My CMO asked for “AI search reports” after reading an article about ChatGPT taking traffic from Google.
Problem: I’ve been doing marketing analytics for 8 years and I have no idea what to track.
What I know how to report on:
What I don’t know:
Google Analytics shows some referral traffic from chat.openai.com and perplexity.ai, but it’s tiny. Is that all there is?
Anyone building real AI search reports? What does yours look like?
I’ve been building AI search reports for clients for 18 months. Here’s the framework:
Tier 1: Core Metrics (Track Weekly)
| Metric | What It Measures | Why It Matters |
|---|---|---|
| Brand Mention Frequency | How often you appear in AI responses | Basic visibility indicator |
| Citation Rate | % of mentions that link to your site | Quality of visibility |
| Share of Voice | Your mentions vs competitors | Competitive positioning |
| Position Distribution | Where you appear in responses (1st, 2nd, etc.) | Primacy matters |
Tier 2: Quality Metrics (Track Monthly)
| Metric | What It Measures | Why It Matters |
|---|---|---|
| Sentiment | How AI describes you (positive/neutral/negative) | Brand perception |
| Context | What topics trigger your mentions | Strategic insights |
| Platform Distribution | ChatGPT vs Perplexity vs others | Platform strategy |
| Prompt Categories | Which question types mention you | Content gaps |
Tier 3: Business Metrics (Track Monthly)
| Metric | What It Measures | Why It Matters |
|---|---|---|
| AI Referral Traffic | Visits from AI platforms | Direct traffic impact |
| AI-Attributed Conversions | Leads/sales from AI traffic | Business value |
| Content Citation Rate | Which pages get cited | Content strategy |
The reporting stack:
This isn’t as mature as SEO reporting yet, but these metrics give stakeholders what they need.
Mix of both:
Automated (Tools):
Manual (Validation):
Why both:
Tools give scale. Manual testing gives context.
For example, Am I Cited might show you appeared in 45% of prompts this week. Manual testing shows you that when you appear, AI describes you as “a budget option” - context that matters for strategy.
For stakeholder reports, automated data gives the numbers. Manual testing gives the story.
Realistic time investment:
C-suite perspective on what stakeholders actually want:
They don’t care about:
They care about:
My executive AI report structure:
Page 1: Summary
Page 2: Competitive Landscape
Page 3: Recommendations
That’s it. One page of metrics, one page of context, one page of actions. Executives don’t need more.
Practical tip: GA4 setup for AI traffic tracking
Most AI referral traffic shows up fine, but here’s how to ensure you catch everything:
Step 1: Create AI Referral Segment Filter referral source containing:
Step 2: Track “Dark” AI Traffic Some AI traffic comes through as direct (copy-paste from AI response). Watch for:
Step 3: Create Custom Report Combine:
Reality check:
You’ll never track 100% of AI-influenced traffic. Users might ask AI for recommendations, then Google your brand directly. That shows as organic traffic.
Track what you can. Use citation data to infer the rest. Don’t obsess over perfect attribution.
We do AI reports for 12 clients. Here’s what works:
Monthly Report Template:
Section 1: Visibility Scorecard
Section 2: Share of Voice
Section 3: Citation Analysis
Section 4: Traffic Attribution
Section 5: Recommendations
What clients love:
What clients don’t need:
One metric nobody’s mentioned: Content Citation Efficiency
Formula: Citations per piece of content
Example:
Now break it down:
This tells you:
We found that our FAQ pages get cited 4x more than regular blog posts. That insight changed our content strategy.
Include “content type performance” in your AI reports. Stakeholders love seeing which investments are paying off.
Simple approach for smaller teams:
Minimum Viable AI Report (2 hours/month):
Tool: Am I Cited (or similar)
Manual testing (30 min/week):
Monthly report (1 hour):
That’s it.
Don’t overthink it. Start simple, add complexity as you learn what matters for your business.
Our first report was literally:
Stakeholders appreciated the simplicity.
At enterprise scale, we track additional metrics:
Business Unit Breakdown:
Attribution Modeling:
Alerting:
Quarterly Deep Dives:
Key executive metrics:
This is overkill for most companies, but if you’re enterprise scale, you need this granularity.
This thread gave me everything I need. Here’s my reporting plan:
Immediate Setup:
Monthly Report Structure:
Key Metrics to Track:
Manual Validation:
Key insight: Start simple. The CMO doesn’t need complexity - they need “are we visible, how do we compare, what should we do?”
Thanks everyone for the frameworks and practical examples!
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