Document 10

Course Crosswalk and Sources

Course mapping and current primary 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This system preserves the course’s practical workflow while replacing ambiguous or outdated labels with measurable technical concepts.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 — 28 rows
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

The grammar converts the course’s persona, asset, medium, optimization, and nudge model into:

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

Audience
+ Conditions
+ Task
+ Intent
+ Canonical asset
+ Search surface
+ Next action
+ Business outcome

Semantic research and mapping

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.

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

Document and page design

The grammar turns checklists into task-specific page specifications and measured interventions.

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

Authority and earned evidence

The grammar broadens authority from raw link counts to relevant independent evidence, qualified referring domains, brand demand, and target-cluster outcomes.

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

Technical eligibility

The grammar separates the technical lifecycle into:

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

Discover
→ Fetch
→ Render
→ Canonicalize
→ Index
→ Retrieve
→ Display

Measurement

The system extends these lessons into an intervention ledger, task events, qualification, margin, controls, and explicit experiment decisions.

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

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:

These elements should be included because they complete the task, not because a tool produced a term list.

entities
relations
attributes
values
collocations
questions
evidence

“One keyword equals one page”

Use:

A page can be relevant to many query variants. Different words do not automatically require different pages.

one dominant intent cluster
=
one intended canonical owner

“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

SEO Starter Guide
Search Essentials
Spam policies
Creating helpful, reliable, people-first 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

Crawling and indexing overview
Link best practices
Canonicalization
Sitemaps
JavaScript SEO
Robots.txt introduction

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

Structured data introduction
Core Web Vitals and Search
Web Vitals

Generative search

- Optimizing for generative AI features on Google Search

https://developers.google.com/search/docs/fundamentals/ai-optimization-guide

Key current implications:

Optimizing for generative AI features on Google Search

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:

This prevents forecasts and hypotheses from being presented as established facts.

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.

6. Versioning

The rule library and source guidance should be reviewed when:

Record:

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

system version
rule version
source review date
changed rules
reason
migration impact

This document as JSON: GET /v1/documents/course-crosswalk-and-sources · raw markdown

← All documents