Hvordan identifiserer du relaterte emner som AI assosierer med merkevaren din? Ønsker å utvide synligheten min

Let me share my framework for identifying related topics:

The Concentric Circles Model:

Core Topics (innermost)
├── Adjacent Topics (high relevance)
│   ├── Peripheral Topics (moderate relevance)
│   │   └── Tangential Topics (low relevance)

How to identify each layer:

Practical discovery methods:

1. AI interrogation

   • Ask: “What topics relate to [your core topic]?”
   • Ask: “If someone is interested in [core], what else might they want to know?”

2. Competitor analysis

   • What do competitors cover that you don’t?
   • What gets them cited that you’re missing?

3. Customer research

   • What other questions do customers ask?
   • What related problems do they have?

Practical methods for discovering related topics:

Method 1: AI brainstorming

Prompt: “I’m an expert in [your topic]. What related topics should I also cover to provide comprehensive value to my audience?”

Document the suggestions. Test which ones appear in AI answers for related queries.

Method 2: “People also ask” analysis

For your core keywords, note all “People also ask” questions. These represent semantic relationships Google (and AI) sees.

Method 3: Topic co-occurrence

Look at content that ranks for your topics. What other topics do those pages also cover? This reveals co-occurrence patterns.

Method 4: Competitor topic mapping

Gaps where multiple competitors cover something you don’t = opportunities.

Method 5: Customer journey mapping

What does your customer need to understand:

• Before they need your solution?
• While evaluating options?
• After purchase?

Each stage has related topic opportunities.

Connecting keyword research to topic expansion:

Traditional keyword → Related topic discovery:

1. Seed keyword in SEO tool
2. Explore “related keywords”
3. Group into topic clusters
4. Evaluate each cluster for AI opportunity

Tools that help:

Example process:

Core: “Project management software”

Related keyword clusters found:

• Team collaboration tools → Adjacent topic
• Task management methods → Adjacent topic
• Remote team productivity → Peripheral topic
• Agile methodology → Adjacent topic
• Time tracking tools → Peripheral topic

Each cluster = potential topic expansion area.

AI-specific topic relationship discovery:

Technique: Topic relationship mapping via AI

Step 1: Ask AI about your core topic “Explain [your topic] comprehensively”

Step 2: Note every related concept mentioned Document entities, terms, concepts that appear

Step 3: Ask about each related concept “How does [related concept] relate to [your topic]?”

Step 4: Map the relationships Create a visual map of topic connections

What you’ll discover:

• Topics AI strongly associates (frequently mentioned together)
• Topics AI weakly associates (mentioned occasionally)
• Topics AI doesn’t associate (might be opportunity or too far)

Monitoring ongoing:

Periodically ask AI: “What topics is [your brand] associated with?”

Track changes. As you expand, does AI update its understanding?

Am I Cited can help track which topics your brand appears for over time.

Enterprise approach to topic expansion:

Our systematic process:

Phase 1: Topic universe definition

• List all potential topics (broad)
• Categorize by relevance layer
• Score business value

Phase 2: Authority assessment

• Where do we have expertise?
• Where do we have existing content?
• Where do we have credibility?

Phase 3: Opportunity analysis

• AI answer quality for each topic
• Competitor coverage
• Search/query demand

Phase 4: Prioritization matrix

Phase 5: Expansion roadmap

• Quarter 1: Deepen core topics
• Quarter 2: Expand to adjacent topics
• Quarter 3: Evaluate peripheral topics
• Quarter 4: Refine based on results

Key insight:

Systematic expansion beats random. Plan your topic expansion like you’d plan a product roadmap.

Excellent frameworks everyone. Here’s my topic expansion plan:

Phase 1: Discovery (Week 1)

1. AI interrogation for related topics
2. Competitor topic analysis
3. “People also ask” mining
4. Customer question review

Phase 2: Mapping (Week 2)

Create topic map with circles:

• Core topics (already strong)
• Adjacent topics (expand first)
• Peripheral topics (evaluate carefully)

Phase 3: Prioritization (Week 2-3)

Score each potential topic:

• Relevance to core (0-10)
• Our expertise level (0-10)
• AI opportunity (0-10)
• Business value (0-10)

Phase 4: Expansion plan (Week 3)

• Month 1: 3 adjacent topics
• Month 2: 2 adjacent topics
• Month 3: Evaluate, potentially 1 peripheral

Validation:

• Monitor AI brand associations monthly
• Track citation expansion to new topics
• Watch for authority dilution signals

Key principles:

• Expand one layer at a time
• Build depth before breadth
• Monitor AI’s understanding
• Stop if authority dilutes

Thanks everyone for the systematic approaches.