Local Search & Entity Resolution: The Semantics of Trust and Location
Search engines have evolved from matching strings to resolving 'things.' This guide explores the engineering behind Entity-Based Search—how algorithms verify identity through local signals (NAP consistency), quantify trust via E-E-A-T metrics, and map relationships using ontologies like Wikidata.
Local SEO
Google Business Profile Optimization
Google Business Profile (GBP) is the cornerstone of local SEO—it's your digital storefront on Google Search and Maps. Optimization involves completing every field (categories, attributes, services, products), adding high-quality photos weekly, posting updates regularly, enabling messaging, and maintaining accurate business hours including special hours for holidays.
┌─────────────────────────────────────────────────────────┐ │ GOOGLE BUSINESS PROFILE CHECKLIST │ ├─────────────────────────────────────────────────────────┤ │ ✓ Primary + Secondary Categories │ │ ✓ Complete Business Description (750 chars) │ │ ✓ Services/Products with Descriptions │ │ ✓ Attributes (wheelchair accessible, Wi-Fi, etc.) │ │ ✓ Photos: Logo, Cover, Interior, Exterior, Team │ │ ✓ Business Hours + Special Hours │ │ ✓ Q&A Section (seed with common questions) │ │ ✓ Weekly Posts (Events, Offers, Updates) │ │ ✓ Messaging Enabled │ │ ✓ Booking/Appointment Links │ └─────────────────────────────────────────────────────────┘
Local Pack Ranking Factors
The Local Pack (3-pack) ranking is determined by three primary factors: Relevance (how well your listing matches search intent), Distance (proximity to searcher), and Prominence (how well-known/authoritative your business is online through reviews, links, citations, and overall web presence).
LOCAL PACK RANKING ALGORITHM ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ RELEVANCE │ │ DISTANCE │ │ PROMINENCE │ │ │ │ │ │ │ │ • Category │ │ • Searcher │ │ • Reviews │ │ • Keywords │ │ Location │ │ • Citations │ │ • Services │ │ • Service │ │ • Links │ │ • Attributes│ │ Area │ │ • Authority │ └──────┬──────┘ └──────┬──────┘ └──────┬──────┘ │ │ │ └──────────────────┼──────────────────┘ ▼ ┌─────────────────┐ │ LOCAL PACK │ │ POSITION │ └─────────────────┘
NAP Consistency
NAP (Name, Address, Phone) consistency means your business information must be identical across all online platforms—your website, GBP, directories, social media, and citations. Even minor variations (St. vs Street, Suite vs Ste) can confuse search engines and dilute your local ranking signals.
❌ INCONSISTENT NAP: ┌────────────────────────────────────────────────────────┐ │ Website: "Bob's Pizza, 123 Main Street, Suite 100" │ │ GBP: "Bob's Pizza LLC, 123 Main St, Ste 100" │ │ Yelp: "Bobs Pizza, 123 Main St #100" │ │ Facebook: "Bob's Pizza Restaurant, 123 Main Street" │ └────────────────────────────────────────────────────────┘ ✅ CONSISTENT NAP: ┌────────────────────────────────────────────────────────┐ │ Website: "Bob's Pizza | 123 Main St, Suite 100" │ │ GBP: "Bob's Pizza | 123 Main St, Suite 100" │ │ Yelp: "Bob's Pizza | 123 Main St, Suite 100" │ │ Facebook: "Bob's Pizza | 123 Main St, Suite 100" │ └────────────────────────────────────────────────────────┘
Local Citations
Local citations are online mentions of your business NAP on directories, websites, apps, and social platforms. They act as trust signals validating your business existence and are divided into structured (directory listings like Yelp, Yellow Pages) and unstructured (mentions in blogs, news articles, forum posts).
CITATION PRIORITY PYRAMID ▲ /█\ Tier 1: Primary Aggregators /███\ (Data Axle, Localeze, Foursquare) /█████\ /███████\ Tier 2: Major Platforms /█████████\ (Yelp, Apple Maps, Bing, Facebook) /███████████\ /█████████████\ Tier 3: Industry Directories /███████████████\ (TripAdvisor, Healthgrades, Avvo) /█████████████████\ /███████████████████\ Tier 4: Local/Niche Directories /█████████████████████\(Chamber of Commerce, Local blogs) ━━━━━━━━━━━━━━━━━━━━━━━━━
Review Management
Review management involves actively soliciting reviews, monitoring them across platforms, responding promptly (especially to negative reviews within 24-48 hours), analyzing sentiment for business insights, and maintaining a steady flow of fresh reviews—Google values recency, quantity, quality, and owner response rate.
# Example: Automated Review Response Classification def classify_review(rating, text): response_templates = { 'positive': "Thank you {name}! We're thrilled you enjoyed {highlight}.", 'neutral': "Thanks for your feedback, {name}. We'd love to learn more.", 'negative': "We're sorry to hear this, {name}. Please contact us at..." } if rating >= 4: return 'positive', prioritize_response(hours=48) elif rating == 3: return 'neutral', prioritize_response(hours=24) else: return 'negative', prioritize_response(hours=4) # URGENT # Review velocity target: 2-5 new reviews per month minimum
Local Schema Markup
Local Business schema is structured data (JSON-LD) that helps search engines understand your business details—location, hours, services, reviews—and can enable rich results like star ratings in search. It's critical for local SEO and should be implemented on every location page.
{ "@context": "https://schema.org", "@type": "LocalBusiness", "@id": "https://example.com/#business", "name": "Bob's Pizza", "image": "https://example.com/photos/storefront.jpg", "telephone": "+1-555-123-4567", "address": { "@type": "PostalAddress", "streetAddress": "123 Main St, Suite 100", "addressLocality": "Austin", "addressRegion": "TX", "postalCode": "78701", "addressCountry": "US" }, "geo": { "@type": "GeoCoordinates", "latitude": 30.2672, "longitude": -97.7431 }, "openingHoursSpecification": [ { "@type": "OpeningHoursSpecification", "dayOfWeek": ["Monday","Tuesday","Wednesday","Thursday","Friday"], "opens": "11:00", "closes": "22:00" } ], "aggregateRating": { "@type": "AggregateRating", "ratingValue": "4.8", "reviewCount": "256" }, "priceRange": "$$" }
Geo-Targeted Landing Pages
Geo-targeted landing pages are location-specific pages designed to rank for "[service] in [city]" searches. Each page must contain unique, valuable content—not just template swaps—including local testimonials, area-specific services, local landmarks/references, embedded maps, and location-specific schema.
LANDING PAGE STRUCTURE FOR: "plumber in austin tx" ┌─────────────────────────────────────────────────────────┐ │ URL: /plumbing-services/austin-tx/ │ ├─────────────────────────────────────────────────────────┤ │ H1: Professional Plumbing Services in Austin, TX │ │ │ │ ┌─────────────────────┐ ┌──────────────────────────┐ │ │ │ Unique local intro │ │ Embedded Google Map │ │ │ │ mentioning Austin │ │ with service area │ │ │ │ neighborhoods │ └──────────────────────────┘ │ │ └─────────────────────┘ │ │ │ │ H2: Areas We Serve in Austin │ │ • Downtown Austin • South Congress • East Austin │ │ │ │ H2: Austin Customer Reviews (location-specific) │ │ [Review from verified Austin customer] │ │ │ │ LocalBusiness Schema + Service Schema │ └─────────────────────────────────────────────────────────┘
Local Link Building
Local link building focuses on acquiring backlinks from geographically relevant sources: local news sites, community organizations, chambers of commerce, local bloggers, sponsorships of local events/teams, partnerships with nearby businesses, local university/college sites, and local resource pages.
LOCAL LINK BUILDING OPPORTUNITIES ┌─────────────────────────────────────────────────────────┐ │ HIGH VALUE │ │ ├── Local news sites (.com domains with city focus) │ │ ├── Chamber of Commerce member directory │ │ ├── Local .edu links (scholarships, resources) │ │ └── City/County .gov resource pages │ │ │ │ MEDIUM VALUE │ │ ├── Local blogger reviews/features │ │ ├── Community event sponsorships │ │ ├── Local business associations │ │ └── Neighborhood websites/forums │ │ │ │ ONGOING │ │ ├── Local charity partnerships │ │ ├── Sports team/school sponsorships │ │ └── Cross-promotions with complementary businesses │ └─────────────────────────────────────────────────────────┘
Multi-Location SEO
Multi-location SEO involves managing separate GBP listings, unique landing pages, and distinct citation profiles for each business location while maintaining brand consistency. Key challenges include avoiding duplicate content, managing reviews at scale, and establishing local authority for each location independently.
MULTI-LOCATION SITE ARCHITECTURE example.com │ ┌─────────────┼─────────────┐ │ │ │ ▼ ▼ ▼ /locations/ /locations/ /locations/ austin-tx dallas-tx houston-tx │ │ │ ┌─────┴─────┐ ┌─────┴─────┐ ┌─────┴─────┐ │ │ │ │ │ │ ▼ ▼ ▼ ▼ ▼ ▼ /services Unique /services Unique /services /reviews Content /reviews Content /reviews /team + NAP /team + NAP /team Each location page needs: ✓ Unique H1 with city name ✓ Unique intro paragraph (not templated) ✓ Location-specific reviews ✓ Unique photos of that location ✓ Individual LocalBusiness schema ✓ Separate GBP listing linked via CID
Service Area Business Optimization
Service Area Businesses (SABs) serve customers at their location (plumbers, cleaners, mobile services) rather than at a storefront. In GBP, you hide your address, define service areas (up to 20 cities or a radius), and optimize for "near me" searches through strong review profiles and service-area landing pages.
SAB vs STOREFRONT CONFIGURATION ┌─────────────────────────────────────────────────────────┐ │ SERVICE AREA BUSINESS (SAB) │ ├─────────────────────────────────────────────────────────┤ │ GBP Settings: │ │ ☐ Show business address (HIDE for pure SAB) │ │ ☑ I deliver goods and services to my customers │ │ │ │ Service Areas: (define up to 20) │ │ ┌─────────────────────────────────────────────┐ │ │ │ • Austin, TX • Round Rock, TX │ │ │ │ • Cedar Park, TX • Pflugerville, TX │ │ │ │ • Georgetown, TX • Leander, TX │ │ │ └─────────────────────────────────────────────┘ │ │ │ │ NOTE: 2-hour driving distance max recommended │ └─────────────────────────────────────────────────────────┘ HYBRID (Storefront + Service Area): ☑ Show business address ☑ I also serve customers at their location
Local Keyword Optimization
Local keyword optimization involves researching and targeting location-modified search terms: "[service] + [city]", "[service] near me", "[service] in [neighborhood]". Focus on mapping keywords to intent, incorporating them naturally in titles, headers, content, URLs, and meta descriptions while including neighborhood/landmark variations.
LOCAL KEYWORD MAPPING ┌─────────────────────────────────────────────────────────────┐ │ PRIMARY KEYWORDS SEARCH VOLUME INTENT │ ├─────────────────────────────────────────────────────────────┤ │ plumber austin tx 2,400/mo Transactional │ │ emergency plumber austin 880/mo Urgent │ │ plumber near me 12K/mo Local implicit │ │ austin plumbing services 720/mo Transactional │ ├─────────────────────────────────────────────────────────────┤ │ SECONDARY (NEIGHBORHOODS) │ ├─────────────────────────────────────────────────────────────┤ │ plumber south austin 210/mo Geo-modified │ │ downtown austin plumber 90/mo Geo-modified │ │ east austin plumber 110/mo Geo-modified │ ├─────────────────────────────────────────────────────────────┤ │ LONG-TAIL │ ├─────────────────────────────────────────────────────────────┤ │ 24 hour plumber austin tx 170/mo Urgent+Local │ │ water heater repair austin 320/mo Service+Local │ └─────────────────────────────────────────────────────────────┘
Google Maps Optimization
Google Maps optimization extends beyond GBP to focus on map-specific ranking factors: accurate pin placement, driving directions verification, photo geotagging, encouraging check-ins, embedding maps on your site, and ensuring your listing appears correctly across Google's mapping ecosystem including navigation and local discovery.
GOOGLE MAPS OPTIMIZATION CHECKLIST ┌─────────────────────────────────────────────────────────┐ │ PIN & LOCATION │ │ ☑ Verify pin is exactly on building (not parking lot) │ │ ☑ Test driving directions from multiple starting points │ │ ☑ Claim Google Maps listing matches GBP │ │ │ │ PHOTOS (GEO-TAGGED) │ │ ☑ Upload photos with EXIF GPS data intact │ │ ☑ Or use: exiftool -GPSLatitude=30.2672 photo.jpg │ │ │ │ ENGAGEMENT SIGNALS │ │ ☑ Encourage customers to check-in on Maps │ │ ☑ Request photos from customers │ │ ☑ Monitor and answer Q&A on Maps │ │ │ │ WEBSITE INTEGRATION │ │ ☑ Embed Google Maps iframe on contact/location page │ │ ☑ Use Maps link: google.com/maps?cid=YOUR_CID │ │ ☑ Add driving directions link │ └─────────────────────────────────────────────────────────┘
E-E-A-T Optimization
Experience Signals
Experience (the first E in E-E-A-T) demonstrates first-hand, real-world involvement with the topic—showing you've actually used products, visited places, or performed the services you're writing about. Signals include original photos, personal anecdotes, specific details only a user would know, and timestamps showing ongoing engagement.
EXPERIENCE SIGNALS TO IMPLEMENT ┌─────────────────────────────────────────────────────────┐ │ CONTENT SIGNALS │ │ ├── First-person narratives ("I tested...", "When I") │ │ ├── Original photos (with EXIF data) not stock images │ │ ├── Screenshots of actual usage/results │ │ ├── Specific details (model numbers, exact steps) │ │ └── Dated experiences ("In March 2024, I...") │ │ │ │ TECHNICAL SIGNALS │ │ ├── Author schema with experiential credentials │ │ ├── Image metadata showing authenticity │ │ └── Review/testimonial dates and specificity │ │ │ │ WEAK (Avoid) │ STRONG (Aim For) │ │ "This product is great" │ "After 6 months of daily │ │ │ use, the battery still │ │ │ holds 8+ hours..." │ └─────────────────────────────────────────────────────────┘
Expertise Demonstration
Expertise signals convey deep knowledge through credentials, detailed explanations, original research, data analysis, and content that goes beyond surface-level information. For YMYL topics, formal qualifications matter; for other topics, demonstrated knowledge depth and track record suffice.
EXPERTISE PYRAMID ▲ /█\ Formal Credentials /███\ (MD, PhD, CPA, Licensed) /█████\ /███████\ Industry Recognition /█████████\ (Awards, Publications, Speaking) /███████████\ /█████████████\ Demonstrated Knowledge /███████████████\ (Depth, Original Research) /█████████████████\ /███████████████████\Practical Track Record /█████████████████████\(Portfolio, Case Studies, Years) ━━━━━━━━━━━━━━━━━━━━━━━━━ IMPLEMENTATION: ┌──────────────────────────────────────────────────┐ │ • Display credentials near author name/bio │ │ • Link to published works, patents, research │ │ • Show relevant certifications with links │ │ • Include case studies with measurable results │ │ • Reference tools/methods unique to experts │ └──────────────────────────────────────────────────┘
Authoritativeness Building
Authoritativeness reflects how recognized you or your site is as a go-to source in your niche—built through quality backlinks from authoritative sites, brand mentions, press coverage, industry citations, speaking engagements, and a consistent publishing history that establishes topical authority over time.
AUTHORITY BUILDING FRAMEWORK EXTERNAL SIGNALS ┌─────────────────────────────────┐ │ • Backlinks from .edu, .gov │ │ • Press/media mentions │ │ • Industry publication cites │ │ • Expert quote requests │ │ • Wikipedia/Wikidata refs │ └───────────────┬─────────────────┘ │ ▼ ┌──────────────────────────────────────────────┐ │ YOUR AUTHORITY │ └──────────────────────────────────────────────┘ ▲ │ ┌───────────────┴─────────────────┐ │ • Topical depth (content hub) │ │ • Publication consistency │ │ • Social proof/following │ │ • Brand search volume │ │ • Industry partnerships │ └─────────────────────────────────┘ INTERNAL SIGNALS
Trustworthiness Factors
Trustworthiness is the most critical E-E-A-T component—it encompasses site security (HTTPS), transparent ownership/contact info, clear policies (privacy, returns), accurate content with citations, no deceptive practices, and positive reputation signals including reviews and BBB ratings.
TRUST CHECKLIST ┌─────────────────────────────────────────────────────────┐ │ TECHNICAL TRUST │ │ ☑ HTTPS with valid SSL certificate │ │ ☑ Clear privacy policy and ToS │ │ ☑ Accessible contact information │ │ ☑ Physical address (especially for e-commerce) │ │ │ │ CONTENT TRUST │ │ ☑ Sources cited with links to original │ │ ☑ Dates on content (published + last updated) │ │ ☑ Corrections/updates policy │ │ ☑ Fact-checking process disclosed │ │ │ │ REPUTATION TRUST │ │ ☑ Positive reviews on third-party sites │ │ ☑ BBB rating / industry accreditations │ │ ☑ No history of scams/deceptive practices │ │ ☑ Transparent ownership (About/Team pages) │ │ │ │ TRANSACTIONAL TRUST (E-commerce) │ │ ☑ Secure checkout indicators │ │ ☑ Clear return/refund policies │ │ ☑ Customer service contact options │ │ ☑ Trust badges (verified, payment security) │ └─────────────────────────────────────────────────────────┘
Author Entity Optimization
Author entity optimization establishes authors as recognized entities in Google's Knowledge Graph by creating consistent author identities across the web—linking author pages to social profiles, published works, and authoritative bios using sameAs schema, building a web of connected references that Google can validate.
{ "@context": "https://schema.org", "@type": "Person", "@id": "https://example.com/authors/jane-smith#person", "name": "Jane Smith, MD", "jobTitle": "Chief Medical Officer", "description": "Board-certified physician with 15 years experience", "image": "https://example.com/images/jane-smith.jpg", "url": "https://example.com/authors/jane-smith", "sameAs": [ "https://twitter.com/drjanesmith", "https://linkedin.com/in/drjanesmith", "https://www.wikidata.org/wiki/Q123456789", "https://orcid.org/0000-0002-1234-5678" ], "alumniOf": { "@type": "CollegeOrUniversity", "name": "Harvard Medical School" }, "hasCredential": { "@type": "EducationalOccupationalCredential", "credentialCategory": "Medical License", "recognizedBy": { "@type": "Organization", "name": "American Board of Internal Medicine" } } }
About Page Optimization
The About page is crucial for E-E-A-T—it should clearly explain who you are, your company's mission, team credentials, history, achievements, and contact details. Include structured data (Organization schema), links to press coverage, awards, and make it easy for Quality Raters to verify your legitimacy.
ABOUT PAGE STRUCTURE ┌─────────────────────────────────────────────────────────┐ │ ABOUT [BRAND NAME] │ ├─────────────────────────────────────────────────────────┤ │ │ │ COMPANY STORY │ │ Founded in [year], our mission is... │ │ [Brief history, milestones, growth] │ │ │ │ OUR TEAM ┌─────────────────────────────┐ │ │ ├── CEO/Founder ────>│ Photo, Bio, Credentials, │ │ │ ├── Key Expert ────>│ Links to LinkedIn/Twitter │ │ │ └── Team Members ────>│ Link to full author pages │ │ │ └─────────────────────────────┘ │ │ │ │ CREDENTIALS & RECOGNITION │ │ • Awards and certifications (with logos) │ │ • Press mentions (As seen in: Forbes, NYT...) │ │ • Industry memberships │ │ │ │ CONTACT INFORMATION │ │ • Physical address • Phone • Email │ │ • Social media links │ │ │ │ [Organization Schema with sameAs, founders, awards] │ └─────────────────────────────────────────────────────────┘
Author Pages and Bios
Author pages are dedicated pages for each content creator featuring their credentials, expertise areas, published content list, external profiles, and schema markup. Bios on articles should include a photo, credentials, link to the full author page, and establish why this person is qualified to write on this topic.
<!-- Author Box on Article --> <div class="author-box" itemscope itemtype="https://schema.org/Person"> <img itemprop="image" src="/authors/jane-smith.jpg" alt="Dr. Jane Smith"> <div class="author-info"> <span itemprop="name">Dr. Jane Smith, MD</span> <span itemprop="jobTitle">Board-Certified Cardiologist</span> <p itemprop="description"> Dr. Smith has 15 years of clinical experience and has published 30+ peer-reviewed papers on cardiovascular health. </p> <a href="/authors/jane-smith" itemprop="url">View Full Bio →</a> <div class="social-links"> <a itemprop="sameAs" href="https://linkedin.com/in/drjanesmith">LinkedIn</a> <a itemprop="sameAs" href="https://twitter.com/drjanesmith">Twitter</a> </div> </div> </div>
Credentials and Citations
Credentials and citations validate expertise by displaying verifiable qualifications (degrees, certifications, licenses) and backing claims with references to authoritative sources. For YMYL content especially, every factual claim should cite peer-reviewed studies, official sources, or recognized experts.
CREDENTIAL DISPLAY PATTERN ┌─────────────────────────────────────────────────────────┐ │ AUTHOR CREDENTIALS (Make Verifiable) │ │ │ │ ✓ "Jane Smith, MD, FACC" │ │ └── Link to medical license verification │ │ └── Link to FACC (Fellow of ACC) directory │ │ │ │ ✓ "15 years clinical experience at Mayo Clinic" │ │ └── LinkedIn profile corroborates │ │ │ │ ✓ "Published in New England Journal of Medicine" │ │ └── Direct link to publication │ └─────────────────────────────────────────────────────────┘ CITATION FORMAT IN CONTENT "Aspirin reduces heart attack risk by 25% in high-risk patients.[1]" ──────────────────────────────────────────────── REFERENCES: [1] Smith J, et al. "Aspirin in Cardiovascular Prevention." N Engl J Med. 2023;388:1234-1245. doi:10.1056/NEJMoa2304561 ← Direct DOI link
Expert Review Implementation
Expert review (also called medical/legal/financial review) involves having qualified professionals review content before publication, especially for YMYL topics. Display the reviewer's credentials prominently, show the review date, and link to their authoritative profile—this signals to Google that content has been vetted.
EXPERT REVIEW DISPLAY PATTERN ┌─────────────────────────────────────────────────────────┐ │ ARTICLE HEADER │ │ │ │ Written by: John Doe, Health Writer │ │ Medically reviewed by: Dr. Sarah Chen, MD, FACP │ │ Last reviewed: March 15, 2024 │ │ │ │ ┌───────────────────────────────────────────────────┐ │ │ │ ✓ Expert Reviewed │ │ │ │ This article was reviewed by a board-certified │ │ │ │ physician for medical accuracy. │ │ │ │ [View reviewer credentials] │ │ │ └───────────────────────────────────────────────────┘ │ └─────────────────────────────────────────────────────────┘
{ "@context": "https://schema.org", "@type": "Article", "author": {"@id": "https://example.com/authors/john-doe#person"}, "reviewedBy": { "@type": "Person", "name": "Dr. Sarah Chen, MD, FACP", "sameAs": "https://linkedin.com/in/drsarahchen", "hasCredential": { "@type": "EducationalOccupationalCredential", "credentialCategory": "Board Certification" } }, "lastReviewed": "2024-03-15" }
Trust Signals
Trust signals are UI/UX elements and content markers that reinforce credibility: security badges, professional certifications displayed, real testimonials with full names/photos, transparent correction policies, physical address visibility, clear editorial standards, and third-party verification badges.
TRUST SIGNALS PLACEMENT ┌─────────────────────────────────────────────────────────┐ │ HEADER │ │ [SSL Lock] Secure | BBB A+ | Call: (555) 123-4567 │ ├─────────────────────────────────────────────────────────┤ │ │ │ CONTENT AREA │ │ ┌────────────────────────────────────────────────────┐ │ │ │ ★★★★★ "Excellent service!" - John S., Austin TX │ │ │ │ Verified Purchase ✓ │ │ │ └────────────────────────────────────────────────────┘ │ │ │ │ SIDEBAR │ │ ┌──────────────┐ │ │ │ AS SEEN IN: │ │ │ │ Forbes NYT │ │ │ │ WSJ CNN │ │ │ └──────────────┘ │ │ ┌──────────────┐ │ │ │ CERTIFIED BY │ │ │ │ [BBB Logo] │ │ │ │ [Industry │ │ │ │ Cert Logo] │ │ │ └──────────────┘ │ ├─────────────────────────────────────────────────────────┤ │ FOOTER │ │ Privacy Policy | Terms | Editorial Policy | Contact │ │ © 2024 Company Name | 123 Main St, Austin TX 78701 │ └─────────────────────────────────────────────────────────┘
YMYL Content Requirements
YMYL (Your Money Your Life) topics—health, finance, safety, legal, news—face the highest E-E-A-T scrutiny because errors can harm users. These pages require expert authorship/review, citations to authoritative sources, regular updates, clear accuracy disclaimers, and demonstrate the highest levels of trust and expertise.
YMYL CONTENT TIERS ┌─────────────────────────────────────────────────────────┐ │ HIGHEST SCRUTINY (Clear YMYL) │ │ ├── Medical advice, symptoms, treatments │ │ ├── Financial advice, investments, taxes │ │ ├── Legal advice, rights, processes │ │ ├── News about current events │ │ └── Safety information │ │ │ │ REQUIREMENTS: │ │ ✓ Author with verifiable credentials │ │ ✓ Expert/peer review process │ │ ✓ Citations to .gov, .edu, peer-reviewed sources │ │ ✓ Regular content updates with dates shown │ │ ✓ Clear disclaimers ("Not medical advice...") │ │ ✓ Editorial policy publicly available │ └─────────────────────────────────────────────────────────┘ YMYL DISCLAIMER EXAMPLE: ┌─────────────────────────────────────────────────────────┐ │ ⚠️ Medical Disclaimer: This article is for │ │ informational purposes only and is not a substitute │ │ for professional medical advice. Always consult your │ │ physician before making health decisions. │ │ │ │ Last medically reviewed: March 2024 │ │ Reviewer: Dr. Smith, MD | Editorial Policy │ └─────────────────────────────────────────────────────────┘
Quality Rater Guidelines Understanding
Google's Quality Rater Guidelines (QRG) is a 170+ page document used by human evaluators to assess search quality. Understanding it reveals what Google considers high-quality: clear page purpose, adequate E-E-A-T for the topic, high-quality main content, positive reputation, and helpful, people-first content.
QRG QUALITY SCALE ┌─────────────────────────────────────────────────────────┐ │ LOWEST ──────────────────────────────────────► HIGHEST │ │ │ │ Lowest Low Medium High Highest │ │ │ │ │ │ │ │ │ ▼ ▼ ▼ ▼ ▼ │ │ ┌───┐ ┌───┐ ┌───┐ ┌───┐ ┌───┐ │ │ │ L │ │ L │ │ M │ │ H │ │ H │ │ │ │ O │ │ O │ │ E │ │ I │ │ I │ │ │ │ W │ │ W │ │ D │ │ G │ │ G │ │ │ │ E │ │ │ │ │ │ H │ │ H │ │ │ │ S │ │ │ │ │ │ │ │ E │ │ │ │ T │ │ │ │ │ │ │ │ S │ │ │ └───┘ └───┘ └───┘ └───┘ │ T │ │ │ └───┘ │ │ Harmful Poor Okay Exceeds Exceptional │ │ Deceptive Thin Average Standards Authoritative │ └─────────────────────────────────────────────────────────┘ KEY ASSESSMENT QUESTIONS (from QRG): • What is the purpose of this page? • Who is responsible for this content? • Does the author have appropriate E-E-A-T? • Is the main content high quality and sufficient? • What is the reputation of the website/author?
Entity SEO
Entity-Based Search
Entity-based search represents Google's evolution from keyword matching to understanding real-world things (people, places, concepts, organizations) and their relationships. Instead of matching strings, Google now understands that "Apple" could be a fruit, company, or record label—and uses context to disambiguate and serve relevant results.
KEYWORD vs ENTITY SEARCH EVOLUTION KEYWORD ERA (Pre-2012): Query: "apple" ┌─────────────────────────────────────────────────────────┐ │ Match pages containing the STRING "apple" │ │ Rank by: keyword density, backlinks, exact match │ └─────────────────────────────────────────────────────────┘ ENTITY ERA (Post-Knowledge Graph): Query: "apple" ┌─────────────────────────────────────────────────────────┐ │ Which ENTITY does user mean? │ │ │ │ Context Signals: │ │ • Previous searches (tech vs recipes) │ │ • Location (Cupertino = likely Apple Inc) │ │ • Device (iPhone = likely Apple Inc) │ │ • Query modifiers ("apple stock" vs "apple pie") │ │ │ │ ┌──────────┐ │ │ │ APPLE │ (Ambiguous) │ │ └────┬─────┘ │ │ ┌──────────┼──────────┐ │ │ ▼ ▼ ▼ │ │ [Apple Inc] [Fruit] [Records] │ │ Q312 Q89 Q213710 │ └─────────────────────────────────────────────────────────┘
Knowledge Graph Optimization
Google's Knowledge Graph is a database of billions of entities and their relationships, powering Knowledge Panels and rich results. Optimization involves establishing your entity through Wikipedia/Wikidata, consistent structured data, authoritative mentions, and building a strong web of references that Google can verify.
KNOWLEDGE GRAPH OPTIMIZATION PATH ┌─────────────────────────────────────────────────┐ │ KNOWLEDGE GRAPH │ │ (Google's Entity Database) │ └─────────────────────┬───────────────────────────┘ │ Verified From Multiple Sources │ ┌─────────────────────┼───────────────────────────┐ │ │ │ ▼ ▼ ▼ ┌─────────┐ ┌─────────────┐ ┌──────────┐ │Wikidata │ │ Your Site │ │ External │ │Wikipedia│ │ (Schema) │ │ Sources │ └─────────┘ └─────────────┘ └──────────┘ │ │ │ │ Organization │ │ + Person News, Awards │ + sameAs links Directories │ Social Profiles GOAL: Knowledge Panel ┌─────────────────────────────────┐ │ [Image] Company Name │ │ Industry: Technology │ │ Founded: 2010 │ │ CEO: Jane Smith │ │ Headquarters: Austin │ │ │ │ Website | Twitter | LinkedIn │ └─────────────────────────────────┘
Entity Recognition
Entity recognition (Named Entity Recognition/NER) is how search engines identify and classify entities within content—distinguishing persons, organizations, locations, dates, products, and concepts. Optimizing for it means clearly introducing entities, using full names before abbreviations, and providing contextual clarity.
ENTITY RECOGNITION IN CONTENT INPUT TEXT: "Tim Cook announced Apple's new M3 chip at the Cupertino event on October 30, 2023. The CEO said it delivers 60% faster performance than M1." NER OUTPUT: ┌─────────────────────────────────────────────────────────┐ │ ENTITY │ TYPE │ WIKIDATA ID │ ├──────────────────┼──────────────┼──────────────────────┤ │ Tim Cook │ PERSON │ Q265252 │ │ Apple │ ORGANIZATION │ Q312 │ │ M3 chip │ PRODUCT │ Q118762002 │ │ Cupertino │ LOCATION │ Q490624 │ │ October 30, 2023 │ DATE │ - │ │ CEO │ ROLE │ Q484876 │ │ M1 │ PRODUCT │ Q104869880 │ └──────────────────┴──────────────┴──────────────────────┘ OPTIMIZATION TIP: ✗ "Cook announced the new chip..." (Ambiguous) ✓ "Apple CEO Tim Cook announced..." (Clear entity intro)
Entity Relationships
Entity relationships define how entities connect—a person "worksFor" an organization, a product "isProducedBy" a company, a city "isLocatedIn" a country. Google uses these relationships to understand context, answer complex queries, and build comprehensive knowledge about topics.
ENTITY RELATIONSHIP MAP ┌───────────────┐ │ TIM COOK │ │ (Person) │ └───────┬───────┘ │ ┌─────────────┼─────────────┐ │ │ │ ▼ ▼ ▼ [worksFor] [alumniOf] [birthPlace] │ │ │ ▼ ▼ ▼ ┌─────────┐ ┌───────────┐ ┌──────────┐ │ APPLE │ │ DUKE │ │ MOBILE │ │ INC. │ │UNIVERSITY │ │ ALABAMA │ └────┬────┘ └───────────┘ └──────────┘ │ ┌────────┼────────┐ │ │ │ ▼ ▼ ▼ [produces][foundedBy][headquarteredIn] │ │ │ ▼ ▼ ▼ ┌──────┐┌────────┐┌───────────┐ │iPhone││S. Jobs ││ Cupertino │ └──────┘└────────┘└───────────┘ SCHEMA.ORG RELATIONSHIPS: - worksFor, memberOf, alumniOf - founder, ceo, employee - isPartOf, hasPart - sameAs, subjectOf
Wikidata and Wikipedia
Wikidata (structured data) and Wikipedia (content) are primary sources Google uses to build the Knowledge Graph. Creating a Wikidata item establishes your entity with a unique ID (Q-number), while a notable Wikipedia article significantly increases chances of a Knowledge Panel—but both require meeting notability guidelines.
WIKIDATA ENTITY CREATION ┌─────────────────────────────────────────────────────────┐ │ WIKIDATA ITEM: Q123456789 │ ├─────────────────────────────────────────────────────────┤ │ Label: Acme Corporation │ │ Description: American technology company │ │ Also known as: Acme Corp, Acme Tech │ ├─────────────────────────────────────────────────────────┤ │ STATEMENTS (Properties): │ │ ├── instance of (P31): business enterprise (Q4830453) │ │ ├── country (P17): United States (Q30) │ │ ├── inception (P571): 2010 │ │ ├── headquarters (P159): Austin (Q1930) │ │ ├── founder (P112): Jane Smith (Q987654) │ │ ├── official website (P856): https://acme.com │ │ ├── LinkedIn ID (P6634): company/acme-corp │ │ └── Twitter username (P2002): @acmecorp │ ├─────────────────────────────────────────────────────────┤ │ REFERENCES: (Cite reliable sources for each claim) │ │ └── stated in: Forbes, Crunchbase, SEC filings │ └─────────────────────────────────────────────────────────┘ PATH TO KNOWLEDGE PANEL: Wikidata → Wikipedia → Google Knowledge Graph → Panel
Brand Entity Establishment
Brand entity establishment creates a distinct, recognizable entity for your brand in Google's Knowledge Graph through consistent naming, comprehensive schema markup, Wikidata presence, Wikipedia notability, press coverage, social profile verification, and ensuring all references use consistent identifiers linked via sameAs.
BRAND ENTITY CHECKLIST ┌─────────────────────────────────────────────────────────┐ │ FOUNDATION │ │ ☐ Consistent brand name everywhere (exact match) │ │ ☐ Organization schema on website with @id │ │ ☐ Wikidata item created with all properties │ │ ☐ Claimed/verified social profiles │ │ │ │ AUTHORITY SIGNALS │ │ ☐ Wikipedia article (if notable) │ │ ☐ Crunchbase profile │ │ ☐ Press coverage on authoritative sites │ │ ☐ Industry directory listings │ │ │ │ SCHEMA IMPLEMENTATION │ │ ☐ sameAs array linking all profiles │ │ ☐ founder/CEO linked as Person entities │ │ ☐ Products/services as separate entities │ │ ☐ Consistent @id across all schema │ └─────────────────────────────────────────────────────────┘
{ "@context": "https://schema.org", "@type": "Organization", "@id": "https://acme.com/#organization", "name": "Acme Corporation", "url": "https://acme.com", "logo": "https://acme.com/logo.png", "sameAs": [ "https://www.wikidata.org/wiki/Q123456789", "https://twitter.com/acmecorp", "https://linkedin.com/company/acme-corp", "https://www.crunchbase.com/organization/acme-corp" ], "founder": {"@id": "https://acme.com/about/jane-smith#person"} }
Personal Brand Entities
Personal brand entities establish individuals as recognized Knowledge Graph entities—critical for authors, executives, and thought leaders. Build through consistent professional profiles (LinkedIn, Twitter), author pages with schema, Wikidata items, speaking/publication credits, and sameAs connections linking all representations.
PERSONAL ENTITY MAP ┌──────────────────────────────────────┐ │ JANE SMITH │ │ Knowledge Graph Entity │ │ (Q987654321) │ └────────────────┬─────────────────────┘ │ ┌─────────────────────┼─────────────────────┐ │ │ │ ▼ ▼ ▼ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ WEBSITE │ │ SOCIAL │ │ EXTERNAL │ │ PRESENCE │ │ PROFILES │ │ SOURCES │ ├─────────────┤ ├─────────────┤ ├─────────────┤ │/authors/ │ │LinkedIn │ │Wikidata │ │jane-smith │◄────►│Twitter │◄────►│Wikipedia │ │+ Schema │ │GitHub │ │ORCID │ │+ Photo │ │All verified │ │Crunchbase │ └─────────────┘ └─────────────┘ └─────────────┘ │ │ │ └─────────────────────┼─────────────────────┘ │ All connected via sameAs in Schema
Entity Disambiguation
Entity disambiguation is how search engines determine which specific entity a term refers to when multiple entities share the same name—"Michael Jordan" could be the basketball player, actor, or professor. Optimize by providing context, using full names, adding descriptors, and leveraging schema with unique identifiers.
DISAMBIGUATION EXAMPLE Query: "Michael Jordan" CANDIDATE ENTITIES: ┌─────────────────────────────────────────────────────────┐ │ Q41421 │ Michael Jordan │ Basketball player, born │ │ │ │ 1963, played for Bulls │ ├─────────┼───────────────────┼───────────────────────────┤ │ Q27069 │ Michael B. Jordan │ Actor, Black Panther │ ├─────────┼───────────────────┼───────────────────────────┤ │ Q325678 │ Michael I. Jordan │ UC Berkeley professor, │ │ │ │ machine learning │ └─────────┴───────────────────┴───────────────────────────┘ DISAMBIGUATION SIGNALS: • Context: "NBA", "championship" → Basketball player • Context: "movie", "Creed" → Actor • Context: "AI", "research" → Professor OPTIMIZATION STRATEGY: ✗ "Jordan discussed machine learning..." ✓ "UC Berkeley professor Michael I. Jordan, a pioneer in AI research, discussed machine learning..." Use schema @id and sameAs to explicitly identify: "sameAs": "https://www.wikidata.org/wiki/Q325678"
Semantic SEO
Semantic SEO focuses on optimizing for meaning and intent rather than exact keywords—covering topics comprehensively, using related concepts naturally, answering user questions, and helping search engines understand content context through entity relationships, structured data, and topically complete coverage.
SEMANTIC SEO CONTENT MODEL KEYWORD SEO (Old): SEMANTIC SEO (Modern): "best running shoes" Topic: Running Shoes Repeat 15 times │ Add variations ┌──────┼──────────────┐ │ │ │ ▼ ▼ ▼ Related Entities Questions Terms Covered Answered │ │ │ ┌────┴────┐ │ ┌──────┴──────┐ │cushioning│ │ │How to choose│ │pronation │ │ │Best for flat│ │gait │ │ │feet? │ │midsole │ │ │Replace when?│ └─────────┘ │ └─────────────┘ │ ┌─────────────┴─────────────┐ │ Nike, Asics, Brooks │ │ Marathon, trail running │ │ Foot strike, arch type │ └───────────────────────────┘ TOOLS: NLP APIs reveal "missing" entities/concepts: - TF-IDF analysis of top-ranking pages - Entity extraction from competitors - "People Also Ask" coverage
Ontology Basics
An ontology in SEO context is a structured framework defining how concepts, entities, and their relationships are organized within a domain. Understanding ontologies helps you structure content hierarchically, use proper schema types, and build topical authority by covering all related concepts systematically.
ONTOLOGY STRUCTURE EXAMPLE: "Recipes" Domain ┌─────────────┐ │ RECIPE │ │ (Top-Level)│ └──────┬──────┘ │ ┌──────────────────────┼──────────────────────┐ │ │ │ ▼ ▼ ▼ ┌───────────┐ ┌───────────┐ ┌───────────┐ │ CUISINE │ │ MEAL │ │ DIETARY │ │ TYPE │ │ TYPE │ │RESTRICTION│ └─────┬─────┘ └─────┬─────┘ └─────┬─────┘ │ │ │ ┌────┼────┐ ┌────┼────┐ ┌────┼────┐ ▼ ▼ ▼ ▼ ▼ ▼ ▼ ▼ ▼ Italian Asian Mexican Breakfast Dinner Vegan GF Keto │ Lunch ▼ Pasta → hasIngredient → [Flour, Egg, Water] → hasCookingMethod → [Boiling] → hasCookTime → "10 minutes" ONTOLOGY INFORMS: • Site architecture (category hierarchy) • Internal linking (related concepts) • Schema markup (proper @types) • Content gaps (missing entities/concepts)
Entity Salience
Entity salience measures how central or important an entity is within a piece of content—not just mentioned, but prominently featured and contextually significant. Google's NLP uses salience scores (0-1) to understand what content is primarily about, affecting how it ranks for entity-related queries.
ENTITY SALIENCE ANALYSIS Content: "Tim Cook announced Apple's new M3 chip at the Cupertino event, promising 60% better performance than Intel processors." SALIENCE SCORES (0.0 to 1.0): ┌─────────────────────────────────────────────────────────┐ │ ENTITY │ SALIENCE │ VISUALIZATION │ ├─────────────────┼──────────┼───────────────────────────┤ │ Apple │ 0.85 │ ████████████████████░░░░ │ │ M3 chip │ 0.72 │ █████████████████░░░░░░░ │ │ Tim Cook │ 0.45 │ ███████████░░░░░░░░░░░░░ │ │ Cupertino │ 0.15 │ ████░░░░░░░░░░░░░░░░░░░░ │ │ Intel │ 0.12 │ ███░░░░░░░░░░░░░░░░░░░░░ │ └─────────────────┴──────────┴───────────────────────────┘ FACTORS AFFECTING SALIENCE: • Position (title, H1, first paragraph = higher) • Frequency (more mentions = higher) • Syntactic role (subject vs object) • Coreference (pronouns referring back) OPTIMIZATION: ✗ One mention of target entity buried in paragraph 5 ✓ Target entity in title, H1, intro, and recurring themes
# Example using Google Cloud NLP API from google.cloud import language_v1 def analyze_salience(text): client = language_v1.LanguageServiceClient() document = language_v1.Document( content=text, type_=language_v1.Document.Type.PLAIN_TEXT ) response = client.analyze_entities(document=document) for entity in response.entities: print(f"{entity.name}: {entity.salience:.2f}") # Output: Apple: 0.85, M3 chip: 0.72, Tim Cook: 0.45