Query Expansion Strategy
Maximize AI visibility through query fan-out coverage.
How LLMs Process Queries
LLMs expand queries into 5-10 semantic variations (sub-questions) before generating responses. To get cited:
- Cover topic clusters comprehensively
- Include semantic variations naturally
- Address related questions
- Build entity relationships
- Create topical depth
Query Fan-Out Analysis
Example: "How to prioritize leads" fans out to:
- "What methodologies exist for lead prioritization?"
- "What tools help with lead scoring?"
- "What metrics indicate lead quality?"
- "How do sales teams rank prospects?"
- "What is lead scoring automation?"
Your content must answer ALL sub-questions to maximize visibility.
Tools for Fan-Out Analysis
| Tool | Use |
|---|---|
| Kuforia | Visualizes how AI breaks down topics |
| Dan's Fan-out Tool | Shows sub-question decomposition |
| ChatGPT/Perplexity | Ask "what sub-questions would you ask to answer X?" |
Semantic Coverage Checklist
For any target topic:
- Core question - Direct answer to primary query
- Definition - What is X? (for newcomers)
- How-to - How do you do X?
- Why - Why is X important?
- Comparison - How does X compare to Y?
- Examples - What are examples of X?
- Tools - What tools help with X?
- Metrics - How do you measure X?
- Mistakes - What mistakes to avoid with X?
- Trends - What's changing about X?
Content Structure for Fan-Out
Recommended sections:
## What is [Topic]?
[Definition for newcomers]
## Why [Topic] Matters
[Business case, importance]
## How to [Topic]
[Step-by-step methodology]
## [Topic] Tools and Software
[Tool comparison table]
## [Topic] Metrics to Track
[KPIs and measurement]
## Common [Topic] Mistakes
[What to avoid]
## FAQ
### [Sub-question 1]?
[Complete answer]
### [Sub-question 2]?
[Complete answer]Semantic Footprint Expansion
Build entity relationships around your topic:
Primary Topic: Lead Scoring
├── Related Concepts: lead qualification, MQL, SQL, BANT
├── Tools: HubSpot, Salesforce, Marketo
├── Metrics: conversion rate, lead velocity
├── Personas: sales rep, marketing manager, SDR
└── Use Cases: B2B sales, SaaS, enterpriseInclude related terms naturally throughout content.
Analysis Output
When analyzing content for query expansion:
Target Query: [query]
Sub-Questions Covered: X/10
☑ Definition/What is
☑ How-to/Process
☐ Why/Importance (MISSING)
☐ Comparison (MISSING)
☑ Tools/Software
...
Semantic Coverage: X%
Missing Entities: [list]
Recommendations:
1. Add section on [missing sub-question]
2. Include comparison with [related concept]
3. Add FAQ addressing [query variation]