What does a mature GEO strategy actually look like? Looking for examples beyond basics

Let me describe what mature GEO looks like at our organization.

Basic vs Mature comparison:

What mature looks like in practice:

1. Integrated strategy: GEO isn’t separate from SEO, PR, or brand. It’s a lens applied across all activities. Every content piece, every PR mention, every brand activity is evaluated for AI visibility impact.

2. Predictive approach: We don’t just track current visibility. We model:

• Which topics are gaining AI query volume
• Where competitors are investing
• What content gaps represent opportunity

3. Attribution to business outcomes: We trace:

• AI citation → Branded search → Site visit → Conversion
• The full path from visibility to revenue

4. Platform-specific strategies: Different approaches for ChatGPT vs Perplexity vs Claude based on their retrieval behaviors.

5. Competitive intelligence: We know competitor visibility scores, track their changes, and respond strategically.

Executive perspective on mature GEO.

What changed at the leadership level:

Before mature GEO:

• “What’s our organic traffic?”
• GEO as SEO team experiment
• No board-level visibility

After mature GEO:

• “What’s our AI visibility score and trend?”
• GEO in strategic planning discussions
• Board reporting on AI visibility

The metrics I report:

1. Visibility index - Aggregate score across platforms
2. Share of voice - vs top 3 competitors
3. Topic coverage - % of target topics where we’re cited
4. Business attribution - Pipeline influenced by AI visibility
5. Trend trajectory - Are we improving?

The strategic integration:

Product launches include GEO component PR strategy aligned with citation goals Content budget allocated by AI visibility potential Competitive positioning considers AI presence

The culture shift:

Marketing team thinks “Will this help us get cited?” for every initiative.

That’s maturity - when GEO thinking is embedded, not bolted on.

Analytics perspective on mature GEO.

The measurement evolution:

Level 1 (Basic):

• Are we cited? (Yes/No)
• How often? (Count)

Level 2 (Developing):

• Visibility score
• Platform breakdown
• Topic coverage

Level 3 (Mature):

• Attribution modeling
• Predictive indicators
• Business impact
• Competitive position

What mature measurement looks like:

Dashboard components:

• Real-time visibility score (automated)
• Week-over-week trend analysis
• Platform-specific performance
• Topic gap identification
• Competitive share of voice
• Attribution to conversions

The attribution model:

We track:

1. AI platform citation (recorded by Am I Cited)
2. Subsequent branded search (within 7 days)
3. Site visit (attributed to AI awareness)
4. Conversion (attributed through funnel)

Not perfect, but directionally valuable.

The predictive layer:

Based on historical patterns:

• Topic velocity (which topics gaining AI attention)
• Citation correlation with authority signals
• Competitor movement indicators

We forecast visibility 3-6 months out.

Content team perspective on mature GEO.

How content process changed:

Basic: “Write a blog post about X topic”

Mature: “Create comprehensive content on X topic, optimized for AI citation, addressing these specific questions, with expert positioning for our author, connected to our topic cluster, monitored for citation performance”

The content brief evolution:

Now includes:

• Target questions to answer
• Citation-worthy statements to include
• Expert signals to establish
• Related topics to cover
• Schema requirements
• Monitoring setup

The review process:

Before publish, content is checked for:

• AI extractability (can statements be cited?)
• Question coverage (are all questions answered?)
• Expert signals (is authority clear?)
• Technical requirements (schema, structure)

The performance loop:

After publish:

• Citation monitoring activated
• Performance reviewed at 30/60/90 days
• Content updated based on citation gaps
• Continuous optimization cycle

The team structure:

Content, SEO, and PR work together on AI visibility. Not siloed. Weekly syncs on visibility goals.

PR’s role in mature GEO.

The integration:

PR is no longer just media coverage. It’s AI authority building.

What we do differently:

1. Citation-aware pitching: When pitching stories, we think about which quotes/information AI systems might cite.

2. Expert positioning: Building our executives as recognized experts that AI systems trust and cite.

3. Authority placement: Getting mentions on sites AI systems consider authoritative.

4. Consistent messaging: Ensuring our brand story is consistent everywhere AI might learn about us.

The measurement:

PR success now includes:

• Did the coverage result in improved AI visibility?
• Are our experts being cited in AI responses?
• Is our brand accurately represented in AI?

The coordination:

Weekly sync with content and SEO:

• What topics need authority building?
• What experts should be positioned?
• What publications would help most?

PR has become a key GEO input.

Agency view on client maturity levels.

What we see across clients:

Immature (50% of clients):

• No GEO monitoring
• Reactive to issues
• Siloed in SEO team
• No clear metrics

Developing (35% of clients):

• Basic monitoring
• Some content optimization
• Monthly reporting
• Starting to integrate

Mature (15% of clients):

• Real-time monitoring
• Predictive strategy
• Cross-team integration
• Business attribution

The maturity journey:

Most companies move through stages:

Stage 1-2: Awareness and basics (3-6 months) Stage 2-3: Process development (6-12 months) Stage 3-4: Strategic integration (12-18 months)

The blockers:

• Lack of executive buy-in
• Siloed team structure
• No clear ownership
• Inadequate tooling

The accelerators:

• Competitive pressure (competitor is visible, you’re not)
• Executive sponsorship
• Integrated team structure
• Right monitoring tools

Cutting edge approaches I’m seeing.

Beyond current maturity:

1. AI-generated content monitoring: Monitoring not just if you’re cited, but how accurately. Correcting AI misconceptions proactively.

2. Real-time response: Detecting visibility drops immediately and triggering content/PR responses.

3. Multi-modal optimization: Optimizing for image and video citations as AI becomes multimodal.

4. Agentic commerce preparation: Preparing for AI systems that will recommend and facilitate purchases.

5. Custom model considerations: As companies build custom AI, optimizing for enterprise AI systems beyond public ones.

Where the leaders are heading:

GEO as core business capability, not marketing function. AI visibility as competitive moat. Predictive, proactive, integrated.

The advice:

Build the foundation now. The companies investing in mature GEO today will dominate AI discovery tomorrow.

This thread painted a clear picture of maturity.

My understanding now:

Mature GEO characteristics:

1. Strategic integration - Across all marketing functions
2. Predictive approach - Not just tracking, anticipating
3. Business attribution - Connected to revenue
4. Cross-functional - Content, SEO, PR aligned
5. Real-time monitoring - Not monthly checks
6. Competitive intelligence - Strategic positioning

My gap assessment:

• We have basics but lack integration
• No predictive capability yet
• Attribution needs development
• Teams still somewhat siloed

My maturity roadmap:

Next 3 months:

• Implement real-time monitoring (Am I Cited)
• Start cross-functional syncs
• Develop initial attribution tracking

6-12 months:

• Build predictive capability
• Full team integration
• Competitive intelligence system
• Executive reporting

12-18 months:

• Strategic planning integration
• Mature measurement
• Competitive excellence

Thanks for showing me what to aim for!