SEO Optimizer

Comprehensive guidance for search engine optimization and AI search optimization (GEO) across content, technical implementation, and strategic planning.

When to Use This Skill

Use this skill when:

• Optimizing for traditional search engines (Google, Bing)
• Optimizing for AI search engines (ChatGPT, Perplexity, Google AI Overviews)
• Implementing schema markup for rich results and AI citation
• Improving Core Web Vitals (LCP, INP, CLS)
• Creating citation-worthy content structure
• Conducting keyword research and analysis
• Planning content strategy for organic and AI traffic
• Implementing E-E-A-T signals

Critical 2025-2026 Statistics

• 61% of searches will start on AI platforms by 2026
• 50% of SEO effort should focus on GEO for 2026
• 58-60% of Google searches are zero-click
• 3.7x more likely to be cited by AI with proper schema markup
• INP threshold: ≤ 200ms (replaced FID in March 2024)
• CTR drops 61% for queries with AI Overviews

AI Search Optimization (GEO)

What is GEO?

Generative Engine Optimization (GEO) is the practice of optimizing content to be surfaced, cited, and referenced by AI-powered search engines like ChatGPT Search, Perplexity, Google AI Overviews, and Claude.

GEO vs Traditional SEO

Platform-Specific Optimization

ChatGPT Search

Top Sources: Wikipedia, G2, Forbes, Amazon, official documentation Strategy:

• Reference-style content with inline citations
• Well-organized hierarchical structure
• Comprehensive topical coverage
• Clear definitions and explanations

Perplexity

Top Sources: Reddit, YouTube, LinkedIn, niche forums Strategy:

• Community-driven, discussion-friendly content
• UGC-friendly formats (Q&A, testimonials)
• Real-world examples and case studies
• Conversational tone

Google AI Overviews

Top Sources: High E-E-A-T sites, recent/fresh content Strategy:

• Schema markup (critical)
• Content freshness signals
• Direct answers in BLUF format
• Structured data for Knowledge Panel

Citation Boost Statistics

GEO Content Formatting

BLUF (Bottom Line Up Front)

AI systems prefer content that answers questions immediately:

## What is React?

**React is a JavaScript library for building user interfaces**, developed by Meta. It uses a component-based architecture and virtual DOM for efficient rendering.

### Key Features
- Component-based architecture
- Virtual DOM for performance
- Declarative syntax
- Large ecosystem

Data Tables for Citation (+4.1x boost)

Original data tables are highly citation-worthy:

## Framework Comparison (2025 Benchmarks)

| Framework | Bundle Size | TTI | Stars | Weekly Downloads |
|-----------|-------------|-----|-------|------------------|
| React 18  | 44kb        | 1.2s| 220k  | 23M              |
| Vue 3     | 34kb        | 0.9s| 206k  | 4M               |
| Svelte 5  | 2kb         | 0.4s| 78k   | 500k             |

*Source: [Your analysis], January 2025*

Inline Citations

According to a [2024 study by Ahrefs](https://ahrefs.com/study),
pages with comprehensive FAQ sections receive 3.2x more AI Overview
inclusions than those without structured Q&A content.

Schema Markup for AI

High-Impact Schema Types

FAQPage Schema (3.2x more AI Overviews)

{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is Generative Engine Optimization?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Generative Engine Optimization (GEO) is the practice of optimizing content to be cited and referenced by AI-powered search engines like ChatGPT, Perplexity, and Google AI Overviews."
      }
    }
  ]
}

Article Schema with Author Attribution

{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "Complete Guide to AI Search Optimization",
  "image": "https://example.com/images/geo-guide.jpg",
  "datePublished": "2025-01-15",
  "dateModified": "2025-02-01",
  "author": {
    "@type": "Person",
    "name": "Jane Developer",
    "url": "https://example.com/authors/jane",
    "sameAs": [
      "https://twitter.com/janedev",
      "https://linkedin.com/in/janedev"
    ],
    "jobTitle": "Senior SEO Specialist",
    "worksFor": {
      "@type": "Organization",
      "name": "Tech Academy"
    }
  },
  "publisher": {
    "@type": "Organization",
    "name": "Tech Academy",
    "logo": {
      "@type": "ImageObject",
      "url": "https://example.com/logo.png"
    }
  }
}

HowTo Schema with Steps

{
  "@context": "https://schema.org",
  "@type": "HowTo",
  "name": "How to Optimize Content for AI Search",
  "step": [
    {
      "@type": "HowToStep",
      "position": 1,
      "name": "Add FAQ Schema",
      "text": "Implement FAQPage schema for question-answer content."
    },
    {
      "@type": "HowToStep",
      "position": 2,
      "name": "Use BLUF Format",
      "text": "Place the key answer in the first paragraph."
    }
  ]
}

Organization Schema for Knowledge Panel

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Your Company",
  "url": "https://example.com",
  "logo": "https://example.com/logo.png",
  "sameAs": [
    "https://twitter.com/yourcompany",
    "https://linkedin.com/company/yourcompany",
    "https://github.com/yourcompany"
  ],
  "contactPoint": {
    "@type": "ContactPoint",
    "telephone": "+1-555-555-5555",
    "contactType": "customer service"
  }
}

Additional Schema Types

• Product - E-commerce listings
• BreadcrumbList - Navigation paths
• Review/AggregateRating - Ratings and reviews
• LocalBusiness - Location-based businesses
• SoftwareApplication - Apps and tools
• Dataset - Structured data sources

Core Web Vitals 2025-2026

Current Thresholds

Largest Contentful Paint (LCP) - Target: ≤ 2.5s

What it measures: Time until the largest content element is rendered.

Optimization Techniques:

• Optimize and compress images (WebP/AVIF format)
• Use CDN for static assets
• Implement resource hints (preload, preconnect)
• Minimize render-blocking resources
• Use fetchpriority="high" on LCP element

<!-- Preload LCP image -->
<link rel="preload" href="/hero.webp" as="image" fetchpriority="high">

<!-- Preconnect to CDN -->
<link rel="preconnect" href="https://cdn.example.com">

Interaction to Next Paint (INP) - Target: ≤ 200ms

What it measures: Responsiveness to user interactions (replaced FID in March 2024).

Key Difference from FID: INP measures the entire interaction lifecycle, not just input delay.

Optimization Techniques:

• Break up long tasks (> 50ms) into smaller chunks
• Use requestIdleCallback for non-critical work
• Implement virtualization for long lists
• Defer non-critical JavaScript
• Use Web Workers for heavy computations
• Optimize event handlers

// Break long task into chunks
function processInChunks(items, processFn) {
  const CHUNK_SIZE = 100;
  let index = 0;

  function processChunk() {
    const chunk = items.slice(index, index + CHUNK_SIZE);
    chunk.forEach(processFn);
    index += CHUNK_SIZE;

    if (index < items.length) {
      requestIdleCallback(processChunk);
    }
  }

  requestIdleCallback(processChunk);
}

Cumulative Layout Shift (CLS) - Target: ≤ 0.1

What it measures: Visual stability of the page.

Optimization Techniques:

• Set explicit dimensions on images/videos
• Reserve space for ads and embeds
• Avoid inserting content above existing content
• Use CSS aspect-ratio property
• Preload fonts with font-display: optional

<!-- Set dimensions to prevent layout shift -->
<img
  src="/image.webp"
  width="800"
  height="600"
  alt="Description"
  loading="lazy"
/>

<!-- Or use aspect-ratio -->
<style>
  .video-container {
    aspect-ratio: 16 / 9;
    width: 100%;
  }
</style>

E-E-A-T for AI Systems

Machine-Readable E-E-A-T Signals

AI systems increasingly look for trust signals. Make them explicit:

Experience Signals

• First-person narratives ("In my 10 years of...")
• Case studies with specific outcomes
• Screenshots and real examples
• Dated timestamps showing ongoing engagement

Expertise Signals

• Author credentials in schema markup
• Bylines with expertise indicators
• Technical depth with accurate terminology
• Original research and data

Authoritativeness Signals

• Citations from/to authoritative sources
• Expert quotes with attribution
• Industry recognition mentions
• Published works references

Trust Signals

• HTTPS (baseline requirement)
• Clear contact information
• Privacy policy and terms
• Physical address for businesses
• Transparent ownership

Author Attribution Pattern

<article>
  <header>
    <h1>Complete Guide to React Performance</h1>
    <div class="author-info" itemscope itemtype="https://schema.org/Person">
      <img src="/authors/jane.jpg" alt="Jane Developer" itemprop="image">
      <div>
        <span itemprop="name">Jane Developer</span>
        <span itemprop="jobTitle">Senior React Engineer</span>
        <span>15 years experience • 50+ articles published</span>
        <time datetime="2025-01-15">Updated January 15, 2025</time>
      </div>
    </div>
  </header>
  <!-- Content -->
</article>

Zero-Click Optimization

With 58-60% of searches resulting in zero clicks, optimize for visibility even without clicks.

Answer Inclusion Strategies

1. Direct Answer Format

   • Start with the answer, then explain
   • Use definition-style formatting
   • Keep key answer under 50 words

2. Entity Clarity

   • Define entities clearly at first mention
   • Use consistent naming throughout
   • Include entity schema markup

3. Structured Credibility

   • Lead with credentials
   • Include specific numbers and dates
   • Cite authoritative sources

Featured Snippet Optimization

Paragraph Snippets:

## What is INP?

Interaction to Next Paint (INP) is a Core Web Vital metric that measures
page responsiveness. It replaced First Input Delay (FID) in March 2024.
A good INP score is 200 milliseconds or less.

List Snippets:

## How to Improve INP

1. Break long tasks into smaller chunks
2. Defer non-critical JavaScript
3. Use Web Workers for heavy computations
4. Optimize event handlers
5. Implement virtualization for long lists

Table Snippets:

## Core Web Vitals Thresholds

| Metric | Good | Poor |
|--------|------|------|
| LCP    | ≤2.5s| >4s  |
| INP    | ≤200ms| >500ms|
| CLS    | ≤0.1 | >0.25|

Multimodal Search Optimization

Voice Search Optimization

Voice queries are conversational and question-based:

Optimization Strategies:

• Target natural language questions ("How do I...", "What is the best...")
• Provide concise, speakable answers (< 30 words ideal)
• Use FAQ schema for question-answer pairs
• Optimize for "near me" queries (local SEO)

Voice-Friendly Content:

## How long does it take to learn React?

Most developers can learn React basics in 2-4 weeks with daily practice.
Becoming proficient typically takes 3-6 months of building real projects.

Visual Search (Google Lens)

Optimization Strategies:

• High-quality, unique images
• Descriptive filenames (blue-running-shoes-nike-2025.jpg)
• Comprehensive alt text
• Image schema markup
• Product images with multiple angles

SEO Fundamentals

Keyword Research & Strategy

Primary Keyword Selection:

• Focus on search intent (informational, navigational, transactional, commercial)
• Balance search volume with competition
• Target long-tail keywords for quick wins
• Consider AI search query patterns (more conversational)

Content Optimization Formula:

• Primary keyword: 1-2% density (natural placement)
• Include in: Title tag, H1, first paragraph, URL, meta description
• Use semantic variations and related terms
• Maintain natural readability

On-Page SEO

Title Tag Optimization:

<!-- Good: Descriptive, keyword-first, under 60 chars -->
<title>INP Optimization Guide: Improve Core Web Vitals in 2025</title>

Meta Description:

<!-- Compelling, 150-160 chars, includes CTA -->
<meta name="description" content="Master INP optimization with proven techniques. Learn to achieve ≤200ms scores and improve Core Web Vitals. Includes code examples and benchmarks.">

Header Structure:

<h1>Main Topic (Primary Keyword)</h1>
  <h2>Section (Related Keywords)</h2>
    <h3>Subsection</h3>
  <h2>Another Section</h2>

URL Structure:

✅ Good: /guides/inp-optimization-2025
❌ Bad: /blog?p=12345&cat=seo

Internal Linking Strategy

• Use descriptive anchor text (avoid "click here")
• Link to relevant, contextual pages
• Include 3-5 internal links per 1,000 words
• Create topic clusters with pillar pages

SEO Content Checklist

Before Publishing

• Primary keyword in title tag (under 60 chars)
• Meta description (150-160 chars, compelling)
• H1 tag with primary keyword
• BLUF format (answer first)
• FAQ section with schema
• Original data/tables where relevant
• Author attribution with credentials
• Schema markup implemented
• Images optimized with alt text
• 3-5 internal links
• Core Web Vitals passing (LCP ≤2.5s, INP ≤200ms, CLS ≤0.1)
• Mobile-friendly and responsive
• Canonical tag set correctly

GEO-Specific Checklist

• Direct answer in first paragraph
• Inline citations to authoritative sources
• Data tables with original research
• Expert quotes with attribution
• FAQ schema for Q&A content
• Article schema with author details
• Content freshness (dateModified)
• Entity clarity (define terms)

Monitoring & Analytics

Traditional SEO Metrics

• Organic traffic trends
• Keyword rankings
• Click-through rates (CTR)
• Core Web Vitals scores
• Backlink profile

GEO Metrics

• Citation Velocity: How often your content is cited by AI
• Answer Inclusion Rate: % of relevant queries showing your content
• Brand Mention Frequency: Mentions in AI responses
• Source Attribution: When AI names your site as source

Tools

• Google Search Console (performance, indexing)
• Google Analytics 4 (traffic, behavior)
• PageSpeed Insights (Core Web Vitals)
• Ahrefs/SEMrush (keywords, backlinks)
• Perplexity Analytics (AI citation tracking)

References

See references/ai-seo-patterns.md for:

• Platform-specific source preferences
• Schema code examples
• Implementation checklists
• Citation boost statistics