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E-E-A-T Factor Extractor — Signal Mining from URLs and Content

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Extracts E-E-A-T signals from any URL or content block: identifies experience markers, expertise indicators, authoritativeness anchors, and trust elements present or absent. Produces a signal inventory and gap map for targeted E-E-A-T improvement.

seoeeatcontent-qualitysignal-extractionaudit
Agent trigger phrases: EEAT factor extractor · extract EEAT signals · EEAT signal mining · find EEAT signals · EEAT inventory · EEAT signal audit · experience markers extractor · EEAT gap map

What Factor Extraction Differs From Scoring

eeat-analyzer assigns scores (1-10 per dimension). eeat-factor-extractor inventories what signals exist and which are absent — the diagnostic layer before scoring. Use this when you need to understand exactly which E-E-A-T signals are present on a page before deciding what to add or remove.

Signal Extraction by Dimension

Experience Signal Inventory

Scan the content for these experience signal types:

Explicit first-person experience markers:

  • First-person pronoun + action + specific context ("When I replaced the roof on a 1960s Tampa bungalow...")
  • Named projects or locations ("On a job in Seminole Heights last spring...")
  • Specific outcomes with numbers ("reduced callbacks by 80% after switching to metal")
  • Before/after specifics ("the decking had 40% rot we had to replace")
  • Time-anchored experiences ("In 15 years of roofing in Florida's hurricane zone...")

Implicit experience markers:

  • Product/material brand names used in context (not as advertising but as working knowledge)
  • Tool or technique specificity ("we use 6d ring-shank nails on deck fastening, not 8d common")
  • Process variation acknowledgment ("this varies depending on the decking material")
  • Failure case knowledge ("the most common reason Tampa roofs fail early is...")

Extract: Pull every sentence containing first-person pronouns + specific technical context. Count explicit vs implicit markers. Flag pages with zero explicit markers as Experience-deficient.

Expertise Signal Inventory

Credential signals:

  • Author name + title in byline
  • License number visible on page
  • Certification names (specific, not generic — "GAF Master Elite Certified" not "certified installer")
  • Years in practice stated
  • Educational credentials (specific degrees/programs, not "formally trained")
  • Professional association memberships with links

Knowledge-depth signals:

  • Technical terminology used correctly in context
  • Edge case acknowledgment ("This doesn't apply if the substrate is OSB vs CDX plywood")
  • Common misconception correction ("Most homeowners think X, but actually Y")
  • Comparative analysis with specific differentiators (not just "option A vs option B")
  • Regulatory or code citations (actual code section numbers)

Extract: List all credential mentions and verify they appear with specifics (a credential without the specific certifying body or number is weak). List all technical terms and verify they're used correctly. Flag pages where all technical content could be written by a generalist researcher.

Authoritativeness Signal Inventory

Internal authority signals:

  • Author bio linked to dedicated author page
  • Author's other articles or publications linked
  • Author's social profiles linked (LinkedIn preferred for professional authority)
  • Company About page linked from content

External authority signals:

  • Outbound links to authoritative sources: government sites (.gov), academic (.edu), industry associations
  • Industry association membership badges or logos with verification links
  • Awards or recognition from named third parties (with links to the awarding organization)
  • Press mentions or media coverage referenced with links
  • Expert quotes from named, verifiable external experts

Citation quality check:

  • Are sources linked (not just referenced)?
  • Are sources authoritative and current (not Wikipedia or blogs)?
  • Do citations support specific claims (not just generic domain links)?

Extract: Inventory all outbound links by domain type. Count author credential mentions. Flag pages with no external links or no author identification.

Trustworthiness Signal Inventory

Contact and business verification:

  • Physical address visible on page (or site-wide)
  • Phone number visible
  • Email or contact form accessible
  • Business hours stated (for service businesses)

Legal and compliance signals:

  • Privacy policy linked (site-wide footer)
  • Terms of service linked
  • Cookie consent mechanism
  • Return/refund policy visible on transactional pages

Third-party verification:

  • BBB rating badge with verification link
  • Google Reviews count and rating visible
  • License number with state licensing board verification link
  • Insurance certificates (for contractors)
  • Professional liability / bond information

Content accuracy signals:

  • Sources cited for statistical claims
  • Date stamps on factual content
  • "Last updated" date for evergreen content
  • Clear distinction between facts and opinions

Extract: Check presence/absence of each signal category. The most common missing signals in local service sites: no physical address on inner pages, no license verification link, no date on blog content.

Gap Map Output Format

After extraction, produce a structured gap map:

PAGE: [URL]
ANALYZED: [date]

EXPERIENCE SIGNALS FOUND:
- [List present signals with brief location note]

EXPERIENCE GAPS:
- [Missing signals, prioritized by impact]

EXPERTISE SIGNALS FOUND:
- [List present signals]

EXPERTISE GAPS:
- [Missing signals]

AUTHORITATIVENESS SIGNALS FOUND:
- [List present signals]

AUTHORITATIVENESS GAPS:
- [Missing signals]

TRUSTWORTHINESS SIGNALS FOUND:
- [List present signals]

TRUSTWORTHINESS GAPS:
- [Missing signals]

PRIORITY ADDITIONS (ranked by impact/effort ratio):
1. [Highest impact, easiest to add]
2. [Second priority]
3. [Third priority]

Automated Extraction Workflow

For bulk extraction across multiple pages:

  1. Crawl target URLs with LibreCrawl (export body text)
  2. For each page body text, run regex/NLP scan for:
    • First-person pronouns in technical context
    • Credential keyword list (license, certified, years, member of, BBB)
    • External domain links (classify as .gov, .edu, industry, general)
    • Contact information patterns (phone, address, email)
  3. Output gap map per URL
  4. Sort by E-E-A-T signal count (lowest = highest remediation priority)

Cross-References

  • eeat-analyzer — scoring layer that operates on the signals this extractor finds
  • eeat-audit — full pipeline combining extraction, scoring, and HCU audit
  • content-mastery — content quality standards that drive E-E-A-T signals
  • seo-prompt-frameworks — prompts for adding E-E-A-T signals to existing content

#seo-sop #seo #eeat #content-quality #signal-extraction #audit

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