# Build an AEO Topic Cluster and Question Graph (Step-by-Step)

> Canonical source: [Build an AEO Topic Cluster and Question Graph (Step-by-Step)](https://ai.answer.cloud/pages/build-an-aeo-topic-cluster-and-question-graph-step-by-step/)

Turn a seed topic into a question graph aligned to query fan-out, then publish chunkable answers to win LLM visibility.

Map the real questions an LLM explores (query fan-out), then publish concise, interlinked answers; this is the fastest path to AI visibility.

## Step 1: Define the seed and goal
- Seed topic: e.g., “Business credit cards for startups”
- Outcome: conversions, demo requests, or assisted discovery

## Step 2: Generate the question graph (fan-out)
Create categories of question variants:
- Clarifications: what/why/how (e.g., “how do signup bonuses work?”)
- Constraints: region, budget, industry, limits
- Comparisons: A vs B, pros/cons, alternatives
- Temporal: latest updates, 2026 changes, deadlines
- Adjacent tasks: eligibility, documentation, fees, rewards

Aim for 40–120 questions for a meaningful cluster.

## Step 3: Cluster by intent and stage
- Awareness: definitions, frameworks
- Evaluation: comparisons, checklists
- Decision: pricing, implementation, onboarding
Map each question to a page or section; combine thin variants into one robust answer.

## Step 4: Prioritize by business value
Score each question on:
- Buyer fit (ICP relevance)
- Conversion proximity (signal strength)
- Moat (can you be authoritative?)
Tackle high-score questions first.

## Step 5: Create chunkable answers
For each page:
- Start with a 1–2 sentence direct answer
- Use H2/H3, bullets, short paragraphs
- Add a small FAQ and 1–4 trustworthy citations
- Include a “Sources” section and update date

## Step 6: Link the cluster
- Internal links from the pillar to subpages and laterally between siblings
- Add a short “Related questions” section on each page
- Ensure sitemap and llms.txt expose the cluster clearly

## Step 7: Publish and measure
- Watch edge logs for AI bot hits by path
- Track LLM referrals and compare engagement vs baseline
- Update content freshness and expand uncovered questions monthly

## Templates
- Page outline:
  - Direct answer (2 sentences)
  - What/Why/How sections
  - Mini-FAQ (3–5 questions)
  - Sources
- Editorial brief:
  - Question, audience, desired action
  - Key facts, constraints, citations
  - Metrics to monitor post-publish

## FAQs
- How big should a cluster be? Large enough to cover the conversation, small enough to publish within a quarter.
- Do I need a page per question? No—group near-duplicates; favor comprehensive but scannable pages.
- How soon do LLM signals appear? Bot hits can appear within days; human LLM referrals often follow after the cluster gains authority.

## Sources
- answer.cloud on query fan-out and why it drives AI visibility
- AEO 101 and best-practice guidance for chunkable answers and structure