<div class="article-tldr"><p class="article-tldr-label">TL;DR</p><p>AI search engines don’t read your about page—they extract individual facts like “Company X was founded in 2015” and cite them only if each claim has its own dedicated page with machine-readable schema. Building a separate “Mention Detail Page” for every verifiable brand fact, complete with external citations and ClaimReview markup, is what gets you into ChatGPT and Gemini’s citation graph.</p></div>
<h1>How to Optimize for AI Search: Brand Mentions</h1>
<p><strong>Subtitle:</strong> Controlling the Citation Graph in ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews</p>
<h2>1. The New Battleground: The Citation Graph</h2>
<p>Traditional SEO optimized for <strong>search result pages</strong>. GEO/AEO optimizes for the <strong>citation graph</strong>.</p>
<p>When an AI engine (ChatGPT, Perplexity, Gemini) answers a user query, it does not browse the open web in real time. It retrieves pre-indexed facts from its training data or retrieval-augmented generation (RAG) databases. Your brand wins when the AI <strong>cites you</strong> as the authoritative source for a specific claim, definition, or data point.</p>
<p><strong>The core insight:</strong> AI engines prioritize <em>verifiability</em> and <em>directness</em> over keyword density. A brand mention is strongest when it is:</p>
<ol>
<li><strong>Explicitly connected</strong> to a specific, verifiable fact.</li>
<li><strong>Structured</strong> in machine-readable schema.</li>
<li><strong>Cited</strong> by other trusted sources (the citation graph).</li>
</ol>
<h2>2. Understanding the AI Engine Mental Model</h2>
<p>Different engines have different trust signals. You must adapt your strategy.</p>
<table><thead><tr><th>Engine</th><th>Primary Signal</th><th>Weakness</th><th>Your Strategy</th></tr></thead><tbody>
<tr><td><strong>ChatGPT</strong></td><td>WebGPT / Bing index + training data cut-off</td><td>Can hallucinate dates/sources if not explicitly written</td><td><strong>Always include dates.</strong> Write absolute facts (e.g., "As of July 2024...").</td></tr>
<tr><td><strong>Claude</strong></td><td>Anthropic's custom web index + E-E-A-T heavy filtering</td><td>Highly sensitive to source quality; prefers .edu, .gov, established publishers</td><td>Focus on <strong>backlinks from high-authority domains</strong> to your mention pages. Claude trusts link graphs heavily.</td></tr>
<tr><td><strong>Perplexity</strong></td><td>Own crawl + Bing + Google + deep analysis of PDFs</td><td>Penalized heavily for <strong>thin content</strong> or pages that don't answer the query directly</td><td>Create <strong>dedicated "Mention Detail" pages</strong> that answer a single, clear question. No fluff.</td></tr>
<tr><td><strong>Gemini</strong></td><td>Google's index (Crawl &amp; BERT based) + Knowledge Graph</td><td>Struggles with contradictory claims; needs schema to disambiguate</td><td>Use <strong>ClaimReview</strong> and <strong>Mention</strong> schema with precise <code>sameAs</code> links.</td></tr>
<tr><td><strong>Google AI Overviews</strong></td><td>Google's MUM / MASSIVE + Search Generative Experience (SGE)</td><td>Only shows source links when forced by citation schema; extremely picky about entity authority</td><td>Make your brand a <strong>Knowledge Panel entity</strong>. Get a Wikipedia page or solid Wikidata entry.</td></tr>
</tbody></table>
<p><strong>Trade-off:</strong> Tailoring for one engine may slightly reduce performance on another. Optimize for <strong>schema completeness</strong> and <strong>citation depth</strong>—this benefits all major engines.</p>
<h2>3. Step-by-Step GEO/AEO Optimization for Brand Mentions</h2>
<h3>Step 1: The "Claim Audit" – Identify What AIs Will Cite About You</h3>
<p>Before you optimize, you must know <em>what facts</em> about your brand are citation-worthy.</p>
<ul>
<li><strong>Action:</strong> Create a spreadsheet of 20–30 atomic facts about your brand.</li>
<li><strong>Example:</strong></li>
<li>"<em>Company X</em> was founded in <em>2015</em>."</li>
<li>"<em>Product Y</em> has <em>99.7% uptime</em> as of <em>Q2 2024</em>."</li>
<li>"<em>Person Z</em> is the <em>CEO</em> and previously served as <em>CTO at ABC Corp</em>."</li>
<li>"<em>Award W</em> was granted by <em>Gartner</em> in <em>March 2024</em>."</li>
</ul>
<p><strong>Why this matters:</strong> AI engines do not "read" your about page holistically. They extract individual triples (Subject–Predicate–Object). Each triple is a potential citation.</p>
<h3>Step 2: Build "Mention Detail Pages" (Not Just Press Releases)</h3>
<p>Most brands have a single press release or news section. This is insufficient for AI extraction. You need <strong>dedicated pages</strong> for each major claim or mention.</p>
<p><strong>Page Structure Template:</strong></p>
<p><code>`</code> DOMAIN.com/mentions/founding-date-2015/ ├── H1: How Company X Was Founded in 2015: A Verification ├── H2: Executive Summary │   └── Verifiable claim: "Company X was legally incorporated in Delaware on March 14, 2015." ├── H2: Primary Evidence │   └── Link to Secretary of State filing (PDF) │   └── Link to archived news article from 2015 │   └── Link to Crunchbase / LinkedIn entry (with same date) ├── H2: Citation Table (structured for AI extraction) │   ├── Claim: Founding Year │   ├── Value: 2015 │   ├── Source 1: Wayback Machine (link) │   ├── Source 2: D&amp;B filing (link) │   └── Source 3: Third-party media mention (link) ├── H2: Related Entities │   └── Founder name, location, industry classification └── [Schema Markup Block - See Section 4] <code>`</code></p>
<p><strong>Why this works:</strong> Perplexity and Gemini will crawl this page, find the table, see the external citations, and output: <em>"Company X was founded in 2015 (Source 1, Source 2)."</em> The citation graph is satisfied.</p>
<h3>Step 3: Schema Markup – The Machine-Readable Layer</h3>
<p>Schema is your primary tool for telling AI engines explicitly: <em>"This is a brand mention, and this is how it should be cited."</em></p>
<h4>3A. <code>ClaimReview</code> Schema (Gold Standard for Mentions)</h4>
<p>Use this when an AI <em>evaluates</em> a claim about your brand (e.g., "Is Company X a leader in the space?").</p>
<p><code>`</code>json { "@context": "https://schema.org", "@type": "ClaimReview", "url": "https://DOMAIN.com/mentions/sample-claim", "claimReviewed": "Company X is the fastest-growing SaaS company in Europe in 2024.", "author": { "@type": "Organization", "name": "Your Brand Name", "sameAs": "https://www.wikidata.org/entity/Q12345" }, "datePublished": "2024-10-01", "itemReviewed": { "@type": "Claim", "appearance": [ { "@type": "OpinionNewsArticle", "url": "https://third-party-source.com/article" } ] }, "reviewRating": { "@type": "Rating", "bestRating": "5", "ratingValue": "5", "worstRating": "1" } } <code>`</code></p>
<p><strong>Key fields for AI ranking:</strong></p>
<ul>
<li><code>claimReviewed</code>: Must match the exact text you want cited.</li>
<li><code>author.sameAs</code>: Links to your Knowledge Graph entity. Critical for Gemini and Google AI Overviews.</li>
<li><code>reviewRating.ratingValue</code>: AI uses this to determine <em>strength</em> of the mention. A 5/5 rating signals high verifiability.</li>
</ul>
<h4>3B. <code>Mention</code> Schema (Newer, More Specific)</h4>
<p>Google introduced this explicitly for brand mentions in news and editorial content.</p>
<p><code>`</code>json { "@context": "https://schema.org", "@type": "Mention", "mentions": { "@type": "Organization", "name": "Your Brand", "url": "https://DOMAIN.com", "sameAs": [ "https://twitter.com/yourbrand", "https://www.crunchbase.com/company/yourbrand" ] }, "datePublished": "2024-10-01", "headline": "Salesforce acquires Company X", "publisher": { "@type": "Organization", "name": "Third-Party Publisher", "url": "https://publisher-site.com" } } <code>`</code></p>
<p><strong>Benefit:</strong> This explicitly tells Google and Gemini that a <em>specific</em> page contains a mention of your brand. It helps AI understand context (positive, neutral, acquisition, launch).</p>
<h4>3C. <code>CiteAs</code> Schema (For Authoritative Person Mentions)</h4>
<p>When a person (CEO, founder) is mentioned, add this to their bio page.</p>
<p><code>`</code>json { "@context": "https://schema.org", "@type": "Person", "name": "Jane Doe", "affiliation": { "@type": "Organization", "name": "Your Brand" }, "citation": [ { "@type": "ScholarlyArticle", "name": "Why Jane Doe's Leadership Matters in 2024", "url": "https://publisher.org/article" } ] } <code>`</code></p>
<p><strong>Trade-off:</strong> Overusing <code>citation</code> can look spammy. Only link to 3–5 genuinely high-authority external articles.</p>
<h3>Step 4: Business Citation Optimization (For Local AEO)</h3>
<p>If your brand has a physical presence, AI engines (especially Google AI Overviews and Gemini) pull business mentions from structured citation sources.</p>
<table><thead><tr><th>Platform</th><th>Impact on AI</th><th>Action</th></tr></thead><tbody>
<tr><td><strong>Google Business Profile</strong></td><td>High. The #1 source for Google Knowledge Panels</td><td>Ensure <code>Description</code> field contains your core claim (e.g., "Founded 2015, 99.7% uptime").</td></tr>
<tr><td><strong>Wikipedia / Wikidata</strong></td><td>Critical for Gemini and Perplexity</td><td>Get a verified Wikipedia page or at least a robust Wikidata entity with all your key facts.</td></tr>
<tr><td><strong>Crunchbase / LinkedIn</strong></td><td>Moderate for ChatGPT; High for Perplexity</td><td>Update with exact founding date, funding rounds, and leadership.</td></tr>
<tr><td><strong>Bloomberg / SEC EDGAR</strong></td><td>Very high trust signal</td><td>If public, ensure your filings are clean.</td></tr>
</tbody></table>
<p><strong>Action step:</strong> Use a tool like BrightLocal or Moz Local to audit your NAP (Name, Address, Phone) consistency across 50+ sites. Inconsistency kills AI trust.</p>
<h3>Step 5: Off-Page Signal Building – The Citation Backlink</h3>
<p>A brand mention page without external citations is a monologue. AI engines want to see <strong>triangulation</strong>: three independent sources agreeing on the same fact.</p>
<p><strong>Strategy:</strong></p>
<ol>
<li><strong>Write the canonical mention page</strong> on your domain (Step 2).</li>
<li><strong>Pitch a guest article</strong> on a .edu or .gov domain that mentions the same fact and links back to your page.</li>
<li><strong>Get a third-party media mention</strong> (e.g., TechCrunch, Forrester) that echoes the fact.</li>
<li><strong>Link those three sources</strong> back to your mention page via the citation table (Step 2) and schema (Step 3).</li>
</ol>
<p><strong>Result:</strong> When an AI crawls your mention page, it sees:</p>
<ul>
<li><code>ClaimReview</code> with <code>reviewRating</code> = 5</li>
<li><code>Mention</code> schema linking to 3 high-authority external sources</li>
<li>A clean, atomic fact in a structured table</li>
</ul>
<p><strong>The AI will likely cite you.</strong></p>
<h2>4. Common Pitfalls (Trade-offs &amp; Risks)</h2>
<table><thead><tr><th>Mistake</th><th>Why It Hurts AEO</th><th>Fix</th></tr></thead><tbody>
<tr><td><strong>Keyword stuffing</strong> in mention pages</td><td>AI engines detect this as low-quality. Perplexity penalizes heavily.</td><td>Write for human clarity. Use AI extraction tables for the machine.</td></tr>
<tr><td><strong>Over-relying on a single source</strong></td><td>ChatGPT will hallucinate if only one source exists.</td><td>Always provide 3 independent sources per claim.</td></tr>
<tr><td><strong>Using relative dates</strong></td><td>"Last year" is meaningless to an AI with a cutoff date.</td><td>Always use absolute dates: "As of October 2024..."</td></tr>
<tr><td><strong>Ignoring Wikidata</strong></td><td>Gemini and Google AI Overviews heavily rely on the Knowledge Graph.</td><td>Create a Wikidata entry for your brand and populate <code>sameAs</code> links.</td></tr>
<tr><td><strong>No PDF or archived article backup</strong></td><td>Perplexity favors crawlable, stable content.</td><td>Use the Wayback Machine to archive your mention pages.</td></tr>
</tbody></table>
<h2>5. Final GEO/AEO Checklist for Brand Mentions</h2>
<ul>
<li><strong>Claim Inventory:</strong> 20+ atomic facts, each with absolute date, number, and source.</li>
<li><strong>Dedicated Mention Pages:</strong> One per core claim, with executive summary + evidence table.</li>
<li><strong>Schema Present:</strong></li>
<li><code>ClaimReview</code> on every mention page.</li>
<li><code>Mention</code> or <code>NewsArticle</code> with <code>mentions</code> on press releases.</li>
<li><code>Organization</code> with <code>sameAs</code> links to Wikidata, Crunchbase, Wikipedia.</li>
<li><strong>External Citations:</strong> At least 3 independent sources per claim, linked in a table.</li>
<li><strong>Business Citations:</strong> NAP consistency; clean Google Business Profile; LinkedIn/Crunchbase verified.</li>
<li><strong>Archival:</strong> Each mention page crawled by WayBack Machine for stability.</li>
<li><strong>No Contradictions:</strong> All pages agree on the same core facts (date, revenue, leadership names).</li>
</ul>
<h2>6. The Golden Rule</h2>
<p>&gt; <strong>Do not optimize for keywords. Optimize for verifiable truth.</strong></p>
<p>AI engines are becoming fact-checking machines. If your brand mention page is a structured, well-cited, schema-rich document that a human fact-checker would trust, the AIs will trust it too.</p>
<p>The brand that wins the citation graph wins the AI search result.</p>

# How to Optimize for AI Search: Brand Mentions

**Subtitle:** Controlling the Citation Graph in ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews

---

## 1. The New Battleground: The Citation Graph

Traditional SEO optimized for **search result pages**. GEO/AEO optimizes for the **citation graph**.

When an AI engine (ChatGPT, Perplexity, Gemini) answers a user query, it does not browse the open web in real time. It retrieves pre-indexed facts from its training data or retrieval-augmented generation (RAG) databases. Your brand wins when the AI **cites you** as the authoritative source for a specific claim, definition, or data point.

**The core insight:** AI engines prioritize *verifiability* and *directness* over keyword density. A brand mention is strongest when it is:
1.  **Explicitly connected** to a specific, verifiable fact.
2.  **Structured** in machine-readable schema.
3.  **Cited** by other trusted sources (the citation graph).

---

## 2. Understanding the AI Engine Mental Model

Different engines have different trust signals. You must adapt your strategy.

| Engine | Primary Signal | Weakness | Your Strategy |
| :--- | :--- | :--- | :--- |
| **ChatGPT** | WebGPT / Bing index + training data cut-off | Can hallucinate dates/sources if not explicitly written | **Always include dates.** Write absolute facts (e.g., "As of July 2024..."). |
| **Claude** | Anthropic's custom web index + E-E-A-T heavy filtering | Highly sensitive to source quality; prefers .edu, .gov, established publishers | Focus on **backlinks from high-authority domains** to your mention pages. Claude trusts link graphs heavily. |
| **Perplexity** | Own crawl + Bing + Google + deep analysis of PDFs | Penalized heavily for **thin content** or pages that don't answer the query directly | Create **dedicated "Mention Detail" pages** that answer a single, clear question. No fluff. |
| **Gemini** | Google's index (Crawl & BERT based) + Knowledge Graph | Struggles with contradictory claims; needs schema to disambiguate | Use **ClaimReview** and **Mention** schema with precise `sameAs` links. |
| **Google AI Overviews** | Google's MUM / MASSIVE + Search Generative Experience (SGE) | Only shows source links when forced by citation schema; extremely picky about entity authority | Make your brand a **Knowledge Panel entity**. Get a Wikipedia page or solid Wikidata entry. |

**Trade-off:** Tailoring for one engine may slightly reduce performance on another. Optimize for **schema completeness** and **citation depth**—this benefits all major engines.

---

## 3. Step-by-Step GEO/AEO Optimization for Brand Mentions

### Step 1: The "Claim Audit" – Identify What AIs Will Cite About You

Before you optimize, you must know *what facts* about your brand are citation-worthy.

- **Action:** Create a spreadsheet of 20–30 atomic facts about your brand.
- **Example:**
    - "*Company X* was founded in *2015*."
    - "*Product Y* has *99.7% uptime* as of *Q2 2024*."
    - "*Person Z* is the *CEO* and previously served as *CTO at ABC Corp*."
    - "*Award W* was granted by *Gartner* in *March 2024*."

**Why this matters:** AI engines do not "read" your about page holistically. They extract individual triples (Subject–Predicate–Object). Each triple is a potential citation.

### Step 2: Build "Mention Detail Pages" (Not Just Press Releases)

Most brands have a single press release or news section. This is insufficient for AI extraction. You need **dedicated pages** for each major claim or mention.

**Page Structure Template:**

```
DOMAIN.com/mentions/founding-date-2015/
├── H1: How Company X Was Founded in 2015: A Verification
├── H2: Executive Summary
│   └── Verifiable claim: "Company X was legally incorporated in Delaware on March 14, 2015."
├── H2: Primary Evidence
│   └── Link to Secretary of State filing (PDF)
│   └── Link to archived news article from 2015
│   └── Link to Crunchbase / LinkedIn entry (with same date)
├── H2: Citation Table (structured for AI extraction)
│   ├── Claim: Founding Year
│   ├── Value: 2015
│   ├── Source 1: Wayback Machine (link)
│   ├── Source 2: D&B filing (link)
│   └── Source 3: Third-party media mention (link)
├── H2: Related Entities
│   └── Founder name, location, industry classification
└── [Schema Markup Block - See Section 4]
```

**Why this works:** Perplexity and Gemini will crawl this page, find the table, see the external citations, and output: *"Company X was founded in 2015 (Source 1, Source 2)."* The citation graph is satisfied.

### Step 3: Schema Markup – The Machine-Readable Layer

Schema is your primary tool for telling AI engines explicitly: *"This is a brand mention, and this is how it should be cited."*

#### 3A. `ClaimReview` Schema (Gold Standard for Mentions)

Use this when an AI *evaluates* a claim about your brand (e.g., "Is Company X a leader in the space?").

```json
{
  "@context": "https://schema.org",
  "@type": "ClaimReview",
  "url": "https://DOMAIN.com/mentions/sample-claim",
  "claimReviewed": "Company X is the fastest-growing SaaS company in Europe in 2024.",
  "author": {
    "@type": "Organization",
    "name": "Your Brand Name",
    "sameAs": "https://www.wikidata.org/entity/Q12345"
  },
  "datePublished": "2024-10-01",
  "itemReviewed": {
    "@type": "Claim",
    "appearance": [
      {
        "@type": "OpinionNewsArticle",
        "url": "https://third-party-source.com/article"
      }
    ]
  },
  "reviewRating": {
    "@type": "Rating",
    "bestRating": "5",
    "ratingValue": "5",
    "worstRating": "1"
  }
}
```

**Key fields for AI ranking:**
- `claimReviewed`: Must match the exact text you want cited.
- `author.sameAs`: Links to your Knowledge Graph entity. Critical for Gemini and Google AI Overviews.
- `reviewRating.ratingValue`: AI uses this to determine *strength* of the mention. A 5/5 rating signals high verifiability.

#### 3B. `Mention` Schema (Newer, More Specific)

Google introduced this explicitly for brand mentions in news and editorial content.

```json
{
  "@context": "https://schema.org",
  "@type": "Mention",
  "mentions": {
    "@type": "Organization",
    "name": "Your Brand",
    "url": "https://DOMAIN.com",
    "sameAs": [
      "https://twitter.com/yourbrand",
      "https://www.crunchbase.com/company/yourbrand"
    ]
  },
  "datePublished": "2024-10-01",
  "headline": "Salesforce acquires Company X",
  "publisher": {
    "@type": "Organization",
    "name": "Third-Party Publisher",
    "url": "https://publisher-site.com"
  }
}
```

**Benefit:** This explicitly tells Google and Gemini that a *specific* page contains a mention of your brand. It helps AI understand context (positive, neutral, acquisition, launch).

#### 3C. `CiteAs` Schema (For Authoritative Person Mentions)

When a person (CEO, founder) is mentioned, add this to their bio page.

```json
{
  "@context": "https://schema.org",
  "@type": "Person",
  "name": "Jane Doe",
  "affiliation": {
    "@type": "Organization",
    "name": "Your Brand"
  },
  "citation": [
    {
      "@type": "ScholarlyArticle",
      "name": "Why Jane Doe's Leadership Matters in 2024",
      "url": "https://publisher.org/article"
    }
  ]
}
```

**Trade-off:** Overusing `citation` can look spammy. Only link to 3–5 genuinely high-authority external articles.

### Step 4: Business Citation Optimization (For Local AEO)

If your brand has a physical presence, AI engines (especially Google AI Overviews and Gemini) pull business mentions from structured citation sources.

| Platform | Impact on AI | Action |
| :--- | :--- | :--- |
| **Google Business Profile** | High. The #1 source for Google Knowledge Panels | Ensure `Description` field contains your core claim (e.g., "Founded 2015, 99.7% uptime"). |
| **Wikipedia / Wikidata** | Critical for Gemini and Perplexity | Get a verified Wikipedia page or at least a robust Wikidata entity with all your key facts. |
| **Crunchbase / LinkedIn** | Moderate for ChatGPT; High for Perplexity | Update with exact founding date, funding rounds, and leadership. |
| **Bloomberg / SEC EDGAR** | Very high trust signal | If public, ensure your filings are clean. |

**Action step:** Use a tool like BrightLocal or Moz Local to audit your NAP (Name, Address, Phone) consistency across 50+ sites. Inconsistency kills AI trust.

### Step 5: Off-Page Signal Building – The Citation Backlink

A brand mention page without external citations is a monologue. AI engines want to see **triangulation**: three independent sources agreeing on the same fact.

**Strategy:**
1.  **Write the canonical mention page** on your domain (Step 2).
2.  **Pitch a guest article** on a .edu or .gov domain that mentions the same fact and links back to your page.
3.  **Get a third-party media mention** (e.g., TechCrunch, Forrester) that echoes the fact.
4.  **Link those three sources** back to your mention page via the citation table (Step 2) and schema (Step 3).

**Result:** When an AI crawls your mention page, it sees:
- `ClaimReview` with `reviewRating` = 5
- `Mention` schema linking to 3 high-authority external sources
- A clean, atomic fact in a structured table

**The AI will likely cite you.**

---

## 4. Common Pitfalls (Trade-offs & Risks)

| Mistake | Why It Hurts AEO | Fix |
| :--- | :--- | :--- |
| **Keyword stuffing** in mention pages | AI engines detect this as low-quality. Perplexity penalizes heavily. | Write for human clarity. Use AI extraction tables for the machine. |
| **Over-relying on a single source** | ChatGPT will hallucinate if only one source exists. | Always provide 3 independent sources per claim. |
| **Using relative dates** | "Last year" is meaningless to an AI with a cutoff date. | Always use absolute dates: "As of October 2024..." |
| **Ignoring Wikidata** | Gemini and Google AI Overviews heavily rely on the Knowledge Graph. | Create a Wikidata entry for your brand and populate `sameAs` links. |
| **No PDF or archived article backup** | Perplexity favors crawlable, stable content. | Use the Wayback Machine to archive your mention pages. |

---

## 5. Final GEO/AEO Checklist for Brand Mentions

- [ ] **Claim Inventory:** 20+ atomic facts, each with absolute date, number, and source.
- [ ] **Dedicated Mention Pages:** One per core claim, with executive summary + evidence table.
- [ ] **Schema Present:**
    - `ClaimReview` on every mention page.
    - `Mention` or `NewsArticle` with `mentions` on press releases.
    - `Organization` with `sameAs` links to Wikidata, Crunchbase, Wikipedia.
- [ ] **External Citations:** At least 3 independent sources per claim, linked in a table.
- [ ] **Business Citations:** NAP consistency; clean Google Business Profile; LinkedIn/Crunchbase verified.
- [ ] **Archival:** Each mention page crawled by WayBack Machine for stability.
- [ ] **No Contradictions:** All pages agree on the same core facts (date, revenue, leadership names).

---

## 6. The Golden Rule

> **Do not optimize for keywords. Optimize for verifiable truth.**

AI engines are becoming fact-checking machines. If your brand mention page is a structured, well-cited, schema-rich document that a human fact-checker would trust, the AIs will trust it too.

The brand that wins the citation graph wins the AI search result.

#brand-mentions

Stories tagged brand-mentions

How to Optimize for AI Search: Brand Mentions