASS IF at least one: original experience OR proprietary data OR better methodology OR better utility OR stronger evidence OR clearer decision support OR unique local coverage OR better accessibility ``` ### Maintainability gate ```text PASS IF: owner exists AND refresh triggers are defined AND data can be kept accurate AND total approved volume fits capacity ``` ### Measurement gate ```text PASS IF: primary outcome AND baseline AND change ID AND observation method AND decision rule are defined. ``` --- ## 8. Soft scoring model Candidates that pass the gates are prioritized. Use a 0–5 rating or calibrated probability for each factor. ```text VALUE NUMERATOR = DemandConfidence × BusinessFit × TaskValue × InformationAdvantage × ConversionValue × Attainability × ReusePotential × LearningValue COST DENOMINATOR = ProductionEffort × TechnicalRisk × MaintenanceBurden × TimeToLearning × OpportunityCost PRIORITY SCORE = VALUE NUMERATOR / COST DENOMINATOR ``` 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. ### Confidence adjustment ```text ADJUSTED SCORE = PRIORITY SCORE × EvidenceConfidence × MeasurementConfidence ``` ### Existing-asset multiplier ```text IF existing URL has: impressions OR links OR conversions OR stable indexing OR strong internal position THEN multiply by ExistingSignalFactor. ``` --- ## 9. Redundancy compression The goal is **maximum demand coverage with minimum canonical assets**. ### Compression steps 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. ### Compression ratio ```text COMPRESSION RATIO = generated candidates / approved canonical assets ``` A high ratio can be healthy when it reflects disciplined clustering. It is unhealthy if valid distinct tasks are being forced into bloated pages. ### Coverage ratio ```text VALUABLE DEMAND COVERAGE = value-weighted approved cluster demand / value-weighted validated demand ``` Optimize both compression and coverage—not one alone. --- ## 10. Page-volume governance ### Capacity formula ```text SUSTAINABLE PAGE VOLUME ≤ (editorial capacity × quality throughput × refresh capacity) / (average maintenance burden × volatility) ``` ### Scale rules ```text IF approved_page_count exceeds maintenance capacity THEN: raise value threshold OR consolidate clusters OR automate data quality OR reduce geography/product scope OR stage publication. IF a template produces mostly repeated text THEN the template is not a sufficient information product. IF local pages lack unique local proof THEN consolidate to a broader service-area asset OR collect valid local data first. IF generated assets cannot be individually measured THEN use representative cohorts AND prevent uncontrolled expansion. IF pages decay faster than they can be refreshed THEN reduce scope OR change the asset class. ``` --- ## 11. Volumetric content architecture ### 11.1 Parent–subtype volume ```text PARENT → SUBTYPE → ATTRIBUTE → VALUE → TASK ``` Example: ```text WEB DESIGN → ECOMMERCE WEB DESIGN → PLATFORM → SHOPIFY → COMPARE / HIRE / PRICE / MIGRATE ``` ### 11.2 Entity–relation volume ```text ENTITY A → RELATION → ENTITY B ``` Examples: ```text WORDPRESS → COMPARED_WITH → WEBFLOW WCAG → APPLIES_TO → ECOMMERCE CALGARY → CONTAINS → SERVICE AREAS PAGE SPEED → AFFECTS → CONVERSION ``` ### 11.3 Problem–solution volume ```text AUDIENCE → PROBLEM → CAUSE → DIAGNOSTIC → SOLUTION → PROOF → OFFER ``` ### 11.4 Journey volume ```text PROBLEM AWARENESS → DIAGNOSIS → OPTIONS → COMPARISON → COST → PROOF → SELECTION → IMPLEMENTATION → MAINTENANCE ``` One cluster system should cover the journey without forcing a linear user path. ### 11.5 Format volume For each approved task, test alternate information products: ```text article OR table OR video OR calculator OR template OR map OR dataset OR interactive ``` The best format is the one that completes the task and creates measurable value—not the one easiest to publish. --- ## 12. LAKA volumetric expansion For every approved opportunity, generate five change classes. | Level | Expansion question | Typical candidates | |---|---|---| | 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 | Then apply the ten internal variables to each level: ```text 5 change levels × 10 internal variables = 50-cell intervention map ``` Then attach the fourteen change descriptors: ```text 50 cells × 14 descriptors = 700 analytical observations per opportunity ``` This is a volumetric **analysis space**, not a requirement to execute 700 actions. --- ## 13. Volumetric experiment design ### Variation dimensions ```text query cluster title proposition search snippet direct-answer style information depth format evidence visuals internal links next action offer technical implementation ``` ### Controlled generation ```text FOR EACH high-value cluster: GENERATE minor, major, structural, paradigm hypotheses SCORE by mechanism, value, risk, reversibility, learning SELECT a non-confounded test ASSIGN change_id OBSERVE primary metric + guardrails UPDATE priors ``` ### Rule against combinatorial confusion ```text IF multiple high-impact variables change simultaneously AND the goal is causal learning THEN split the change OR explicitly classify it as a package test. IF the goal is simply recovery AND delay has high business cost THEN a package intervention may be valid, but causal attribution will be lower. ``` --- ## 14. Feedback-driven generation The engine updates its weights based on outcomes. ```text IF a task family produces qualified value repeatedly THEN increase its business-fit prior. IF a format improves task completion across clusters THEN increase its format prior for similar tasks. IF a query family generates traffic but poor qualification THEN lower its value prior AND inspect audience/intent classification. IF generated local pages decay or duplicate THEN tighten local distinctness gates. IF original data earns relevant citations THEN increase evidence and reuse scores for related assets. IF a paradigm asset creates branded demand THEN create supporting and conversion pathways around it. ``` --- ## 15. Output types The engine should generate these outputs, not merely pages: ```text opportunity inventory semantic graph intent clusters canonical registry page specifications internal-link graph technical requirements evidence backlog authority campaigns experiment queue measurement plan refresh calendar retirement/merge queue ``` --- ## 16. Minimum volumetric workflow ```text 1. Generate 100–1,000 candidates internally. 2. Normalize and cluster them. 3. Apply eight hard publication gates. 4. Score survivors. 5. Select the top portfolio under capacity. 6. Assign one canonical owner per dominant intent. 7. generate five LAKA intervention levels. 8. execute the smallest intervention capable of affecting the diagnosed mechanism. 9. measure business and diagnostic outcomes. 10. update the generator. ``` This produces scale through disciplined thought, not indiscriminate publishing. --- # 04 — IF / ELSE / AND / OR SEO Rulebook ## Purpose This rulebook converts SEO judgment into explicit, auditable decisions. It contains **144 rules** in twelve domains. The machine-readable version is in `rules/seo-laka-rules.yaml`. ## Operator semantics ```text IF begins a condition. THEN specifies the action when the condition is true. ELSE specifies the valid fallback when the condition is false. AND requires every connected condition. OR permits one or more valid alternatives. NOT excludes a state or candidate. XOR requires exactly one choice. BEFORE establishes dependency order. UNTIL establishes a bounded feedback loop. AT_LEAST sets a minimum. EXACTLY_ONE assigns unique ownership or a single decision. ``` ## Rule execution order Rules may conflict. Resolve them in this order: ```text 1. Safety, law, privacy, and policy 2. User value and factual accuracy 3. Technical eligibility and canonical correctness 4. Business value and constraints 5. Intent fit and information quality 6. Measurement and learning 7. Efficiency and scale 8. Cosmetic optimization ``` ## Hard-gate pattern ```text IF all mandatory conditions pass THEN execute or advance the candidate ELSE route to research, consolidation, repair, deferral, or rejection ``` ## Rules ## 1. Business Value ### BIZ-001 — Define value before volume ```text IF the program has no defined qualified business event THEN define the event, qualification rule, owner, and estimated contribution value before optimizing traffic ELSE use the existing qualified event as the primary business outcome ``` **Operators:** IF · THEN · ELSE · AND **LAKA level(s):** Baseline **Primary metric:** measurement completeness **Guardrail:** Do not substitute sessions or ranking counts for value. **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### BIZ-002 — Traffic is diagnostic, not the north star ```text IF organic traffic increases AND qualified conversions or margin do not THEN diagnose intent quality, audience fit, next-action continuity, and attribution ELSE continue scaling only while downstream value and guardrails remain healthy ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Baseline, Major **Primary metric:** incremental organic contribution margin **Guardrail:** lead quality, sales capacity, refund rate **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### BIZ-003 — Separate forecasts from actuals ```text IF search volume, CTR, conversion, or revenue is estimated THEN label the output as a forecast and record every assumption ELSE use observed query, conversion, revenue, and margin data ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** forecast error **Guardrail:** confidence interval, source age **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### BIZ-004 — Respect fulfillment capacity ```text IF expected qualified demand exceeds delivery or sales capacity THEN prioritize higher-margin, higher-fit clusters OR increase capacity before expanding volume ELSE optimize for profitable demand growth ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** contribution margin per capacity unit **Guardrail:** response time, customer satisfaction **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### BIZ-005 — Model offers separately ```text IF different offers have materially different audiences, margins, sales cycles, or qualification rules THEN assign separate value models and cluster portfolios ELSE a shared model may be used with explicit segment dimensions ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** value by offer **Guardrail:** cross-offer cannibalization **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### BIZ-006 — Count assisted value carefully ```text IF an informational asset rarely receives last-click conversions but appears in qualified journeys THEN measure assisted progression, returning users, branded demand, and controlled lift ELSE judge the asset on direct value and task completion ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Baseline, Major **Primary metric:** assisted contribution value **Guardrail:** double counting **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### BIZ-007 — Split branded and non-branded demand ```text IF brand familiarity materially changes intent, CTR, or conversion THEN report branded and non-branded performance separately ELSE aggregate only for top-level totals ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** value-weighted non-brand clicks **Guardrail:** brand campaign effects **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### BIZ-008 — Include retention and expansion ```text IF organic search serves existing customers, support, renewal, or repeat purchase tasks THEN assign retention events and lifetime-value effects ELSE use acquisition outcomes for new-user clusters ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Major **Primary metric:** organic-assisted retained margin **Guardrail:** support deflection quality, churn **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### BIZ-009 — Raise evidence thresholds for high stakes ```text IF the topic can materially affect health, money, safety, legal rights, or major decisions THEN require qualified review, primary sources, explicit limitations, and stronger maintenance ELSE apply the normal evidence standard ``` **Operators:** IF · OR · THEN · ELSE · AND **LAKA level(s):** Major, Structural **Primary metric:** verified task success **Guardrail:** harm, complaint, correction rate **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### BIZ-010 — Resolve competing goals explicitly ```text IF traffic, lead quality, margin, brand, retention, and learning objectives conflict THEN name one primary objective and classify the others as constraints or secondary outcomes ELSE use the single aligned objective ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** objective clarity **Guardrail:** unintended metric trade-offs **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### BIZ-011 — Allocate by marginal value ```text IF multiple valid initiatives compete for limited resources THEN rank them by expected incremental value divided by effort, risk, maintenance, and time to learning ELSE execute the only valid initiative ``` **Operators:** IF · THEN · ELSE · AND **LAKA level(s):** Baseline, Structural **Primary metric:** realized value per implementation hour **Guardrail:** portfolio concentration risk **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### BIZ-012 — Use economic stop rules ```text IF expected remaining incremental value is below expected cost OR risk exceeds tolerance THEN stop, defer, retire, or redesign the initiative ELSE continue to the next defined review point ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Baseline, Paradigm **Primary metric:** net incremental value **Guardrail:** sunk-cost bias **Reason:** Makes the decision explicit, measurable, and reversible where possible. ## 2. Audience and Journey ### AUD-001 — Require an audience-task pair ```text IF a candidate query cannot be mapped to a plausible audience and task THEN classify it as uncertain and gather evidence ELSE attach the audience, condition, task, and journey state ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** classified-demand share **Guardrail:** forced persona assumptions **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUD-002 — Treat funnel modifiers as heuristics ```text IF a word such as how, best, review, price, or buy suggests a journey stage THEN use it as a hypothesis and verify the actual task and result set ELSE infer stage from the full query, context, and behavior ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** intent-classification accuracy **Guardrail:** stage stereotyping **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUD-003 — Model the funnel as a graph ```text IF journey analysis assumes every user enters at awareness and moves linearly THEN allow entry, exit, return, skip, and backward transitions ELSE retain observed journey paths ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** state-transition rate **Guardrail:** attribution inflation **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUD-004 — Use adjacent next actions ```text IF the proposed CTA requires substantially more trust or commitment than the current task supports THEN offer an adjacent useful action OR add the proof needed to justify the transition ELSE measure the direct transition ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Minor, Major **Primary metric:** next-state transition rate **Guardrail:** bounce, complaint, unsubscribe **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUD-005 — Split materially different audience needs ```text IF two audience segments require different evidence, terminology, constraints, or offers THEN create distinct sections, experiences, or canonical assets based on task compatibility ELSE serve them in one asset ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Major, Structural **Primary metric:** qualified conversion by segment **Guardrail:** duplication, maintenance **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUD-006 — Include accessibility conditions ```text IF the task depends on visual, motor, auditory, cognitive, or assistive-technology access THEN design the format, navigation, media, and controls for those conditions ELSE apply baseline accessible design to all assets ``` **Operators:** IF · OR · THEN · ELSE · AND **LAKA level(s):** Major, Structural **Primary metric:** task completion by accessibility condition **Guardrail:** keyboard traps, missing alternatives **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUD-007 — Require real local distinctness ```text IF a geography modifier is proposed as a separate page THEN require actual service eligibility, local evidence, local differences, and maintainable data ELSE consolidate into a broader service-area asset ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** qualified local conversions **Guardrail:** doorway-page risk, inaccurate claims **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUD-008 — Localize, do not merely translate ```text IF language or country versions differ in terminology, regulation, inventory, currency, or user expectations THEN localize content and targeting signals ELSE use a shared translation only where the task and facts truly remain equivalent ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Major, Structural **Primary metric:** correct-locale conversion **Guardrail:** translation quality, hreflang errors **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUD-009 — Account for device context ```text IF device changes task conditions or interface needs THEN adapt layout, media, interaction, and next action while preserving canonical meaning ELSE use the common responsive experience ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Minor, Major **Primary metric:** task completion by device **Guardrail:** content parity **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUD-010 — Match evidence to urgency ```text IF the user has high urgency or high perceived risk THEN front-load direct answers, scope, availability, proof, and safe next actions ELSE use the standard information order ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Major **Primary metric:** time to task completion **Guardrail:** misleading urgency **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUD-011 — Explicitly exclude wrong audiences ```text IF queries attract jobs, students, freebie seekers, unsupported geographies, or unrelated senses THEN add exclusions to research, paid data, reporting, and content positioning ELSE retain the query in its valid cluster ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Baseline, Minor **Primary metric:** irrelevant-impression and unqualified-lead rate **Guardrail:** accidental exclusion of valuable demand **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUD-012 — Build post-purchase search pathways ```text IF customers search for setup, use, troubleshooting, maintenance, renewal, or complementary products THEN create support and retention task clusters with appropriate next actions ELSE focus the cluster on acquisition ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Major **Primary metric:** retention and support value **Guardrail:** support accuracy **Reason:** Makes the decision explicit, measurable, and reversible where possible. ## 3. Semantic Demand ### SEM-001 — Start from parent concepts ```text IF an offer lacks a mapped semantic territory THEN identify parent concepts, neighboring categories, and business boundaries ELSE extend the existing concept graph ``` **Operators:** IF · THEN · ELSE · AND **LAKA level(s):** Baseline **Primary metric:** concept-map coverage **Guardrail:** scope drift **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### SEM-002 — Expand through subtypes ```text IF a parent concept contains meaningful narrower types with distinct tasks THEN create subtype clusters and evaluate them independently ELSE keep subtype terms as sections or variants ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Baseline, Major **Primary metric:** subtype demand coverage **Guardrail:** thin fragmentation **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### SEM-003 — Normalize synonyms and paraphrases ```text IF different phrases express the same sense and dominant task THEN map them to one query cluster and one intended canonical asset ELSE investigate whether the task differs ``` **Operators:** IF · AND · THEN · ELSE · XOR **LAKA level(s):** Baseline **Primary metric:** cluster cohesion **Guardrail:** missed senses **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### SEM-004 — Disambiguate homonyms and polysemy ```text IF the same wording can refer to different concepts, entities, or tasks THEN create sense labels and exclusions before clustering ELSE use the unambiguous concept ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** wrong-sense rate **Guardrail:** query misclassification **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### SEM-005 — Model modifiers as facets ```text IF terms vary by price, material, size, audience, platform, location, time, or other attributes THEN represent them as attribute-value pairs and test whether they create a distinct task ELSE treat them as lexical variants ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Baseline, Structural **Primary metric:** facet value and distinctness **Guardrail:** facet explosion **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### SEM-006 — Use co-occurrence as context ```text IF a term commonly appears near the topic but is not itself the user’s target THEN use it only where it explains an entity, relation, attribute, or evidence need ELSE exclude it from mandatory coverage ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Minor, Major **Primary metric:** task completeness **Guardrail:** unnatural term insertion **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### SEM-007 — Map entities and relations ```text IF the task depends on named things and how they connect THEN record entity types and typed relations, then express those relations visibly ELSE use concept-only structure ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Major **Primary metric:** entity-relation coverage **Guardrail:** entity ambiguity **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### SEM-008 — Map query fan-out without page fan-out ```text IF one broad task implies several supporting questions THEN map the questions as sections, evidence needs, or distinct adjacent tasks ELSE do not create a separate page for every wording variation ``` **Operators:** IF · THEN · ELSE · OR **LAKA level(s):** Major, Structural **Primary metric:** fan-out task coverage **Guardrail:** scaled-content duplication **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### SEM-009 — Triangulate demand evidence ```text IF a candidate appears in only one tool or source THEN seek corroboration from first-party data, users, result sets, competitors, or sales/support evidence ELSE increase confidence when independent sources agree ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** demand-confidence score **Guardrail:** tool bias **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### SEM-010 — Do not equate zero tool volume with zero demand ```text IF a query has low or zero reported volume but appears in first-party or customer evidence THEN retain it as a low-volume or emerging candidate and measure the cluster ELSE deprioritize only after value and evidence review ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** observed cluster demand **Guardrail:** anecdotal overreach **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### SEM-011 — Attach time state ```text IF facts, prices, availability, standards, laws, events, or recommendations can change THEN assign freshness requirements and update triggers ELSE classify the asset as stable evergreen ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** freshness compliance **Guardrail:** stale claims **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### SEM-012 — Model emerging demand separately ```text IF a new technology, regulation, event, or behavior has weak historical search data but strong causal evidence THEN create an experimental demand thesis with explicit uncertainty ELSE use normal historical prioritization ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Paradigm **Primary metric:** learning-adjusted emerging-demand value **Guardrail:** trend chasing **Reason:** Makes the decision explicit, measurable, and reversible where possible. ## 4. Clustering and Canonical Ownership ### CLU-001 — One dominant intent, one owner ```text IF a dominant intent cluster is approved THEN assign exactly one intended canonical URL ELSE keep the cluster in research ``` **Operators:** IF · THEN · ELSE · EXACTLY_ONE **LAKA level(s):** Baseline, Structural **Primary metric:** canonical ownership completeness **Guardrail:** multiple owners **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CLU-002 — Merge same-task candidates ```text IF sense, task, answer structure, result class, and next action are compatible THEN merge candidates into one cluster ELSE evaluate split conditions ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** demand coverage per canonical asset **Guardrail:** over-broad pages **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CLU-003 — Split different tasks ```text IF queries share vocabulary but require different completion conditions or document forms THEN create separate clusters and page roles ELSE keep them together ``` **Operators:** IF · AND · OR · THEN · ELSE **LAKA level(s):** Baseline, Major **Primary metric:** intent purity **Guardrail:** duplicated introductions **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CLU-004 — Use result overlap as evidence, not law ```text IF current top results overlap strongly for two queries THEN increase merge confidence but still inspect task and business context ELSE do not force a split solely because result overlap is low ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** cluster validation accuracy **Guardrail:** SERP volatility **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CLU-005 — Detect cannibalization by behavior ```text IF multiple owned URLs receive the same cluster’s impressions with unstable dominance or divided value THEN inspect intent, links, conversion, and canonical ownership ELSE allow multiple URLs when they serve genuinely different tasks ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Baseline, Structural **Primary metric:** dominant URL share and URL entropy **Guardrail:** false-positive cannibalization **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CLU-006 — Merge with migration discipline ```text IF two pages are redundant and one combined page is superior THEN merge best information, select the winner, redirect the loser, and update links/sitemaps ELSE reposition or retain both ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** consolidated value and retained demand **Guardrail:** migration loss **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CLU-007 — Reposition a useful weaker page ```text IF a weaker page has independent value but overlaps the stronger page’s task THEN change its dominant intent and connect it as a supporting asset ELSE merge it ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Major, Structural **Primary metric:** distinct-cluster value **Guardrail:** residual overlap **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CLU-008 — Inspect equity before deletion ```text IF a page appears useless or redundant THEN check links, traffic, conversions, references, and dependencies before delete/noindex ELSE retain or consolidate the page ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Baseline, Structural **Primary metric:** value preserved after retirement **Guardrail:** broken dependencies **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CLU-009 — Align canonical signals ```text IF duplicate or parameter URLs must remain accessible THEN align canonical annotations, internal links, sitemap entries, redirects, and content signals ELSE self-canonicalize the unique page ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** declared-selected canonical agreement **Guardrail:** mixed signals **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CLU-010 — Protect established URLs ```text IF an older URL has links, traffic, or history and the only proposed improvement is a prettier slug THEN keep the URL unless expected benefit clearly exceeds migration risk ELSE optimize the new URL before launch ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Minor, Structural **Primary metric:** post-change value retention **Guardrail:** redirect chains **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CLU-011 — Keep lexical variants together ```text IF differences are spelling, word order, pluralization, abbreviation, or stemming without task change THEN include natural variants in one asset and reporting cluster ELSE treat materially different senses separately ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Minor **Primary metric:** variant coverage **Guardrail:** keyword stuffing **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CLU-012 — Test uncertain cluster boundaries ```text IF merge/split evidence is inconclusive THEN assign a provisional owner, record uncertainty, and observe query-to-URL behavior before scaling ELSE finalize the cluster ``` **Operators:** IF · THEN · ELSE · UNTIL **LAKA level(s):** Baseline, Major **Primary metric:** cluster stability **Guardrail:** premature page multiplication **Reason:** Makes the decision explicit, measurable, and reversible where possible. ## 5. Content, Format, and Evidence ### CON-001 — Select format from task ```text IF the dominant task is known THEN choose a format that completes that task: guide, table, calculator, map, diagnostic, template, video, or transaction page ELSE research the task before drafting ``` **Operators:** IF · THEN · ELSE · OR **LAKA level(s):** Major **Primary metric:** task completion rate **Guardrail:** format novelty without utility **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CON-002 — Answer early ```text IF a user can benefit from a concise direct answer THEN provide it near the beginning and then support it ELSE state the path to the answer and necessary prerequisites ``` **Operators:** IF · THEN · ELSE **LAKA level(s):** Minor, Major **Primary metric:** time to first useful answer **Guardrail:** oversimplification **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CON-003 — Require information advantage ```text IF the proposed asset only restates widely available material THEN add original experience, data, testing, utility, synthesis, local proof, or decision support ELSE proceed with the defensible advantage ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Major, Paradigm **Primary metric:** information-advantage score **Guardrail:** unsupported originality claims **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CON-004 — Prefer firsthand evidence where relevant ```text IF the task involves reviews, demonstrations, processes, products, or lived outcomes THEN show what was actually tested, observed, used, or built ELSE use the best available primary evidence ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Major **Primary metric:** firsthand-evidence coverage **Guardrail:** conflicts of interest **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CON-005 — Make evidence visible ```text IF a claim depends on a source, test, credential, or dataset THEN place the supporting evidence where the user can inspect it ELSE qualify the claim as opinion or uncertainty ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Minor, Major **Primary metric:** verifiable-claim rate **Guardrail:** citation mismatch **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CON-006 — State limitations ```text IF evidence has uncertainty, sample limits, conflicts, exceptions, or changing conditions THEN state limitations and applicability boundaries ELSE present the stable conclusion ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Minor **Primary metric:** correction and dispute rate **Guardrail:** loss of nuance **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CON-007 — Avoid arbitrary length targets ```text IF a word count is proposed without a task-based reason THEN define completeness by required questions, evidence, and decision support ELSE use length as a production estimate only ``` **Operators:** IF · THEN · ELSE · AND **LAKA level(s):** Baseline, Major **Primary metric:** task completeness per reading time **Guardrail:** content bloat **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CON-008 — Govern AI-assisted content ```text IF AI assists research, drafting, transformation, or scale THEN require factual verification, original value, editorial ownership, and policy compliance ELSE use the same quality controls for human-only work ``` **Operators:** IF · OR · THEN · ELSE · AND **LAKA level(s):** Structural **Primary metric:** verified publication quality **Guardrail:** hallucination, scaled abuse **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CON-009 — Require row-level uniqueness at scale ```text IF a template generates pages from a dataset THEN require accurate unique data, distinct user utility, and a valid canonical task for each row ELSE consolidate rows into filters, tables, or broader assets ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Structural, Paradigm **Primary metric:** unique-value coverage per generated page **Guardrail:** doorway and thin-page risk **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CON-010 — Use media when it improves the task ```text IF an image, diagram, video, audio, or interactive can explain or demonstrate more effectively THEN include accessible, relevant media and measure its use ELSE keep the experience text-first where sufficient ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Major **Primary metric:** media-assisted task completion **Guardrail:** performance, accessibility **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CON-011 — Define refresh triggers ```text IF content depends on changing data or conditions THEN assign owner, source, review cadence, and event-triggered updates ELSE review only when performance or business context changes ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** freshness SLA **Guardrail:** maintenance debt **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CON-012 — Support commercial pages with useful assets ```text IF a commercial page is important but difficult to cite or insufficient for research-stage users THEN create genuinely useful supporting evidence, tools, comparisons, or guides ELSE improve the commercial page directly ``` **Operators:** IF · AND · OR · THEN · ELSE **LAKA level(s):** Major, Structural **Primary metric:** assisted commercial value **Guardrail:** manufactured link bait **Reason:** Makes the decision explicit, measurable, and reversible where possible. ## 6. On-page and Search Appearance ### ONP-001 — Align the title with the task ```text IF the title does not clearly identify the page’s dominant task or value THEN rewrite it truthfully for relevance and useful differentiation ELSE retain it and monitor ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Minor **Primary metric:** position-adjusted CTR **Guardrail:** qualified conversion rate **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### ONP-002 — Use unique titles for unique canonicals ```text IF two intended indexable canonical pages use materially duplicate titles THEN differentiate titles according to their distinct tasks ELSE allow shared patterns with unique identifying content ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Minor, Structural **Primary metric:** duplicate-title rate **Guardrail:** template inconsistency **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### ONP-003 — Measure title changes causally ```text IF a title or snippet is changed THEN record change date, exposed queries/pages, expected mechanism, and CTR guardrails ELSE do not claim impact ``` **Operators:** IF · THEN · ELSE · AND **LAKA level(s):** Minor **Primary metric:** CTR residual **Guardrail:** ranking, conversion, seasonality **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### ONP-004 — Write descriptions for decision support ```text IF the result snippet can help users determine relevance THEN write a concise truthful proposition with task, benefit, and distinguishing detail ELSE allow the search engine to select contextual text ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Minor **Primary metric:** organic CTR **Guardrail:** snippet mismatch **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### ONP-005 — Use headings as answer architecture ```text IF the task has stages, criteria, subquestions, or choices THEN structure headings around those information functions ELSE use a simple hierarchy ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Major **Primary metric:** section-level task coverage **Guardrail:** heading keyword stuffing **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### ONP-006 — Write natural body language ```text IF required concepts, entities, attributes, and relations are missing THEN add them where they improve the explanation ELSE do not insert terms solely for coverage scores ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Major **Primary metric:** semantic task completeness **Guardrail:** readability **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### ONP-007 — Reject keyword stuffing ```text IF repetition exists primarily to influence ranking rather than aid comprehension THEN remove or rewrite it and preserve only natural references ELSE retain meaningful repetition ``` **Operators:** IF · THEN · ELSE **LAKA level(s):** Minor **Primary metric:** editorial quality **Guardrail:** loss of clarity **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### ONP-008 — Describe meaningful images ```text IF an image communicates information or functions as a link/control THEN provide appropriate descriptive alternative text ELSE use empty alternative text for purely decorative images ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Minor, Structural **Primary metric:** accessible-media coverage **Guardrail:** redundant alt text **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### ONP-009 — Optimize new URLs, protect old ones ```text IF a page has not launched THEN use a concise descriptive stable URL ELSE avoid changing an established URL without a migration case ``` **Operators:** IF · THEN · ELSE **LAKA level(s):** Minor, Structural **Primary metric:** URL stability and migration retention **Guardrail:** redirect chains **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### ONP-010 — Use structured data only when applicable ```text IF a supported structured-data type accurately represents visible page content THEN implement and validate it ELSE do not add irrelevant or hidden markup ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Major, Structural **Primary metric:** valid eligible items **Guardrail:** manual action, markup drift **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### ONP-011 — Measure rich-result realization ```text IF structured data validates successfully THEN measure actual search appearance, impressions, CTR, and value ELSE debug eligibility or accept that display is not guaranteed ``` **Operators:** IF · THEN · ELSE **LAKA level(s):** Baseline, Major **Primary metric:** rich-result appearance and value **Guardrail:** misattribution **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### ONP-012 — Adjust CTR expectations ```text IF CTR is evaluated THEN control for position, device, country, brand status, query class, and search appearance ELSE do not use a universal CTR threshold ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** CTR residual **Guardrail:** low sample size **Reason:** Makes the decision explicit, measurable, and reversible where possible. ## 7. Internal Graph and Architecture ### GRF-001 — Link every priority page ```text IF a page is intended to receive organic visibility THEN ensure at least one crawlable contextual internal link points to it ELSE remove it from the priority/index set if it has no valid role ``` **Operators:** IF · THEN · ELSE · AT_LEAST **LAKA level(s):** Baseline, Minor **Primary metric:** priority-page orphan rate **Guardrail:** forced links **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GRF-002 — Use descriptive anchors ```text IF anchor text is generic and a natural descriptive label is available THEN replace it with concise context-setting text ELSE retain the generic control only when interface convention requires it ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Minor **Primary metric:** descriptive-anchor coverage **Guardrail:** over-optimization **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GRF-003 — Require user context for links ```text IF a proposed link does not help the reader understand, compare, verify, or take the next step THEN do not add it ELSE add it in the relevant sentence or interface ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Minor **Primary metric:** useful internal-link interaction **Guardrail:** link clutter **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GRF-004 — Create hubs for navigation needs ```text IF a coherent task family requires users to choose among multiple paths THEN create or improve a hub with clear categories and routes ELSE connect assets contextually without a dedicated hub ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** hub-assisted discovery and conversion **Guardrail:** empty taxonomy pages **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GRF-005 — Validate supporting assets ```text IF an adjacent question has independent demand, a complete answer, and a useful relationship to a core asset THEN create a supporting asset and connect it ELSE include it as a section or FAQ ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Major **Primary metric:** supporting-asset assisted value **Guardrail:** thin content **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GRF-006 — Reduce excessive depth ```text IF important pages are difficult to reach through internal navigation THEN add meaningful paths, hubs, or template links ELSE retain depth for low-value or intentionally isolated pages ``` **Operators:** IF · THEN · ELSE · OR **LAKA level(s):** Structural **Primary metric:** priority-page click depth **Guardrail:** navigation overload **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GRF-007 — Use strong internal sources deliberately ```text IF an authoritative owned page can naturally support a high-value target THEN add a contextual link where it benefits the reader ELSE do not insert an unrelated link solely to move authority ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Minor **Primary metric:** target visibility lift **Guardrail:** source-page task disruption **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GRF-008 — Keep topical communities coherent ```text IF a link crosses unrelated topic communities without user need THEN remove or avoid it ELSE retain cross-topic links that represent a real prerequisite, comparison, or journey edge ``` **Operators:** IF · AND · NOT · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** topical edge precision **Guardrail:** over-siloing **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GRF-009 — Make links crawlable ```text IF navigation or internal discovery relies on nonstandard scripted interactions THEN expose crawlable anchors with destinations and validate rendered HTML ELSE retain standard crawlable links ``` **Operators:** IF · THEN · ELSE · AND **LAKA level(s):** Structural **Primary metric:** crawlable-link coverage **Guardrail:** duplicate navigation **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GRF-010 — Concentrate, do not hoard ```text IF many low-value pages dilute attention and internal graph flow THEN consolidate, noindex, archive, or demote according to user and business value ELSE retain useful nodes ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** value-weighted index and graph concentration **Guardrail:** loss of long-tail value **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GRF-011 — Update the graph after migrations ```text IF a page is merged, redirected, renamed, or retired THEN update internal links, navigation, canonicals, and sitemaps to the final destination ELSE leave the graph unchanged ``` **Operators:** IF · OR · THEN · ELSE · AND **LAKA level(s):** Structural **Primary metric:** direct-to-final-link rate **Guardrail:** redirect loops **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GRF-012 — Measure paths, not link counts alone ```text IF internal linking is evaluated THEN measure discovery, depth, target visibility, task progression, and conversion paths ELSE use raw link counts only as diagnostics ``` **Operators:** IF · THEN · ELSE · AND **LAKA level(s):** Baseline **Primary metric:** graph-assisted value **Guardrail:** correlation mistaken for causation **Reason:** Makes the decision explicit, measurable, and reversible where possible. ## 8. External Authority and Earned Evidence ### AUT-001 — Evaluate link quality multidimensionally ```text IF an external link opportunity is considered THEN evaluate relevance, editorial independence, source credibility, placement, uniqueness, and persistence ELSE reject or deprioritize the opportunity ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** qualified retained referring domains **Guardrail:** spam and paid-link risk **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUT-002 — Create a linkable reason ```text IF outreach asks for attention without a concrete user benefit THEN build or identify data, utility, evidence, correction, visualization, or unique reference value ELSE lead with the existing value ``` **Operators:** IF · AND · NOT · THEN · ELSE · OR **LAKA level(s):** Major, Paradigm **Primary metric:** placement rate **Guardrail:** misleading claims **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUT-003 — Support difficult commercial targets ```text IF the target commercial page is unlikely to earn independent citations THEN earn links to a relevant useful asset and connect it to the target OR improve the target’s reference value ELSE promote the target directly ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Major, Structural **Primary metric:** assisted target-page visibility **Guardrail:** manipulative intermediary pages **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUT-004 — Reject manipulative placements ```text IF a link requires deception, irrelevant insertion, undisclosed payment, or policy violation THEN reject it ELSE proceed with transparent editorial or appropriately attributed placement ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** policy-compliant placement rate **Guardrail:** manual actions, reputation **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUT-005 — Prefer unique relevant domains ```text IF many links come repeatedly from the same source while relevant independent sources are available THEN diversify outreach toward unique relevant domains ELSE deepen the useful relationship without treating every link as independent authority ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Major **Primary metric:** qualified unique referring domains **Guardrail:** diversity for its own sake **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUT-006 — Prefer contextual editorial placement ```text IF a link can appear in a useful body context or only in a repeated footer/sidebar THEN prefer the contextual editorial placement ELSE treat repeated placement as lower-confidence evidence ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Major **Primary metric:** contextual placement share **Guardrail:** sponsorship disclosure **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUT-007 — Use tool metrics as proxies ```text IF DA, DR, UR, PA, traffic estimates, or difficulty scores are used THEN treat them as vendor-specific diagnostics and compare within one system ELSE use direct observations where available ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** proxy-to-outcome calibration **Guardrail:** cross-tool comparisons **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUT-008 — Investigate lost evidence ```text IF a valuable relevant link or mention disappears THEN classify cause and recover only when the source relationship and user value remain valid ELSE record normal churn ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Minor, Major **Primary metric:** valuable-link recovery rate **Guardrail:** harassing outreach **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUT-009 — Measure brand demand effects ```text IF earned media or authoritative mentions may increase awareness without direct referral clicks THEN track branded queries, direct visits, assisted conversions, and target visibility ELSE measure direct referral and link effects ``` **Operators:** IF · AND · NOT · THEN · ELSE **LAKA level(s):** Baseline, Major **Primary metric:** incremental branded demand **Guardrail:** campaign overlap **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUT-010 — Segment outreach by relationship ```text IF prospects differ by audience, reason to care, or editorial context THEN create distinct outreach propositions and evidence packages ELSE use one aligned proposition ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Major **Primary metric:** positive reply and placement rate by segment **Guardrail:** automation quality **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUT-011 — Compound original research ```text IF original data or a benchmark performs well THEN refresh it, expose methodology, create reusable views, and connect related clusters ELSE treat it as a one-time asset ``` **Operators:** IF · THEN · ELSE · AND **LAKA level(s):** Structural, Paradigm **Primary metric:** research-attributed links and value **Guardrail:** methodology drift **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### AUT-012 — Judge authority by target outcomes ```text IF links or mentions increase but the target cluster does not improve THEN inspect relevance, target selection, indexing, content fit, and time lag ELSE continue scaling the validated authority mechanism ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Baseline, Major **Primary metric:** incremental target-cluster visibility and value **Guardrail:** over-attribution **Reason:** Makes the decision explicit, measurable, and reversible where possible. ## 9. Technical Eligibility ### TEC-001 — Require public accessibility ```text IF a page is intended for search visibility THEN ensure users and permitted crawlers can request its essential content ELSE exclude it intentionally ``` **Operators:** IF · THEN · ELSE · AND **LAKA level(s):** Baseline, Structural **Primary metric:** accessible-priority-URL rate **Guardrail:** private or sensitive exposure **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### TEC-002 — Use correct response states ```text IF a canonical page is healthy and available THEN return a successful response; use redirects, not-found, or server errors only for their true states ELSE repair the response logic ``` **Operators:** IF · THEN · ELSE · OR **LAKA level(s):** Structural **Primary metric:** correct-status rate **Guardrail:** soft 404s **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### TEC-003 — Validate rendered main content ```text IF essential content or links depend on JavaScript THEN inspect rendered output and ensure resources are accessible ELSE use the server-delivered content ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** rendered-content parity **Guardrail:** hydration and blocked-resource errors **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### TEC-004 — Separate crawling from indexing controls ```text IF the goal is to keep a page out of search results THEN use an appropriate noindex, authentication, removal, redirect, or deletion method ELSE use robots.txt only to manage crawler requests, not as a deindex guarantee ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** intended index-state accuracy **Guardrail:** content leakage **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### TEC-005 — Maintain canonical coherence ```text IF multiple URLs represent substantially the same content THEN select a preferred URL and align canonical, redirects where appropriate, links, and sitemap signals ELSE self-canonicalize the unique asset where useful ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** canonical agreement **Guardrail:** canonical chains **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### TEC-006 — Keep sitemaps canonical and current ```text IF a URL is important, canonical, and intended for indexing THEN include its clean URL and accurate modification state in the sitemap ELSE exclude noncanonical, redirected, error, or intentionally nonindexed URLs ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** valid canonical sitemap coverage **Guardrail:** misleading lastmod **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### TEC-007 — Redirect to the closest valid successor ```text IF a URL permanently moves or is consolidated THEN redirect directly to the most relevant final destination and update internal references ELSE serve the existing URL ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** direct permanent-redirect accuracy **Guardrail:** chains, loops, irrelevant redirects **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### TEC-008 — Treat not-found pages intentionally ```text IF a resource no longer exists and has no valid replacement THEN return a real not-found state with helpful navigation ELSE redirect only when a genuine equivalent exists ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** soft-404 rate **Guardrail:** lost valuable links **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### TEC-009 — Control faceted and parameter volume ```text IF filters, sorting, search, tracking, or session parameters create many near-duplicate URLs THEN define crawl, canonical, link, and index rules by facet value ELSE allow unique valuable combinations ``` **Operators:** IF · OR · THEN · ELSE · AND **LAKA level(s):** Structural **Primary metric:** valuable-crawl share **Guardrail:** index explosion **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### TEC-010 — Preserve content parity ```text IF mobile, desktop, locale, or rendered versions differ THEN ensure essential content, metadata, structured data, and links remain equivalent where they should ELSE document intentional differences ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** version parity **Guardrail:** cloaking-like mismatches **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### TEC-011 — Prioritize real-user performance ```text IF field performance or business outcomes show latency, instability, or interaction problems THEN fix the highest-exposure causes and measure Core Web Vitals plus conversion/task outcomes ELSE repair only obvious low-cost issues and avoid score chasing ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Minor, Structural **Primary metric:** good-CWV exposure and task value **Guardrail:** functionality regression **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### TEC-012 — Scale crawl work to site size and change rate ```text IF the site is very large, rapidly changing, or shows crawl/index waste THEN invest in crawl-path, logs, facets, and index-quality optimization ELSE use a lighter periodic technical audit ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** valuable indexed URLs per crawl/resource unit **Guardrail:** technical work without business case **Reason:** Makes the decision explicit, measurable, and reversible where possible. ## 10. Conversion and Experience ### CVR-001 — Complete the search task before selling ```text IF the page asks for conversion before delivering the promised answer THEN front-load useful task completion and place the offer at a logical transition ELSE retain the aligned conversion path ``` **Operators:** IF · BEFORE · THEN · ELSE **LAKA level(s):** Major **Primary metric:** task completion then conversion **Guardrail:** reduced qualified action **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CVR-002 — Match nudge to journey state ```text IF the next action is not adjacent to the user’s current state THEN choose a lower-friction or more relevant action ELSE measure the existing transition ``` **Operators:** IF · THEN · ELSE **LAKA level(s):** Minor, Major **Primary metric:** next-state conversion rate **Guardrail:** lead quality **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CVR-003 — Optimize speed for outcomes ```text IF slow or unstable experience correlates with abandonment or conversion loss THEN fix the responsible bottleneck and validate field/user outcomes ELSE do not pursue a perfect tool score solely for ranking ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Minor, Structural **Primary metric:** conversion and task completion by performance band **Guardrail:** broken features **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CVR-004 — Reduce form friction selectively ```text IF form abandonment is high AND removed fields are not needed for qualification or routing THEN shorten, stage, or clarify the form ELSE retain fields and improve explanation ``` **Operators:** IF · AND · THEN · ELSE · OR **LAKA level(s):** Minor, Major **Primary metric:** qualified form completion **Guardrail:** unqualified volume **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CVR-005 — Optimize for lead quality ```text IF lead count rises while acceptance, close rate, or margin falls THEN tighten intent, promise, qualification, or routing ELSE scale the validated acquisition path ``` **Operators:** IF · AND · OR · THEN · ELSE **LAKA level(s):** Major, Structural **Primary metric:** sales-accepted organic leads **Guardrail:** total pipeline **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CVR-006 — Test CTA propositions, not colors alone ```text IF a CTA underperforms THEN test task relevance, value, risk, evidence, commitment, placement, and wording before cosmetic variables ELSE retain and scale it ``` **Operators:** IF · THEN · ELSE · BEFORE **LAKA level(s):** Minor, Major **Primary metric:** qualified CTA conversion **Guardrail:** misleading claims **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CVR-007 — Place trust at the decision point ```text IF users hesitate because scope, proof, identity, terms, price, or risk is unclear THEN place relevant evidence and clarification near the decision ELSE avoid repetitive trust decoration ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Major **Primary metric:** decision completion rate **Guardrail:** privacy and disclosure **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CVR-008 — Avoid premature hard selling ```text IF the query is early-stage and commercial pressure harms task satisfaction THEN use a useful soft transition such as a related guide, tool, save, or diagnostic ELSE present the proportional commercial action ``` **Operators:** IF · AND · THEN · ELSE · OR **LAKA level(s):** Major **Primary metric:** assisted qualified progression **Guardrail:** unsubscribe, bounce **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CVR-009 — Design retention paths ```text IF the organic visitor is an existing customer or user THEN route to successful use, support, renewal, expansion, or advocacy ELSE route prospects toward acquisition ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Major **Primary metric:** retention/expansion event value **Guardrail:** support escalation **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CVR-010 — Measure satisfaction with task-specific events ```text IF generic engagement metrics cannot show whether the task was completed THEN instrument meaningful events such as calculator completion, comparison use, download, copy, or successful route ELSE use the existing task event ``` **Operators:** IF · THEN · ELSE · OR **LAKA level(s):** Structural **Primary metric:** task completion rate **Guardrail:** event inflation **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CVR-011 — Preserve message continuity ```text IF the search promise, landing answer, CTA, and sales follow-up describe different outcomes THEN align the chain around one user task and offer ELSE retain the coherent journey ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** promise-to-close continuity **Guardrail:** overly narrow messaging **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### CVR-012 — Protect user and brand guardrails ```text IF a conversion intervention increases action but also complaints, refunds, low-quality leads, or distrust THEN revert, constrain, or redesign the intervention ELSE continue while guardrails stay within tolerance ``` **Operators:** IF · AND · OR · THEN · ELSE **LAKA level(s):** Minor, Major **Primary metric:** guardrail-adjusted conversion value **Guardrail:** dark patterns **Reason:** Makes the decision explicit, measurable, and reversible where possible. ## 11. Measurement and Experimentation ### EXP-001 — Require a mechanism hypothesis ```text IF an intervention has no stated reason it should affect an outcome THEN write an object → action → mechanism → outcome hypothesis ELSE execute the stated hypothesis ``` **Operators:** IF · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** hypothesis completeness **Guardrail:** post-hoc storytelling **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### EXP-002 — Capture a baseline ```text IF a change is about to be implemented THEN record pre-change performance, context, exposure, and data quality ELSE do not claim incremental effect ``` **Operators:** IF · THEN · ELSE · AND **LAKA level(s):** Baseline **Primary metric:** baseline completeness **Guardrail:** seasonal distortion **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### EXP-003 — Use a change ledger ```text IF any SEO-relevant production change occurs THEN assign a change ID, owner, scope, time, expected mechanism, and rollback state ELSE retain the previous ledger ``` **Operators:** IF · THEN · ELSE · AND **LAKA level(s):** Structural **Primary metric:** change attribution coverage **Guardrail:** logging overhead **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### EXP-004 — Choose one primary metric ```text IF an experiment has many possible success metrics THEN select one primary decision metric and label others secondary or guardrail ELSE use the aligned primary metric ``` **Operators:** IF · THEN · ELSE · EXACTLY_ONE **LAKA level(s):** Baseline **Primary metric:** decision consistency **Guardrail:** metric cherry-picking **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### EXP-005 — Set guardrails before launch ```text IF a change can improve the primary metric while harming quality, accessibility, revenue, or trust THEN define guardrail thresholds and rollback behavior ELSE use standard site guardrails ``` **Operators:** IF · OR · THEN · ELSE · AND **LAKA level(s):** Baseline **Primary metric:** guardrail breach rate **Guardrail:** unobserved harm **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### EXP-006 — Use controls when feasible ```text IF comparable untreated pages, clusters, regions, or time periods exist THEN use a control or difference-in-differences design ELSE use interrupted time series with explicit limitations ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** estimated incremental lift **Guardrail:** control contamination **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### EXP-007 — Account for seasonality and external events ```text IF demand, algorithms, campaigns, news, inventory, or holidays can affect the outcome THEN annotate and model those factors before attributing change ELSE use the stable comparison ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** context-adjusted lift **Guardrail:** overfitting **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### EXP-008 — Represent uncertainty ```text IF sample size is small, variance is high, or exposure is incomplete THEN report ranges, confidence, and directional evidence ELSE report the stable estimate ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** estimate uncertainty **Guardrail:** false precision **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### EXP-009 — Allow processing and learning time ```text IF a change has not had enough crawl, index, ranking, or behavioral exposure THEN continue observation until the predefined minimum exposure or stop condition ELSE make the decision ``` **Operators:** IF · OR · THEN · ELSE · UNTIL **LAKA level(s):** Baseline **Primary metric:** minimum-exposure completion **Guardrail:** indefinite waiting **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### EXP-010 — Distinguish single-variable and package tests ```text IF several material variables change together THEN classify the intervention as a package test OR separate variables for causal learning ELSE treat it as a focused test ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Minor, Major, Structural **Primary metric:** attribution confidence **Guardrail:** slow recovery **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### EXP-011 — Escalate by diagnosed mechanism ```text IF a lower-level LAKA intervention fails THEN re-diagnose and move to Major, Structural, or Paradigm only when the failure mechanism requires it ELSE retain or scale the successful level ``` **Operators:** IF · THEN · ELSE · OR **LAKA level(s):** Minor, Major, Structural, Paradigm **Primary metric:** value gained per escalation **Guardrail:** unnecessary redesign **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### EXP-012 — Use explicit continue/revise/revert/retire decisions ```text IF a review point is reached THEN choose exactly one decision based on primary metric, guardrails, cost, and confidence ELSE continue observation only under a predefined uncertainty rule ``` **Operators:** IF · AND · THEN · ELSE · XOR **LAKA level(s):** Baseline **Primary metric:** decision closure rate **Guardrail:** zombie experiments **Reason:** Makes the decision explicit, measurable, and reversible where possible. ## 12. Generative Search, Scale, and Governance ### GOV-001 — Keep foundational SEO as the base ```text IF the goal includes visibility in generative search experiences THEN apply the same valuable-content, crawlability, indexability, and search-quality foundations ELSE apply normal search foundations ``` **Operators:** IF · AND · THEN · ELSE **LAKA level(s):** Baseline, Structural **Primary metric:** search and generative visibility value **Guardrail:** channel-specific hacks **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GOV-002 — Do not depend on llms.txt for Google Search ```text IF a proposal claims a special AI text file is required for Google visibility THEN reject the requirement and prioritize public crawlable indexable content ELSE maintain such a file only for a separate system that explicitly uses it ``` **Operators:** IF · THEN · ELSE **LAKA level(s):** Baseline **Primary metric:** eligible indexed coverage **Guardrail:** maintenance distraction **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GOV-003 — Do not chunk content mechanically ```text IF content is being split only because an AI system is assumed to need tiny sections THEN organize by human task, readability, and information structure ELSE retain useful natural sections ``` **Operators:** IF · THEN · ELSE **LAKA level(s):** Major **Primary metric:** task completion and retrieval coverage **Guardrail:** fragmentation **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GOV-004 — Use query fan-out as a research map ```text IF a broad request implies related information needs THEN map prerequisite, comparison, evidence, and follow-up needs across the cluster graph ELSE use the direct task map ``` **Operators:** IF · THEN · ELSE · AND **LAKA level(s):** Major, Structural **Primary metric:** fan-out information coverage **Guardrail:** one-page-per-query expansion **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GOV-005 — Block scaled content abuse ```text IF content volume is generated primarily to manipulate rankings or AI responses without distinct user value THEN stop publication and redesign the system ELSE continue only with row-level utility, accuracy, and governance ``` **Operators:** IF · AND · NOT · THEN · ELSE **LAKA level(s):** Structural, Paradigm **Primary metric:** unique useful asset rate **Guardrail:** spam-policy exposure **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GOV-006 — Measure generative visibility directly ```text IF Search Console or another first-party surface provides generative-search reporting THEN track it as a distinct search appearance and connect it to downstream value ELSE use broader search and referral diagnostics with limitations ``` **Operators:** IF · THEN · ELSE · AND **LAKA level(s):** Baseline, Structural **Primary metric:** generative-search qualified value **Guardrail:** reporting coverage **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GOV-007 — Do not invent AI-specific schema ```text IF a proposal adds unsupported structured data solely for generative visibility THEN reject it; use supported structured data only when it matches visible content ELSE validate the applicable markup ``` **Operators:** IF · THEN · ELSE **LAKA level(s):** Baseline, Structural **Primary metric:** valid supported markup **Guardrail:** markup abuse **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GOV-008 — Prepare for agentic use through usability ```text IF browser agents or assistive systems need to interpret and operate the site THEN improve semantic controls, labels, accessible structure, clear states, and stable data ELSE retain the usable human-facing implementation ``` **Operators:** IF · OR · THEN · ELSE · AND **LAKA level(s):** Structural, Paradigm **Primary metric:** successful task completion by automated/assistive clients **Guardrail:** security and consent **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GOV-009 — Expose freshness and provenance ```text IF data may change or be reused in generated answers THEN show dates, methodology, sources, ownership, and update state where useful ELSE omit unnecessary metadata ``` **Operators:** IF · OR · THEN · ELSE · AND **LAKA level(s):** Major **Primary metric:** freshness/provenance completeness **Guardrail:** false recency **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GOV-010 — Constrain programmatic expansion ```text IF candidate combinations exceed quality or maintenance capacity THEN raise gates, consolidate, stage release, or automate verified data maintenance ELSE publish within capacity ``` **Operators:** IF · OR · THEN · ELSE **LAKA level(s):** Structural **Primary metric:** maintained useful-page rate **Guardrail:** index and maintenance debt **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GOV-011 — Protect privacy, consent, and sensitive data ```text IF volumetric generation or personalization uses personal, confidential, licensed, or restricted data THEN minimize data, obtain rights/consent, secure access, and exclude unsafe outputs ELSE use public or owned permissible data ``` **Operators:** IF · OR · THEN · ELSE · AND **LAKA level(s):** Structural **Primary metric:** governance compliance **Guardrail:** privacy harm **Reason:** Makes the decision explicit, measurable, and reversible where possible. ### GOV-012 — Pursue paradigm assets selectively ```text IF a new tool, dataset, benchmark, diagnostic, or agent can complete the task far better than existing result classes THEN run a bounded paradigm experiment with a defensibility and maintenance plan ELSE improve the current asset class ``` **Operators:** IF · OR · THEN · ELSE · AND **LAKA level(s):** Paradigm **Primary metric:** new-demand and incremental value creation **Guardrail:** build cost, adoption risk **Reason:** Makes the decision explicit, measurable, and reversible where possible. ## Composite decision programs ### Program A — Should a new page exist? ```text IF observed_or_defensible_demand AND distinct_task AND one_canonical_role AND meaningful_information_advantage AND business_or_strategic_value AND maintainable_accuracy AND technical_feasibility AND measurable_outcome THEN approve page specification ELSE: merge into existing page OR create a section OR retain as research OR reject ``` ### Program B — Should two pages merge? ```text IF same_sense AND same_dominant_task AND substantial_query_overlap AND combined_answer_improves_user_value AND migration_risk_is_acceptable THEN: choose winner merge best information redirect loser update internal links update sitemap observe retained value ELSE: clarify separate intents OR reposition weaker page ``` ### Program C — What should be fixed first? ```text IF measurement_is_unreliable THEN fix measurement ELSE IF priority_asset_is_ineligible THEN fix technical eligibility ELSE IF existing_asset_has_high_value_gap THEN optimize existing asset ELSE IF canonical_ownership_is_confused THEN consolidate or restructure ELSE IF information_product_is_inferior THEN improve content, evidence, or format ELSE IF authority_gap_is_material THEN build independent evidence and promotion ELSE create the highest-scoring new asset ``` ### Program D — LAKA escalation ```text START Baseline IF failure is presentation-level THEN Minor ELSE IF failure is answer/evidence/format-level THEN Major ELSE IF failure spans pages, templates, graph, or data systems THEN Structural ELSE IF the current solution class cannot satisfy the opportunity THEN Paradigm ELSE stop or monitor ``` ### Program E — Volumetric scale permission ```text FOR EACH candidate combination: IF distinct_task AND unique_or_verified_data AND useful_output AND canonical_role AND maintenance_owner AND measurable_value THEN allow staged generation ELSE consolidate, filter, or suppress UNTIL: marginal_value < marginal_cost OR quality_guardrail fails OR maintenance_capacity is reached ``` --- # 05 — Measurement and Experiment System ## 1. Measurement philosophy SEO is a partially observed causal system. Search engines do not expose every internal variable, so the measurement model separates: ```text BUSINESS OUTCOMES DIAGNOSTIC OUTCOMES SYSTEM STATES INTERVENTIONS CONTEXT UNCERTAINTY ``` Never infer success from a proxy without checking the downstream outcome it is supposed to influence. ```text ranking ↑ does not automatically imply qualified value ↑ ``` --- ## 2. Outcome hierarchy ### Level 1 — Business outcomes ```text qualified leads sales subscription starts retained customers expansion revenue support value contribution margin customer lifetime value ``` ### Level 2 — Journey outcomes ```text task completion next-step action assessment completion demo request quote request trial start qualified form return visit renewal action referral/review ``` ### Level 3 — Search outcomes ```text impressions search appearances average position / rank distribution clicks CTR landing sessions branded demand non-branded demand ``` ### Level 4 — Asset and graph diagnostics ```text query-cluster coverage canonical ownership internal in-links click depth orphan state qualified referring domains content/evidence completeness freshness ``` ### Level 5 — Technical states ```text discoverable crawlable renderable canonicalized indexable indexed retrievable valid structured data field performance ``` --- ## 3. Primary formulas ### 3.1 Actual organic contribution margin ```text ACTUAL ORGANIC CONTRIBUTION = Σ( attributed organic conversions × contribution margin per conversion ) − attributable SEO operating cost ``` ### 3.2 Incremental lift When a reasonable comparison group exists: ```text INCREMENTAL LIFT = (Post_treatment − Pre_treatment) − (Post_control − Pre_control) ``` Apply separately to: - impressions; - clicks; - qualified conversions; - revenue; - contribution margin; - retention. ### 3.3 Expected value ```text EXPECTED VALUE = Σ( demand estimate × probability of eligibility × probability of useful visibility × expected CTR × expected qualified conversion rate × contribution margin ) − expected cost ``` Every estimated input must be labeled and later replaced with observed data. ### 3.4 Value-weighted visibility ```text VALUE-WEIGHTED VISIBILITY = Σ( query opportunity value × observed visibility weight ) / Σ(query opportunity value) ``` Visibility weight may be based on impression share, rank distribution, or a calibrated CTR curve. ### 3.5 CTR residual ```text CTR RESIDUAL = Observed CTR − Expected CTR( position, device, country, brand class, query class, search appearance ) ``` This is more useful than a universal “good CTR” threshold. ### 3.6 Qualified conversion value ```text QUALIFIED ORGANIC VALUE = organic value events × qualification probability × contribution margin ``` ### 3.7 Opportunity score ```text OPPORTUNITY SCORE = ( demand confidence × business fit × task value × information advantage × attainable response gap × conversion value × evidence confidence ) / ( effort × risk × maintenance burden × time to learning ) ``` ### 3.8 Eligible canonical coverage ```text ELIGIBLE CANONICAL COVERAGE = priority canonical URLs that are eligible and indexed / all priority canonical URLs intended for indexing ``` ### 3.9 Canonical agreement ```text CANONICAL AGREEMENT = URLs where intended/declarative canonical agrees with observed selected canonical / evaluated duplicate or canonical URLs ``` ### 3.10 Cannibalization indicators ```text DOMINANT URL SHARE = largest URL impression share for cluster / total cluster impressions ``` ```text URL ENTROPY = −Σ(p_url × ln(p_url)) ``` High entropy is a diagnostic, not automatic failure. Confirm same-intent duplication, instability, divided links, or value loss. ### 3.11 Internal graph diagnostics ```text PRIORITY ORPHAN RATE = priority pages with no useful crawlable internal in-link / all priority pages ``` ```text WEIGHTED CLICK DEPTH = Σ(page business weight × page click depth) / Σ(page business weight) ``` ### 3.12 Authority diagnostics ```text QUALIFIED LINK RATE = retained relevant editorial referring domains / all acquired referring domains ``` --- ## 4. Data grain Store search observations at the smallest useful grain: ```text date site_id cluster_id query canonical_url country device search_type search_appearance brand_class change_id ``` Attach: ```text impressions clicks ctr average_position organic_sessions task_completions next_actions qualified_leads sales revenue contribution_margin ``` Store technical observations separately: ```text observation_time url status_code robots_allowed render_success declared_canonical selected_canonical index_state sitemap_state internal_inlinks click_depth field_lcp field_inp field_cls structured_data_state ``` Store changes: ```text change_id object_type object_id laka_level hypothesis mechanism owner start_time end_time rollback_state primary_metric guardrails decision_rule ``` --- ## 5. Event dictionary A measurement plan must define every event. | Event | Definition | Required properties | |---|---|---| | `organic_landing` | Session begins on an organic search landing page | landing URL, cluster, query class | | `task_start` | User initiates the primary page task | task ID | | `task_complete` | User reaches a valid completion condition | task ID, method | | `next_action` | User takes the intended adjacent step | action ID | | `qualified_form` | Form meets qualification rules | offer, segment, qualification | | `sales_accept` | Sales accepts the lead | CRM status | | `closed_value` | Revenue or margin is confirmed | value, margin, offer | | `retention_value` | Renewal, expansion, or support outcome | customer, event value | | `evidence_interaction` | User opens data, sources, demo, comparison, or case proof | evidence ID | | `internal_path` | User follows a meaningful graph edge | edge type, target | | `calculator_complete` | Tool returns a valid result | inputs band, result band | | `download_use` | User downloads or uses a template | asset ID | Avoid meaningless event inflation. An event should correspond to a user state or business state. --- ## 6. Baseline protocol Before changing a priority object: ```text 1. Verify data collection. 2. Define treatment object and exposure. 3. Record at least the available stable pre-period. 4. Record query mix, device, country, brand class, and seasonality. 5. Record technical eligibility. 6. Record current page and graph state. 7. Record current business value. 8. Assign change ID. 9. Predefine primary metric and guardrails. 10. State minimum exposure and review rule. ``` If historical data is unavailable, create a prospective baseline and explicitly reduce causal confidence. --- ## 7. Hypothesis grammar ```text IF [INTERVENTION] is applied to [OBJECT] under [CONDITIONS], THEN [PRIMARY METRIC] will change in [DIRECTION] because [MECHANISM], while [GUARDRAILS] remain within [THRESHOLDS]. ``` Example: ```text IF the title proposition for the Calgary web design cost guide is rewritten to state the year, location, and estimator benefit, THEN position-adjusted organic CTR will increase because relevance and expected utility become clearer, while qualified assessment rate does not decline by more than 10%. ``` --- ## 8. LAKA experiment card ```text Experiment ID: Object: Conditions: Action: Tools: Resources: Expected outcome: Feedback source: Constraints: Value: Failure mode: LAKA level: Magnitude: Rate: Direction: Scope: Depth: Duration: Frequency: Acceleration: Variability: Detectability: Reversibility: Propagation: Amplification: Accumulation: Primary metric: Baseline: Treatment scope: Comparison: Minimum exposure: Decision rule: Guardrails: Rollback: Owner: ``` --- ## 9. Decision outcomes At every review, choose one: ```text CONTINUE EXPAND REVISE REVERSE ESCALATE RETIRE MONITOR ``` ### Continue ```text IF evidence is positive AND guardrails pass AND additional exposure is needed THEN continue. ``` ### Expand ```text IF positive effect is credible AND mechanism is transferable AND capacity permits THEN expand to a defined cohort. ``` ### Revise ```text IF mechanism appears valid BUT implementation is weak or guardrails fail mildly THEN revise. ``` ### Reverse ```text IF primary outcome declines materially OR a critical guardrail fails AND rollback is feasible THEN reverse. ``` ### Escalate ```text IF the diagnosed failure is deeper than the current LAKA level AND expected value still exceeds cost THEN escalate. ``` ### Retire ```text IF remaining value is low OR maintenance/risk is too high OR the asset has no distinct task THEN consolidate, redirect, noindex, archive, or remove appropriately. ``` --- ## 10. Experiment types ### 10.1 Minor element test Examples: - title proposition; - snippet description; - introductory answer; - CTA wording; - anchor text; - small media change. Best for high exposure and reversible mechanisms. ### 10.2 Major asset test Examples: - full rewrite; - new comparison; - original data; - tool or video; - new evidence architecture. Evaluate as an intervention package unless components can be separated. ### 10.3 Structural test Examples: - page merge; - template change; - internal graph redesign; - facet control; - CRM linkage; - site architecture. Use cohort or time-series analysis and monitor propagation. ### 10.4 Paradigm test Examples: - calculator instead of article; - benchmark instead of generic guide; - verified directory instead of location-page set; - interactive diagnostic instead of lead form; - data API or agent action instead of static copy. Primary value may include new demand, citations, brand searches, product adoption, and conversion. --- ## 11. Comparison designs Use the strongest feasible design: ```text Randomized controlled test > matched page/cluster control > staggered rollout > difference-in-differences > interrupted time series > before/after with context controls > directional observation ``` SEO often prevents perfect randomization. State the design’s limits rather than implying certainty. --- ## 12. Observation windows Do not use one fixed calendar window for every intervention. Define exposure criteria: ```text minimum crawl confirmation minimum index confirmation minimum impressions minimum qualified sessions minimum conversions minimum full business cycle ``` A review may occur when one or more exposure thresholds are met, with a maximum stop date to prevent endless observation. --- ## 13. Dashboard architecture ### Executive dashboard ```text incremental organic contribution margin qualified organic conversions value-weighted non-brand clicks value-weighted target-cluster visibility eligible canonical coverage ``` ### Demand dashboard ```text cluster impressions new query families branded vs non-branded journey state audience/offer country/device value-weighted demand ``` ### Asset dashboard ```text canonical owner rank distribution CTR residual task completion next-action conversion freshness information/evidence score ``` ### Technical dashboard ```text status correctness render parity canonical agreement index eligibility sitemap coverage orphan rate click depth field CWV exposure structured data validity ``` ### Authority dashboard ```text qualified new/lost referring domains relevance target page placement type retention brand-demand lift assisted value ``` ### Experiment dashboard ```text change ID LAKA level status primary metric effect estimate uncertainty guardrails decision learning ``` --- ## 14. Metric anti-patterns ```text DO NOT: count indexed pages as success without value; treat average position as a precise rank; use a single sitewide CTR benchmark; equate bounce with failure for every task; equate tool authority scores with Google internals; claim revenue from a forecast; attribute all movement to the most recent change; ignore branded demand created by other channels; optimize event count rather than user state; continue an experiment without a stop rule. ``` --- ## 15. Monthly learning review Ask: ```text Which clusters created the most qualified value? Which assets lost demand or eligibility? Which query families are emerging? Where is the intended canonical not dominant? Which formats improve task completion? Which evidence earns links or branded demand? Which next actions produce quality, not merely volume? Which technical failures block the most value? Which LAKA level produced the best value per effort? Which assumptions were disproved? What should the generator weight differently next month? ``` The output is an updated rule prior, portfolio, and backlog—not merely a report. --- # 06 — Audit and Execution SOPs ## SOP 1 — Establish the SEO measurement foundation ### Goal Create a trustworthy chain from search visibility to contribution margin. ### Steps 1. List offers, audiences, and qualified value events. 2. Define contribution margin or provisional value bands. 3. Verify Search Console and analytics access. 4. Define organic landing and task events. 5. connect leads/sales to CRM or commerce records where possible. 6. classify branded and non-branded demand. 7. create a change ledger. 8. record data limitations. 9. build the five-metric executive dashboard. 10. run a test transaction and verify the complete chain. ### Pass rule ```text PASS IF search exposure AND landing AND task event AND qualified outcome AND value can be connected at an acceptable confidence level. ``` --- ## SOP 2 — Build the semantic demand graph ### Inputs ```text offers customer interviews/calls sales objections support questions site search Search Console paid-search terms competitor visibility industry entities ``` ### Steps 1. Define the parent concept and business boundary. 2. Generate subtypes, entities, attributes, relations, problems, causes, solutions, comparisons, and questions. 3. Attach audience and journey states. 4. collect observed query language. 5. normalize synonyms and variants. 6. mark homonyms and exclusions. 7. attach demand evidence and source confidence. 8. attach possible task formats. 9. export candidates for clustering. ### Output `semantic-demand-inventory` --- ## SOP 3 — Cluster queries and assign canonical ownership ### Steps 1. Group same-sense lexical variants. 2. identify the dominant task for each query. 3. compare answer structure and result class. 4. inspect current result overlap as supporting evidence. 5. merge same-task queries. 6. split different completion conditions. 7. assign one intended canonical URL. 8. map existing URLs to clusters. 9. flag missing pages, duplicate owners, and uncertain boundaries. 10. record exclusions and supporting questions. ### Decision ```text same sense AND same task AND compatible answer AND compatible next action → same cluster different task OR different sense OR different necessary format → separate cluster ``` --- ## SOP 4 — Find high-value existing opportunities ### Steps 1. Export query-page data. 2. join business value and conversion data. 3. calculate cluster-level impressions, clicks, CTR residual, and value. 4. identify positions or visibility below potential. 5. identify pages with links/authority but weak intent alignment. 6. identify ranking pages with poor conversion. 7. identify converting pages with low visibility. 8. identify high-value pages with technical eligibility problems. 9. score opportunities by incremental value per effort. 10. select a bounded treatment portfolio. ### Priority logic ```text measurement block > eligibility block > canonical conflict > existing high-value response gap > content/format gap > authority gap > new asset ``` --- ## SOP 5 — Create a page specification ### Steps 1. Copy the page brief template. 2. state one dominant task. 3. define audience, condition, intent, and journey state. 4. list same-intent queries and exclusions. 5. choose canonical URL and page type. 6. define the direct answer. 7. map required entities, attributes, and relations. 8. choose the task-appropriate format. 9. define evidence and media. 10. define links in and out. 11. define next action. 12. define primary metric, guardrails, refresh trigger, and owner. ### Gate ```text IF any required field is unknown THEN mark it as a research question AND do not silently invent it. ``` --- ## SOP 6 — Optimize an existing page with LAKA ### Baseline - record query mix; - verify canonical/index state; - measure current CTR, task completion, conversion, and value; - inspect current result classes and competitors; - map content/evidence gaps; - map internal and external graph position. ### Minor candidates - title; - snippet; - direct answer; - heading; - anchor; - CTA; - image optimization. ### Major candidates - rewrite; - new evidence; - comparison; - calculator; - video; - decision tree; - accessibility improvement. ### Structural candidates - merge/split; - template; - hub; - internal graph; - canonical/facet repair; - conversion data pipeline. ### Paradigm candidates - new information product; - proprietary benchmark; - free diagnostic; - verified directory; - agent-operable workflow. ### Selection Choose the lowest LAKA level capable of affecting the diagnosed failure. --- ## SOP 7 — Resolve cannibalization ### Detection Flag clusters with: ```text multiple ranking URLs AND unstable dominant URL OR divided links OR wrong landing page OR lower conversion from the winning URL ``` ### Options ```text MERGE if task and answer substantially overlap. REPOSITION if the weaker page has a valid adjacent task. KEEP BOTH if tasks are distinct and behavior is healthy. RETIRE if the weak page has no value, dependencies, or equity. ``` ### Migration steps 1. choose canonical winner; 2. combine unique useful information; 3. preserve required evidence and media; 4. redirect when the old URL should disappear; 5. update internal links; 6. update sitemap and canonical signals; 7. observe impressions, dominant share, links, and value; 8. rollback or refine if material loss occurs. --- ## SOP 8 — Build a useful internal graph ### Steps 1. list priority canonical pages. 2. calculate orphan state and click depth. 3. classify page relationships. 4. create understanding, choice, journey, and authority edges. 5. use crawlable links and descriptive anchors. 6. add hubs only where path selection is useful. 7. link strong pages to high-value targets where contextually appropriate. 8. remove irrelevant or repetitive link clutter. 9. update links after migrations. 10. measure discovery, path use, visibility, and conversion. --- ## SOP 9 — Technical eligibility audit ### Ordered checks 1. intended search state; 2. public accessibility; 3. HTTP status; 4. rendered main content and links; 5. robots and index directives; 6. declared and selected canonical; 7. duplicate/facet behavior; 8. internal discovery and depth; 9. sitemap correctness; 10. mobile/content parity; 11. field performance; 12. structured data eligibility; 13. international/local signals; 14. security/manual-action issues. ### Value ranking For every issue: ```text Affected priority URLs × affected demand/value × probability of blocking or degrading visibility ÷ repair effort and risk ``` Fix business-blocking defects before generic audit-score improvements. --- ## SOP 10 — Authority and earned-evidence campaign ### Steps 1. choose a target cluster and business goal. 2. diagnose the authority/evidence gap. 3. define a linkable reason. 4. select or build the evidence asset. 5. identify relevant audiences and publishers. 6. segment prospects by reason to care. 7. create truthful outreach. 8. record placement type and destination. 9. monitor retained links, brand demand, target visibility, and value. 10. refresh or compound successful evidence assets. --- ## SOP 11 — Volumetric page-generation audit ### Use before programmatic publishing For every proposed template row, verify: ```text distinct task AND unique accurate data AND real user utility AND one canonical role AND local/product eligibility AND internal path AND quality ownership AND refresh mechanism AND measurable value ``` ### Sampling 1. inspect random rows; 2. inspect highest- and lowest-data rows; 3. inspect duplicate-risk rows; 4. inspect missing-data behavior; 5. inspect stale-data behavior; 6. inspect generated titles/descriptions; 7. inspect canonical and facet behavior; 8. inspect mobile/accessibility; 9. inspect conversion continuity; 10. inspect index and maintenance capacity. ### Launch Use staged cohorts. Do not release the full theoretical volume at once. --- ## SOP 12 — Monthly portfolio review 1. update all business and diagnostic data. 2. review technical eligibility by value. 3. review cluster ownership and cannibalization. 4. review existing opportunities. 5. review new demand. 6. review authority and evidence. 7. review experiments and guardrails. 8. update opportunity scores. 9. choose continue, expand, revise, reverse, escalate, retire, or monitor. 10. rebalance the portfolio under capacity. --- ## SOP 13 — Content refresh or retirement ### Refresh ```text IF demand remains valuable AND facts/format/evidence are stale AND improvement value exceeds cost THEN refresh. ``` ### Consolidate ```text IF several assets overlap AND one stronger canonical can cover the task THEN merge and migrate. ``` ### Retire ```text IF the page has no distinct task AND no meaningful demand, value, links, or dependency THEN retire with the appropriate technical state. ``` ### Preserve ```text IF the page serves a valid user need despite low search traffic THEN preserve it AND do not judge it only by SEO metrics. ``` --- ## SOP 14 — Generative-search readiness 1. ensure valuable content is public, crawlable, indexable, and snippet-eligible where intended. 2. map broad tasks and their supporting information needs. 3. add firsthand experience, original data, evidence, and useful media. 4. avoid creating a page for every query fan-out variation. 5. avoid unsupported AI-specific markup or assumed special files. 6. expose freshness, provenance, and limitations when relevant. 7. make controls, labels, content, and data understandable to humans, assistive technology, and browser agents. 8. measure generative search appearances and downstream value when first-party reporting is available. 9. apply the same spam, quality, privacy, and legal governance as ordinary search. 10. test paradigm assets that let users or agents complete real tasks. --- # 07 — Page and Cluster Templates Copy these templates into your project. Keep unknown fields visible as research questions. --- ## Template A — Business and value model ```markdown # Business Value Model Business: Offer: Audience: Geography: Primary business goal: Qualified value event: Qualification rule: Average revenue per event: Average contribution margin per event: Capacity constraint: Sales-cycle length: Retention/expansion value: Primary guardrails: Data sources: Known limitations: ``` --- ## Template B — Audience–task card ```markdown # Audience–Task Card Audience ID: Segment: Role: Industry: Experience: Problem awareness: Solution awareness: Urgency: Budget/risk: Geography: Language: Device/context: Accessibility conditions: Problem or desire: Task verb: Task object: Completion condition: Intent: Journey state: Common language: Objections: Wrong-audience exclusions: Desired next state: Business value event: ``` --- ## Template C — Semantic demand inventory | Candidate ID | Parent | Concept/entity | Relation | Attribute | Value | Audience | Task | Intent | Modifier | Query evidence | Exclusions | Confidence | |---|---|---|---|---|---|---|---|---|---|---|---|---| --- ## Template D — Intent-cluster brief ```markdown # Intent Cluster Cluster ID: Working name: Parent concept: Dominant task: Completion condition: Intent: Journey state: Audience: Conditions: Representative query: Same-intent variants: Entities: Relations: Attributes: Questions: Adjacent intents: Exclusions: Demand evidence: Business value: Expected result forms: Current competing result forms: Information gap: Information advantage: Cluster confidence: Intended canonical URL: Existing URLs: Supporting assets: Next action: Primary metric: Guardrails: Owner: Status: ``` --- ## Template E — Same-page / separate-page decision ```markdown # Cluster Boundary Test Candidate A: Candidate B: Same sense? yes/no/uncertain Same dominant task? yes/no/uncertain Same completion condition? yes/no/uncertain Compatible answer structure? yes/no/uncertain Compatible result class? yes/no/uncertain Compatible audience state? yes/no/uncertain Compatible next action? yes/no/uncertain Substantial current result overlap? yes/no/uncertain Independent user value if separated? high/medium/low Maintenance cost if separated? high/medium/low Decision: - Merge - Split - Keep provisional - Test Reason: Canonical owner: Uncertainty: Review trigger: ``` --- ## Template F — Canonical registry | Cluster ID | Dominant task | Intended canonical | Existing competing URLs | Decision | Redirect/canonical action | Internal-link action | Status | |---|---|---|---|---|---|---|---| --- ## Template G — Page specification ```markdown # Page Specification Page ID: Cluster ID: Canonical URL: Page type: Owner: Status: ## Audience and task Audience: Conditions: Dominant task: Completion condition: Intent: Journey state: Next logical action: ## Search language Representative query: Same-intent variants: Exclusions: Expected search appearances: Competing result forms: ## Promise and answer Title proposition: Direct answer: Core promise: User success condition: ## Information architecture Required sections: Required entities: Required relations: Required attributes: Required comparisons: Required edge cases: Required FAQs: ## Format Primary format: Supporting media: Interactive element: Downloadable: Accessibility requirements: ## Evidence Firsthand evidence: Original data: Primary sources: Expert review: Case proof: Methodology: Limitations: Freshness date: Refresh trigger: ## Graph Parent/hub: Prerequisite links: Supporting links: Comparison links: Commercial/next-step links: Required links into page: Required links out: ## Technical Intended index state: Status: Canonical: Sitemap: Structured data: Rendering requirements: Performance risks: Locale/device notes: ## Measurement Primary metric: Secondary metrics: Guardrails: Baseline: Change ID: Minimum exposure: Decision rule: ``` --- ## Template H — LAKA 50-cell change matrix | Internal variable | Baseline | Minor change | Major change | Structural change | Paradigm change | |---|---|---|---|---|---| | Object | | | | | | | Conditions | | | | | | | Actions | | | | | | | Tools | | | | | | | Resources | | | | | | | Outcomes | | | | | | | Feedback | | | | | | | Constraints | | | | | | | Value | | | | | | | Failure mode | | | | | | Attach the fourteen descriptors to every shortlisted change. --- ## Template I — Fourteen-variable change descriptor ```markdown Change ID: LAKA level: Magnitude: Rate: Direction: Scope: Depth: Duration: Frequency: Acceleration: Variability: Detectability: Reversibility: Propagation: Amplification: Accumulation: ``` --- ## Template J — Experiment card ```markdown # SEO Experiment Experiment ID: Date: Owner: Object: LAKA level: Hypothesis: Mechanism: Treatment: Treatment scope: Comparison/control: Baseline: Minimum exposure: Maximum review date: Primary metric: Expected direction: Expected minimum useful effect: Secondary metrics: Guardrails: Rollback: Magnitude: Rate: Direction: Scope: Depth: Duration: Frequency: Acceleration: Variability: Detectability: Reversibility: Propagation: Amplification: Accumulation: Decision: - Continue - Expand - Revise - Reverse - Escalate - Retire - Monitor Result: Uncertainty: Learning: Rule-weight update: ``` --- ## Template K — Opportunity scorecard | Factor | 0–5 score | Evidence | Confidence | |---|---:|---|---:| | Demand confidence | | | | | Business fit | | | | | Task value | | | | | Information advantage | | | | | Conversion value | | | | | Attainability | | | | | Existing signal | | | | | Reuse potential | | | | | Learning value | | | | | Production effort | | | | | Technical risk | | | | | Maintenance burden | | | | | Time to learning | | | | ```text Adjusted priority = value factors / cost factors × evidence confidence × measurement confidence ``` --- ## Template L — Technical state record | URL | Intended state | Accessible | Status | Rendered | Robots | Index directive | Declared canonical | Selected canonical | Indexed | Sitemap | In-links | Depth | CWV | Structured data | Priority | |---|---|---|---|---|---|---|---|---|---|---|---:|---:|---|---|---| --- ## Template M — Internal graph map | Source URL | Edge type | Anchor/context | Target URL | User reason | Crawlable | Priority | Change ID | |---|---|---|---|---|---|---|---| Allowed edge types: ```text definition_of prerequisite_of example_of evidence_for comparison_to alternative_to step_before step_after supports converts_to location_variant_of service_variant_of ``` --- ## Template N — Authority campaign ```markdown # Authority Campaign Campaign ID: Target cluster: Target URL: Business outcome: Diagnosed gap: Linkable reason: Evidence asset: Relevant audiences: Publisher/prospect classes: Outreach propositions: Disclosures: Placement requirements: Rejected placement conditions: Primary metric: Qualified-domain definition: Target-page metric: Brand-demand metric: Conversion metric: Retention check: Owner: Refresh/compound plan: ``` --- ## Template O — Content refresh / merge / retirement decision ```markdown URL: Cluster: Distinct task still valid?: Demand: Business value: Links/evidence: Conversions: Freshness: Accuracy: Maintenance burden: Competing owned URLs: Dependencies: Decision: - Preserve - Refresh - Reposition - Merge - Redirect - Noindex - Archive - Remove Reason: Migration steps: Guardrails: Observation plan: ``` --- ## Template P — Monthly portfolio review ```markdown # Monthly SEO Portfolio Review Period: Owner: ## Business Contribution margin: Qualified conversions: Lead quality: Capacity: ## Demand Growing clusters: Declining clusters: New queries: Brand/non-brand movement: ## Canonical ownership Conflicts: Merges needed: Missing assets: Uncertain clusters: ## Technical Highest-value blockers: Canonical agreement: Eligible coverage: Orphans/depth: Field performance: ## Information products Best task-completion assets: Weak assets: Evidence gaps: Refreshes: ## Authority Qualified new/lost domains: Target lift: Research/assets to compound: ## Experiments Won: Lost: Uncertain: Escalated: Retired: ## Allocation decisions Continue: Expand: Revise: Reverse: Escalate: Retire: Monitor: ## Generator updates Weights increased: Weights decreased: New gates: Removed assumptions: ``` --- # 08 — Agent Operating Prompt Use this prompt to configure a lead SEO agent or an agent team. --- ## System prompt You are the **LAKA SEO Architect**, a rigorous SEO strategist, semantic modeler, information architect, technical auditor, conversion analyst, and experiment designer. Your purpose is not to maximize page count, keyword count, or rankings in isolation. Your purpose is to produce **incremental qualified business value** by connecting valuable user demand to technically eligible, task-completing, evidence-rich information products. ### Governing equation ```text SEO BUSINESS VALUE = VALUABLE DEMAND × TECHNICAL ELIGIBILITY × INTENT FIT × INFORMATION ADVANTAGE × DISCOVERABILITY × PROMINENCE × SEARCH-RESULT RESPONSE × CONVERSION EFFICIENCY × CONTRIBUTION MARGIN × LEARNING VELOCITY ``` Treat every factor as necessary. Do not hide a near-zero factor behind strong proxy metrics. ### Required grammar Every recommendation must name: ```text GOAL AUDIENCE CONDITIONS TASK INTENT QUERY CLUSTER CANONICAL ASSET FORMAT EVIDENCE INTERNAL GRAPH ROLE NEXT ACTION PRIMARY METRIC GUARDRAILS LAKA LEVEL DECISION RULE ``` ### LAKA levels ```text Baseline Minor Change Major Change Structural Change Paradigm Change ``` Always start with Baseline diagnosis. Select the lowest level capable of affecting the diagnosed mechanism. ### LAKA internal variables For every shortlisted intervention, fill: ```text Object Conditions Actions Tools Resources Outcomes Feedback Constraints Value Failure Mode ``` ### LAKA change descriptors Attach: ```text Magnitude Rate Direction Scope Depth Duration Frequency Acceleration Variability Detectability Reversibility Propagation Amplification Accumulation ``` ### Boolean logic Use explicit logic: ```text IF THEN ELSE AND OR NOT XOR FOR EACH UNTIL AT LEAST EXACTLY ONE ``` Do not substitute vague recommendations such as “improve content” or “build authority” without conditions, mechanisms, outputs, and metrics. ### Semantic rules 1. A core keyword is only a representative label for an intent cluster. 2. Synonyms, paraphrases, pluralization, stems, spelling, and word order usually remain in one cluster when the task is unchanged. 3. Homonyms and different senses must be separated. 4. Co-occurring terms are contextual entities, relations, and attributes—not words to insert mechanically. 5. One dominant intent cluster has exactly one intended canonical owner. 6. Split pages only when task, sense, necessary answer, result type, audience condition, geography/product eligibility, or next action materially differs. 7. Do not create a page for every query fan-out variation. 8. Generate candidates volumetrically, but publish only candidates that pass all hard gates. ### Hard publication gates ```text APPROVE IF demand is evidenced AND task is distinct AND business or strategic value exists AND information advantage exists AND technical feasibility exists AND maintainability exists AND measurement exists AND policy, privacy, legal, and ethical requirements pass. ``` Otherwise merge, include as a section, research, defer, or reject. ### Evidence standard Prefer: ```text firsthand experience OR original data OR reproducible testing OR primary sources OR expert review OR documented case evidence OR useful tool/visualization ``` State limitations and uncertainty. Never invent data, citations, tool outputs, customer evidence, or search results. ### Technical state model Keep these states separate: ```text Discovered Fetched Rendered Canonicalized Indexed Retrieved Displayed Visited Completed Converted ``` Prioritize technical work by affected business value, not by audit score alone. ### Measurement standard The primary business measure is normally: ```text Incremental Organic Contribution Margin ``` Also use: ```text Qualified Organic Conversions Value-Weighted Non-Brand Clicks Value-Weighted Target-Cluster Visibility Eligible Canonical Coverage ``` Every experiment requires a change ID, baseline, mechanism, primary metric, guardrails, exposure rule, decision rule, and rollback. ### Workflow #### Phase 1 — Inputs and constraints Collect or infer only from evidence: ```text business offers audiences geographies value events margins/value bands capacity constraints available data site scope ``` Mark unknown information explicitly. #### Phase 2 — Baseline Audit: ```text measurement technical eligibility query-to-URL behavior canonical ownership existing opportunity content/evidence internal graph external evidence conversion continuity ``` #### Phase 3 — Semantic demand graph Generate: ```text parents subtypes synonyms entities attributes relations problems causes solutions alternatives comparisons objections risks questions time states ``` Attach audience, task, intent, query evidence, and exclusions. #### Phase 4 — Clustering Apply the same-page/split rules. Produce a canonical intent registry. Flag uncertainty. #### Phase 5 — Volumetric generation For each valid cluster, generate possible: ```text formats evidence modes journey transitions search surfaces internal graph roles LAKA interventions ``` Do not automatically publish combinations. #### Phase 6 — Scoring Score by: ```text demand confidence business fit task value information advantage conversion value attainability existing signal reuse potential learning value effort risk maintenance time to learning ``` #### Phase 7 — Output Produce: 1. executive diagnosis; 2. opportunity inventory; 3. semantic graph; 4. intent clusters; 5. canonical registry; 6. page specifications; 7. internal graph plan; 8. technical backlog; 9. evidence/authority campaigns; 10. LAKA experiment matrix; 11. measurement plan; 12. prioritized implementation backlog; 13. explicit rejected/deferred candidates and reasons. ### Required recommendation format ```markdown ## [Recommendation] Goal: Audience: Task: Intent: Object: Condition: Diagnosed failure: LAKA level: Action: Mechanism: Required resources: Expected outcome: Primary metric: Guardrails: IF: THEN: ELSE: Failure mode: Reversibility: Next review rule: ``` ### Quality controls Before finalizing, check: ```text No keyword-only recommendations. No page without one canonical role. No invented search volume. No traffic-only success claims. No arbitrary word-count requirement. No automatic page per location, modifier, or fan-out query. No use of tool scores as Google internals. No unsupported AI/GEO hacks. No hidden structured data. No robots.txt recommendation as the sole deindex method. No migration without value and risk analysis. No experiment without a primary metric and stop rule. ``` ### Communication Be direct. Show the logic. Distinguish observation, inference, forecast, and decision. Report uncertainty without becoming vague. Prefer a smaller executable plan over a large undifferentiated list. --- # 09 — Implementation Backlog This backlog installs the system in stages. The sequence is dependency-based; it is not a promise of when rankings will change. ## Phase 0 — Governance and workspace ### Deliverables - project owner; - site and offer scope; - source-of-truth repository; - change ledger; - access and privacy rules; - naming conventions; - rule-library version. ### Exit gate ```text owner AND scope AND permissions AND change control are defined. ``` --- ## Phase 1 — Business and measurement baseline ### Tasks 1. Define offers and audiences. 2. Define qualified value events. 3. Record margin or value bands. 4. verify Search Console and analytics. 5. connect CRM/commerce outcomes where feasible. 6. classify brand/non-brand. 7. create executive dashboard. 8. test the event chain. 9. document limitations. 10. capture baseline. ### Output `business-value-model` `event-dictionary` `baseline-scorecard` --- ## Phase 2 — Technical eligibility baseline ### Tasks 1. Inventory intended canonical URLs. 2. classify intended index state. 3. inspect status, robots, rendering, canonical, index, sitemap. 4. calculate eligible canonical coverage. 5. calculate canonical agreement. 6. identify orphan and depth issues. 7. inspect duplicate/facet volume. 8. inspect field performance by exposure. 9. rank issues by affected business value. 10. repair P0 blockers. ### Output `technical-state-table` `value-ranked-technical-backlog` --- ## Phase 3 — Existing opportunity recovery ### Tasks 1. join queries, URLs, conversions, and value. 2. cluster current queries. 3. find strong pages with weak targeting. 4. find high-impression pages with low CTR residual. 5. find converting pages with weak visibility. 6. find ranking pages with poor qualification. 7. find cannibalizing clusters. 8. find pages with authority but no useful target. 9. score opportunities. 10. launch the first bounded Minor/Major cohort. ### Output `existing-opportunity-portfolio` `experiment-cards` --- ## Phase 4 — Semantic and canonical architecture ### Tasks 1. Build audience-task map. 2. build semantic graph. 3. collect query and customer language. 4. normalize synonyms and variants. 5. disambiguate senses. 6. cluster by task. 7. assign exactly one canonical owner. 8. map supporting assets. 9. flag missing, duplicate, and uncertain clusters. 10. approve priority cluster portfolio. ### Output `semantic-demand-inventory` `canonical-intent-registry` `cluster-boundary-log` --- ## Phase 5 — Core information products ### Tasks 1. Select highest-value decision and commercial clusters. 2. create page specifications. 3. choose task-native formats. 4. add information advantage. 5. create evidence. 6. connect next actions. 7. implement technical requirements. 8. add measurement. 9. publish in cohorts. 10. review and update rule priors. ### Output `core-page-specifications` `published-core-assets` --- ## Phase 6 — Supporting graph ### Tasks 1. Identify prerequisite and adjacent tasks. 2. validate supporting asset distinctness. 3. create or improve hubs where useful. 4. add understanding, choice, journey, and authority edges. 5. repair orphans. 6. reduce excessive depth. 7. update links after migrations. 8. measure assisted value. 9. remove weak or redundant nodes. 10. refresh canonical registry. ### Output `internal-graph-map` `supporting-asset-backlog` --- ## Phase 7 — Earned evidence and authority ### Tasks 1. Diagnose target cluster authority gaps. 2. create linkable reasons. 3. prioritize original data, tools, benchmarks, case evidence, and visual references. 4. segment prospects. 5. launch transparent outreach. 6. track retained relevant placements. 7. measure target visibility and brand demand. 8. recover valid lost links. 9. compound successful evidence assets. 10. recalibrate authority proxies. ### Output `authority-campaigns` `evidence-asset-roadmap` --- ## Phase 8 — Volumetric expansion ### Preconditions ```text canonical model is stable AND templates are quality controlled AND data is accurate AND maintenance capacity exists AND measurement cohorts exist AND policy gates pass ``` ### Tasks 1. Expand approved dimensions. 2. generate candidates. 3. normalize and cluster. 4. apply hard gates. 5. sample quality. 6. score survivors. 7. stage publication. 8. monitor duplicate, index, quality, and conversion behavior. 9. pause automatically on guardrail breach. 10. scale only validated cohorts. ### Output `volumetric-candidate-register` `staged-generation-plan` --- ## Phase 9 — Structural improvements Examples: - merge cannibalizing assets; - redesign hubs and templates; - control faceted navigation; - improve data pipelines; - connect value data; - localize international architecture; - improve field performance at scale; - standardize evidence and refresh workflows. Use change IDs and cohort rollouts. --- ## Phase 10 — Paradigm experiments Potential classes: ```text diagnostic tool calculator benchmark verified directory original dataset interactive map assessment engine comparison system API/data feed agent-operable transaction ``` ### Gate ```text IF new solution class completes the task materially better AND creates defensible value AND has a maintenance model AND can be measured THEN run a bounded paradigm experiment. ``` --- ## Ongoing cadence ### Weekly operating review - P0 measurement/technical blockers; - live experiments; - data-quality failures; - major demand or value shifts; - guardrail breaches. ### Monthly portfolio review - contribution value; - qualified conversions; - cluster visibility; - canonical ownership; - technical eligibility; - authority and evidence; - refresh/retirement; - allocation. ### Quarterly model review - rule performance; - scoring calibration; - audience/offer changes; - semantic territory; - structural debt; - paradigm opportunities. --- ## Definition of done An implementation item is complete only when: ```text change is deployed AND change ID is recorded AND intended technical state is verified AND measurement is active AND owner is assigned AND review rule is scheduled AND documentation is updated ``` --- # 10 — Course Crosswalk and Sources ## 1. Course-to-grammar translation This system preserves the course’s practical workflow while replacing ambiguous or outdated labels with measurable technical concepts. | Course concept | Grammar translation | Operational meaning | |---|---|---| | Target persona | Audience + conditions | Segment whose task, context, and value can be measured | | Sales funnel | Journey-state graph | Awareness, evaluation, decision, use, retention, and return paths | | Search framework | Audience–task–asset–surface–transition sentence | Who needs what, where it is served, and what happens next | | Core keyword | Representative query | Human-readable label for one dominant intent cluster | | Secondary keywords | Same-intent variants | Closely equivalent queries that one canonical asset can satisfy | | Accessory keywords | Adjacent task clusters | Related but independently useful information needs | | Keyword variations | Lexical normalization | Synonyms, spelling, word order, pluralization, abbreviations, stems | | LSI keywords | Contextual terms, entities, relations, attributes | Replace the “LSI” bucket with explicit semantic roles | | One keyword = one page | One dominant intent cluster = one canonical owner | Prevent conflicting page ownership without making a page per wording | | Intent bucketing | Task-based query clustering | Group queries according to one completion condition | | Revenue estimates | Probabilistic demand-to-value forecast | Separate assumptions from actual contribution margin | | SEO timeline estimate | Time-to-event forecast | Track crawl, index, impression, value, and uncertainty separately | | Reverse-engineering competitors | Competitive retrieval and information-gap analysis | Identify result forms, gaps, authority, and unmet tasks | | Document relevancy | Query–document task fit | Make the asset understandable and useful for the intended task | | On-page optimization | Document and search-appearance intervention | Improve relevance, response, evidence, and task completion | | Pages vs domains | URL-level intent ownership | Assign work and measurement to canonical assets | | Site architecture | Directed information graph | Paths, depth, hubs, communities, and canonical nodes | | SEO silos | Topical link communities | Useful internal relationships, not ritual folder structures | | UX signals | User-outcome telemetry | Task completion, progression, conversion, and experience measures | | Link building | Independent citation acquisition | Relevant, credible, editorial evidence and prominence | | Authority metrics | Vendor model outputs | Diagnostic proxies that require calibration to direct outcomes | | Technical optimization | Retrieval-eligibility engineering | Discover, fetch, render, canonicalize, index, retrieve, display | | Indexation | One technical state | Inclusion in an index, separated from discovery and display | | Canonical tags | Preferred representative signal | One signal in a coherent canonical system | | Keyword cannibalization | Query-to-URL ownership instability | Confirm same-intent competition and business loss before fixing | | Site speed | Real-user performance system | Improve field experience and value, not a perfect lab score | | Structured data | Machine-readable eligibility signal | Use supported markup that matches visible content | | Analytics and tracking | Outcome and intervention model | Connect search exposure to qualified value and learning | --- ## 2. Lesson map The following transcript modules informed the system. ### Strategy, audience, and funnel ```text 004-target-personas-and-the-sales-funnel.md 005-the-search-framework.md 006-branded-search.md 007-what-is-reputation-management.md 012-keywords-vs-the-sales-funnel.md ``` The grammar converts the course’s persona, asset, medium, optimization, and nudge model into: ```text Audience + Conditions + Task + Intent + Canonical asset + Search surface + Next action + Business outcome ``` ### Semantic research and mapping ```text 008-keyword-research-overview.md 009-keyword-types.md 010-keyword-variations-lsi.md 011-keyword-competitiveness.md 013-keyword-research-walkthrough.md 014-keyword-mapping-intent-bucketing.md 015-keyword-mapping-core-secondary-accessory-keywords.md 016-keyword-mapping-revenue-estimates.md 017-seo-roi-timeline-estimates.md 018-reverse-engineering-competitors.md ``` The grammar preserves the course’s practical grouping process but changes the unit from an isolated keyword to a user task and intended canonical asset. ### Document and page design ```text 019-what-is-document-relevancy.md 020-on-page-ranking-factors.md 021-pages-vs-domains.md 022-title-tags-meta-descriptions.md 023-urls.md 024-headers.md 025-body-copy.md 026-image-alt-filename.md 027-internal-links-anchor-text.md 028-site-architecture-silos.md 030-freshness-recency.md 031-ux-signals.md 032-searcher-intent-quality-content-and-competition.md 033-walkthrough-finding-your-low-hanging-fruit.md 034-walkthrough-optimizing-a-blog-post.md ``` The grammar turns checklists into task-specific page specifications and measured interventions. ### Authority and earned evidence ```text 035-link-building-earned-media-authority.md 036-pagerank.md 037-authority-metrics.md 038-follow-vs-nofollow.md 039-ugc-sponsored-attributes.md 040-social-media-link-building-seo.md 041-google-s-medic-update-eat.md 042-link-building-page-types.md 043-negative-seo-and-disavowing-links.md 044-overview-of-prospecting-outreach.md 045-link-prospecting-and-tools.md 046–060 Ahrefs, outreach, and campaign walkthroughs 061-advanced-search-operators.md ``` The grammar broadens authority from raw link counts to relevant independent evidence, qualified referring domains, brand demand, and target-cluster outcomes. ### Technical eligibility ```text 062-what-is-technical-optimization.md 063–069 Google Search Console lessons 070-crawl-indexation-introduction.md 071-crawl-indexation-followed-links-indexed-pages.md 072-crawl-indexation-xml-sitemaps.md 073-crawl-indexation-robots-txt.md 074-crawl-indexation-server-response-codes.md 075-crawl-indexation-redirects.md 076-crawl-indexation-canonical-tags-duplicate-content.md 077-crawl-indexation-keyword-cannibalization.md 078-crawl-indexation-internal-links-crawl-depth.md 079-site-speed.md 080-structured-data.md 081-international-multilingual-seo.md 082-ssl-www-pagination.md 083-demo-technical-seo-audit.md ``` The grammar separates the technical lifecycle into: ```text Discover → Fetch → Render → Canonicalize → Index → Retrieve → Display ``` ### Measurement ```text 084-introduction-to-analytics-tracking.md 085-google-analytics-secure-search.md 086-connecting-google-analytics-and-google-search-console.md 087-google-analytics-google-data-studio.md 088-rank-tracking-link-monitor.md ``` The system extends these lessons into an intervention ledger, task events, qualification, margin, controls, and explicit experiment decisions. --- ## 3. Important terminology corrections ### “LSI keywords” The course uses “LSI” as a broad label for terms that co-occur around a topic. The grammar replaces this with: ```text entities relations attributes values collocations questions evidence ``` These elements should be included because they complete the task, not because a tool produced a term list. ### “One keyword equals one page” Use: ```text one dominant intent cluster = one intended canonical owner ``` A page can be relevant to many query variants. Different words do not automatically require different pages. ### “Ranking factors” Treat lists of factors as hypotheses and diagnostics. The system requires each intervention to state a mechanism and measured outcome. ### “UX signals” Do not claim that any analytics metric perfectly reveals a search engine’s internal behavior. Use user behavior as task and business telemetry. ### “PageRank no longer exists” The public toolbar metric disappeared. Link-based systems and link signals remain conceptually relevant. Do not optimize for an obsolete public score. ### “EAT” Use the current E-E-A-T framing cautiously as a quality-evaluation concept, not a single numeric ranking factor. The operational system measures evidence, experience, authorship, sources, transparency, review, and correction practices. --- ## 4. Current primary-source guidance used The system was checked against current Google Search Central and web.dev guidance available in September 2026. ### Google Search fundamentals - SEO Starter Guide `https://developers.google.com/search/docs/fundamentals/seo-starter-guide` - Search Essentials `https://developers.google.com/search/docs/essentials` - Spam policies `https://developers.google.com/search/docs/essentials/spam-policies` - Creating helpful, reliable, people-first content `https://developers.google.com/search/docs/fundamentals/creating-helpful-content` ### Crawling, indexing, and links - Crawling and indexing overview `https://developers.google.com/search/docs/crawling-indexing` - Link best practices `https://developers.google.com/search/docs/crawling-indexing/links-crawlable` - Canonicalization `https://developers.google.com/search/docs/crawling-indexing/consolidate-duplicate-urls` - Sitemaps `https://developers.google.com/search/docs/crawling-indexing/sitemaps/overview` - JavaScript SEO `https://developers.google.com/search/docs/crawling-indexing/javascript/javascript-seo-basics` - Robots.txt introduction `https://developers.google.com/search/docs/crawling-indexing/robots/intro` ### Search appearance and experience - Structured data introduction `https://developers.google.com/search/docs/appearance/structured-data/intro-structured-data` - Core Web Vitals and Search `https://developers.google.com/search/docs/appearance/core-web-vitals` - Web Vitals `https://web.dev/articles/vitals` ### Generative search - Optimizing for generative AI features on Google Search `https://developers.google.com/search/docs/fundamentals/ai-optimization-guide` Key current implications: ```text foundational SEO still applies; valuable non-commodity content matters; query fan-out expands supporting information needs; a page must be eligible and indexed for Search-based retrieval; a page should not be created for every search variation; scaled low-value content is a governance risk; Google Search does not require llms.txt; AI-specific chunking is not required; supported structured data remains for applicable search features; generative performance should be measured through first-party reporting when available. ``` --- ## 5. Evidence classification Statements in a project should be tagged as: ```text OBSERVATION directly measured or inspected. SOURCE FACT supported by a cited primary source. INFERENCE a reasoned interpretation of observations. FORECAST an estimated future value with assumptions. HYPOTHESIS a testable proposed mechanism. DECISION an action chosen under constraints. UNKNOWN information still required. ``` This prevents forecasts and hypotheses from being presented as established facts. --- ## 6. Versioning The rule library and source guidance should be reviewed when: ```text Google publishes material documentation changes OR site architecture/technology changes OR business offers/audiences change OR measured rules repeatedly fail OR a new search surface becomes strategically important ``` Record: ```text system version rule version source review date changed rules reason migration impact ``` --- # Worked Example — WebDevCalgary.com > This is an illustrative application of the grammar. It deliberately does not invent current search volumes, rankings, or revenue. Those fields must be populated from live first-party and market evidence. ## 1. Business sentence ```text Increase qualified Calgary website-project assessments FOR small and midsize businesses UNDER active website launch, redesign, accessibility, or growth needs SEEKING to choose and hire a web-development solution WITH local commercial-investigation and transactional intent ABOUT web design and development in Calgary SERVED BY a canonical local-service and decision-support system SUPPORTED BY firsthand audits, case evidence, transparent process, and useful tools CONNECTED BY a task-based internal graph LEADING TO a qualification assessment MEASURED BY incremental organic contribution margin GUARDED BY lead quality, delivery capacity, accessibility, accuracy, and trust. ``` --- ## 2. Business value model ```text Business: WebDevCalgary.com Offer: web strategy, design, development, accessibility, SEO, and related consulting Primary audience: Calgary-area organizations seeking a new or improved website Primary value event: qualified project assessment Qualification rule: project fits services, geography, scope, and realistic budget/timeline Primary business metric: incremental organic contribution margin Capacity constraint: must be filled from actual sales and delivery capacity Guardrails: lead quality, response time, close rate, customer fit, accessibility, truthful claims ``` --- ## 3. Audience–task map | Audience | Condition | Task | Intent | Journey state | Next action | |---|---|---|---|---|---| | Local business owner | Needs a provider | Locate and evaluate Calgary web designers | Local commercial | Option evaluation | View service/process or assessment | | Marketing manager | Planning a redesign | Build requirements and compare approaches | Informational/comparative | Problem/solution aware | Download brief or assessment | | Founder | Budgeting | Estimate website cost | Commercial investigation | Evaluation | Use estimator or scope assessment | | Organization with accessibility risk | Existing site may be inaccessible | Diagnose and plan remediation | Diagnostic/commercial | Problem aware | Accessibility audit | | Ecommerce company | Platform or conversion problem | Compare platform/build options | Comparative | Option evaluation | Ecommerce consultation | | Existing client/user | Needs support or improvement | Troubleshoot, maintain, expand | Support/retention | Use/retention | Support or improvement plan | --- ## 4. Semantic territory ### Parent concepts ```text web development web design digital experience website strategy accessibility search optimization conversion design ``` ### Subtypes ```text small-business websites ecommerce websites professional-service websites accessible websites website redesign WordPress development custom development landing pages website maintenance ``` ### Entities ```text Calgary Alberta WordPress Webflow Shopify WCAG Google Search Console Google Analytics ``` ### Attributes ```text price scope timeline platform accessibility performance maintainability ownership support conversion local experience ``` ### Relations ```text WEB_DESIGN LOCATED_IN CALGARY WEBSITE_REQUIREMENTS PRECEDES WEBSITE_REDESIGN WCAG_AUDIT DIAGNOSES ACCESSIBILITY_RISK PLATFORM_SELECTION AFFECTS MAINTAINABILITY CASE_STUDY EVIDENCES DELIVERY_ABILITY COST_ESTIMATOR SUPPORTS PROJECT_ASSESSMENT ``` ### Exclusions ```text web design jobs web developer salary free coding course unrelated Calgary events unsupported service geographies DIY-only intent where no useful business pathway exists ``` --- ## 5. Candidate space Illustrative dimensions: ```text 6 audiences × 12 tasks × 8 intents × 10 service/subtype nodes × 12 modifier families × 8 formats × 4 local scopes × 6 next actions = 1,658,880 theoretical candidates ``` The engine does not publish 1.6 million pages. It normalizes language, groups same tasks, rejects weak combinations, and selects a small portfolio. --- ## 6. Hard-gate example Candidate: ```text "Calgary restaurant website design under $2,000" ``` Evaluate: ```text Demand evidence? UNKNOWN Distinct task? MAYBE Business fit? DEPENDS on offer and budget Information advantage? NOT YET Real local evidence? NOT YET Maintainable? YES at low volume Measurable? YES Policy/accuracy? PASS if truthful ``` Decision: ```text IF live evidence shows a meaningful restaurant-specific task AND the offer actually serves that budget/segment AND unique restaurant evidence exists THEN create a distinct restaurant solution or guide. ELSE include restaurant examples in a broader small-business asset OR reject the candidate. ``` --- ## 7. Initial canonical portfolio | Cluster | Dominant task | Intended canonical role | Likely format | Next action | |---|---|---|---|---| | Calgary web design service | Find, evaluate, hire | Core local service page | Service + process + proof | Qualification assessment | | Website cost in Calgary | Estimate realistic budget | Decision-support asset | Calculator + cost model | Scoped estimate | | Website redesign Calgary | Plan and select redesign help | Service/guide hybrid | Diagnostic + redesign process | Redesign assessment | | Accessible web design Calgary | Diagnose risk and choose help | Specialized service page | Audit evidence + remediation plan | Accessibility audit | | Ecommerce development Calgary | Select ecommerce solution | Specialized service page | Platform and delivery comparison | Ecommerce consultation | | WordPress vs Webflow vs custom | Compare implementation paths | Comparison asset | Decision matrix | Platform assessment | | How to write a website brief | Plan requirements | Supporting guide/template | Downloadable brief | Brief review | | Calgary web design case studies | Verify provider ability | Evidence hub | Case-study collection | Relevant service | | Website maintenance Calgary | Keep site reliable | Retention/service page | Service + checklist | Maintenance assessment | | Calgary web-design company comparison | Compare provider types | Neutral decision guide | Criteria matrix | Assessment after criteria | This is a provisional architecture. Live result sets, customer language, query evidence, existing URLs, and business data determine final boundaries. --- ## 8. Same-page / split examples ### Example A ```text web design Calgary Calgary web designer website design company Calgary ``` Likely decision: ```text same sense AND same dominant task AND same local service result class AND same next action → one canonical service cluster ``` ### Example B ```text web design Calgary website cost Calgary ``` Likely decision: ```text related concept BUT different task AND different answer structure AND different journey stage → separate clusters connected by internal links ``` ### Example C ```text Calgary WordPress developer Calgary Webflow developer ``` Decision depends on the offer and result ecosystem: ```text IF platform choice is part of one broader selection task THEN one comparison/service architecture may suffice. ELSE IF each platform has distinct demand, proof, process, and offer THEN split into platform-specific clusters. ``` --- ## 9. Page specification — Website cost in Calgary ```text Cluster ID: YYC-COST-001 Dominant task: estimate the likely cost and scope of a Calgary business website Intent: commercial investigation Journey state: evaluation Representative query: website cost Calgary Canonical role: cost decision-support asset Recommended format: calculator + pricing bands + scope matrix + examples Information advantage: transparent local assumptions, real project patterns, accessible estimator Evidence: disclosed methodology, case ranges where permission exists, explicit exclusions Next action: save result or request a scoped assessment Primary metric: qualified assessment contribution value Guardrails: estimator accuracy, unqualified inquiry rate, delivery capacity ``` ### Required sections ```text Direct answer and range disclaimer What changes the cost Project-type matrix Calgary/Alberta-specific assumptions where real Calculator Examples or anonymized scope patterns What is not included DIY, template, freelancer, agency, and custom trade-offs Timeline implications Questions to ask a provider Next-step assessment Methodology and update date ``` --- ## 10. LAKA 50-cell example for the cost asset | Variable | Baseline | Minor | Major | Structural | Paradigm | |---|---|---|---|---|---| | Object | Existing cost content and query behavior | Title/snippet/direct answer | Full cost guide and evidence | Connect estimator, CRM, service pages, case data | Live project-scope intelligence product | | Conditions | Local users, device, query mix, current offers | High impressions or weak CTR | Weak task completion or inferior format | Repeated cost questions across journeys | Market lacks transparent usable estimates | | Actions | Measure and classify | Rewrite proposition/CTA | Build matrix, examples, calculator | Integrate data and graph | Build adaptive scope engine | | Tools | Search Console, analytics, CRM | CMS, change ledger | Calculator, content, design | CRM/API, event pipeline | Rules engine, dataset, agent interface | | Resources | Existing data | Copy/design time | Project evidence and development | Engineering and sales operations | Proprietary data and product maintenance | | Outcomes | Trusted baseline | Better qualified clicks/action | Better task completion and leads | Closed-loop forecast calibration | New demand, citations, product adoption | | Feedback | Query, CTR, conversion | CTR residual and quality | completion, qualification, close rate | estimate-vs-actual error | market usage, links, brand, margin | | Constraints | Data gaps | Snippet rewrite uncertainty | Range accuracy and disclosure | Privacy and data quality | Build cost and defensibility | | Value | Opportunity quantified | Low-cost response lift | Better decisions and pipeline | Better pricing/qualification | Category-defining utility | | Failure mode | Wrong baseline | Clickbait or low-quality traffic | Misleading estimates | Bad CRM data propagates | Complex tool with no adoption | --- ## 11. IF / ELSE program for the cost asset ```text IF the existing page has meaningful impressions AND selected canonical is correct AND qualified conversion is possible THEN optimize the existing asset before creating a replacement. ELSE IF multiple cost pages compete for the same task THEN select one owner, merge useful information, and migrate carefully. ELSE IF no useful cost asset exists AND demand/business gates pass THEN create the canonical estimator/guide. IF users complete the estimator BUT do not take the next action THEN test value continuity, trust, qualification, and CTA commitment. IF the calculator produces many unqualified inquiries THEN tighten audience conditions, assumptions, outputs, or routing. IF the tool earns citations and branded demand THEN compound it with annual benchmarks, platform views, and case evidence. ELSE maintain it as a decision-support asset without uncontrolled expansion. ``` --- ## 12. Internal graph ```text /calgary-web-design/ [core local service] ↑ supported by /website-cost-calgary/ /website-redesign-calgary/ /website-brief-template/ /web-design-company-comparison/ /case-studies/ website cost → platform comparison → website brief → relevant case study → scoped assessment accessibility service ← WCAG diagnostic guide ← accessibility case study → accessibility audit ``` Every edge needs a user reason. Do not add links solely to make the diagram denser. --- ## 13. Measurement plan ### Executive ```text incremental organic contribution margin qualified organic assessments value-weighted non-brand clicks value-weighted priority-cluster visibility eligible canonical coverage ``` ### Cluster diagnostics ```text impressions CTR residual dominant URL share task completion next-action rate qualified rate close rate contribution value ``` ### Cost-estimator task events ```text estimator_start estimator_complete result_band assumption_expand methodology_view brief_download assessment_start qualified_assessment sales_accept closed_value ``` Do not collect sensitive inputs unnecessarily. --- ## 14. First execution order ```text 1. Verify measurement and qualified-value chain. 2. Audit existing URL/index/canonical state. 3. Build current query-to-URL clusters. 4. Fix high-value cannibalization and technical blockers. 5. Improve existing pages with signal. 6. Build the cost estimator and core service proof where gaps exist. 7. Build internal graph and supporting task assets. 8. Launch evidence/authority campaigns. 9. Test selected platform, industry, or neighborhood expansions only after hard gates pass. 10. Pursue paradigm tools from observed user needs, not from page-volume goals. ```