Building our first AI visibility dashboard. Need help on what to include.
Current SEO reporting:
What I think we need for AI:
Questions:
I’ve built AI visibility dashboards for multiple enterprises. Here’s the framework.
Core Metrics (Must Have):
| Metric | Definition | Benchmark |
|---|---|---|
| Brand Visibility Score | % of relevant AI responses mentioning you | 70%+ exceptional |
| Citation Frequency | How often your URLs appear as sources | Track trend |
| Share of Voice | Your mentions vs competitors | 15% top, 25-30% leader |
| Average Rank Position | Position in multi-brand responses | Lower is better |
| Cross-Platform Coverage | Presence across 4+ platforms | 2.8x citation likelihood |
Supporting Metrics (Should Have):
| Metric | Definition | Why It Matters |
|---|---|---|
| Sentiment Score | Positive/negative/neutral context | Recommendation likelihood |
| Citation Drift | Monthly volatility | 40-60% normal |
| Content Recency Impact | % from recent content | 65% from past year |
| Source Analysis | Which of your pages cited | Content strategy |
The executive summary:
Your report should answer: “How visible is our brand in AI search?”
Dashboard layout that works.
Page 1: Executive Summary
Page 2: Platform Breakdown
| Platform | Visibility | Trend | Top Cited Content |
|---|---|---|---|
| ChatGPT | 42% | +5% | [Link] |
| Perplexity | 38% | +8% | [Link] |
| Google AI | 55% | +2% | [Link] |
| Claude | 28% | New | [Link] |
Page 3: Competitive Analysis
| Competitor | Their SOV | Our SOV | Gap |
|---|---|---|---|
| Competitor A | 28% | 22% | -6% |
| Competitor B | 18% | 22% | +4% |
| Competitor C | 15% | 22% | +7% |
Page 4: Content Performance
Which pages get cited most Which topics we’re winning Content gaps to address
Page 5: Recommendations
Prioritized action items based on data
The foundation of good AI reporting is the query panel.
What’s a query panel:
25-30 tracked prompts that represent your target audience’s questions.
How to select queries:
| Category | Example | Why Include |
|---|---|---|
| Awareness | “What is [category]?” | Top of funnel |
| Consideration | “Best [category] for [use case]” | Comparison stage |
| Decision | “[Your brand] vs [competitor]” | Bottom of funnel |
| Feature-specific | “How to [specific task]” | Detailed queries |
Query selection criteria:
Warning:
If your query panel doesn’t match real user behavior, your metrics are meaningless.
How to build:
Reporting cadence that works.
Weekly (internal team):
Monthly (stakeholder report):
Quarterly (strategic review):
Why monthly is the baseline:
| Issue | Why Not Weekly |
|---|---|
| AI volatility | 40-60% variation normal |
| Overreaction risk | Changes might reverse |
| Resource drain | Too much reporting time |
The 30-day minimum rule:
First month data is establishing baseline. Don’t panic about fluctuations.
Week 6-8 is when actionable patterns emerge.
Platform-specific reporting considerations.
ChatGPT reporting focus:
| Metric | Why Important |
|---|---|
| Parametric mentions | Without web search |
| Retrieved citations | With web search |
| Topic coverage | What you’re known for |
Perplexity reporting focus:
| Metric | Why Important |
|---|---|
| Real-time citations | Freshness signals |
| Source diversity | 8,000+ unique domains cited |
| Reddit correlation | 46.7% of top sources |
Google AI Overviews focus:
| Metric | Why Important |
|---|---|
| Traditional rank correlation | 93.67% link to top 10 |
| Deep page discovery | 4.5% from Page 1 directly |
| YouTube integration | Video content |
Claude focus:
| Metric | Why Important |
|---|---|
| Brave Search backend | Different index |
| Constitutional AI preferences | Trustworthy sources |
Report should break down by platform, not just aggregate.
Connecting visibility to business outcomes.
Attribution metrics to include:
| Metric | Source | Purpose |
|---|---|---|
| AI referral traffic | GA4 | Direct attribution |
| Brand search growth | GSC | Correlational |
| “Discovered via AI” responses | Form field | Self-reported |
| Sales-mentioned AI | CRM | Anecdotal |
How to set up GA4 for AI tracking:
Create segments for:
The attribution section should answer:
“What business impact is AI visibility having?”
| Signal | What It Suggests |
|---|---|
| AI traffic growing | Direct discovery happening |
| Brand search correlates with visibility | Indirect discovery working |
| Sales hears AI mentions | Awareness impact |
| Form responses cite AI | Attribution working |
Honest caveat:
Full attribution is impossible. Show what you can measure and correlate the rest.
This is exactly what I needed. Here’s my report structure.
Monthly AI Visibility Report:
Section 1: Executive Summary
Section 2: Core Metrics
| Metric | Current | MoM | Benchmark |
|---|---|---|---|
| Visibility Score | X% | +/- | 70%+ |
| Share of Voice | X% | +/- | 15-25% |
| Citation Frequency | X | +/- | Trend |
| Cross-Platform | X/4 | +/- | 4+ |
Section 3: Platform Breakdown
Section 4: Competitive Analysis
Section 5: Content Performance
Section 6: Business Attribution
Section 7: Recommendations
Tool: Using Am I Cited for data collection.
Thanks everyone for the framework!
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