Aeo Geo

What This Does

Optimize AI engine visibility.

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Quick Start

Step 1: Create a Project Folder

Create a dedicated folder for this workflow (e.g. ~/marketing/aeo-geo).

Step 2: Download the Template

Click Download above and save the file as CLAUDE.md in that folder.

Step 3: Run the Workflow

Open the folder in Claude Code and describe your goal. Claude will prompt you for any missing inputs, follow the structured process, and produce a complete deliverable.

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Inputs You'll Need

Claude will prompt for the brand context, objective, and any asset references needed to produce the deliverable.

How It Works

Primary Workflow: AI Visibility Audit & Optimization

1. Discovery & Baseline

   • Collect brand details, target queries (10-25 queries), and competitor list
   • Document current schema markup, Knowledge Graph presence, and Wikipedia/Wikidata status
   • Identify the business model to determine which AI platforms matter most
   • Catalog existing authoritative content assets (whitepapers, research, data, expert bios)
   • Assess YMYL classification — brands in health, finance, or legal face higher authority thresholds

2. AI Platform Testing

   • For each target query, document how the brand appears (or fails to appear) on:
     • Google AI Overviews
     • ChatGPT (latest model)
     • Perplexity
     • Gemini
     • Microsoft Copilot
   • Score each result: Cited (direct mention with link), Referenced (mentioned without link), Absent, Misrepresented
   • Capture exact AI-generated text for each query as a baseline

3. Entity Consistency Check

   • Audit brand name, founding date, leadership, product descriptions, and key claims across all knowledge sources
   • Flag inconsistencies between sources (e.g., different founding years on Crunchbase vs. Wikipedia)
   • Prioritize fixes by source authority weight

4. Gap Analysis & Strategy

   • Identify patterns: Which query types yield citations? Which don't?
   • Map content gaps: What authoritative content is missing that AI models need?
   • Assess structured data gaps: What schema markup is missing or incorrect?
   • Benchmark against competitors who ARE getting cited

5. Optimization Execution Plan

   • Prioritized list of content to create or restructure
   • Schema markup implementation plan
   • Knowledge Graph correction/enhancement steps
   • Entity consistency fix checklist
   • Content formatting guidelines for AI-first optimization

6. Monitoring & Iteration

   • Define monitoring cadence (weekly for priority queries, monthly for full audit)
   • Set up tracking framework to detect citation changes
   • Establish KPIs: citation rate, accuracy score, query coverage percentage
   • Track competitor citation changes as part of ongoing monitoring
   • Re-test after major content updates or schema implementations to measure impact
   • Log all AI platform model updates that may affect visibility (new model releases, retrieval changes)

Secondary Workflow: Citation-Optimized Content Creation

1. Identify a target query cluster where the brand should be cited but currently is not
2. Analyze what sources ARE being cited for those queries — study their content structure, authority signals, and formatting
3. Create or restructure content that surpasses cited sources in:
   • Factual accuracy and specificity (include precise data, dates, numbers)
   • Clear definitional statements (AI models favor content with unambiguous definitions)
   • Structured formatting (clear headings, bullet points, tables that AI can parse)
   • Source credibility signals (author credentials, citations to primary research, organizational authority)
4. Implement supporting schema markup (FAQ, HowTo, Article, Organization as appropriate)
5. Build inbound authority signals (internal links from high-authority pages, external citations)
6. Re-test AI platform responses 2-4 weeks after publication to measure citation pickup

What You Get

A complete, brand-aligned deliverable ready to review, share, or hand off to execution.