aeo-scorecard

name	aeo-scorecard
description	Measurement framework for Answer Engine Optimization (AEO). Provides AI visibility metrics, share of voice tracking, citation monitoring, and referral demand measurement. Use when discussing AEO/GEO metrics or AI visibility performance.
triggers	["AEO metrics","AI visibility measurement","answer engine performance","GEO scorecard","AI share of voice","citation tracking"]

AEO Scorecard: Measuring AI Visibility

The Four AEO Metrics

Track these metrics to measure Answer Engine Optimization success:

1. AI Visibility

Definition: Are you recommended for your priority queries?

How to Measure:

• Test priority queries in ChatGPT, Perplexity, Gemini, Claude
• Document which queries return your brand
• Track visibility over time (weekly/monthly)

Tools:

• HubSpot AEO Grader (free audit)
• XFunnel (comprehensive tracking)
• Manual testing with query lists

Target: Appear in recommendations for 60%+ of priority queries.

2. AI Share of Voice

Definition: Of all recommendations for a query, how often is YOUR brand named vs. competitors?

Calculation:

Share of Voice = (Your mentions / Total brand mentions) × 100

Why It Matters:

• Distinguishes platform changes (everyone drops) from brand failures (you drop, competitors stay)
• Tracks competitive position in AI recommendations

Example:

• Query: "Best CRM for small business"
• Total recommendations across 10 AI sessions: 50 brand mentions
• Your brand mentioned: 8 times
• Share of Voice: 16%

Target: Match or exceed your traditional search market share.

3. AI Citations

Definition: How often is YOUR WEBSITE the source of the answer?

Why It Matters:

• Being cited = more positive recommendation
• Citation = authority signal for future queries
• Direct traffic potential from "learn more" links

How to Track:

• Monitor AI bot traffic in analytics (GPTBot, Anthropic-AI, etc.)
• Use XFunnel to track citation sources
• Test queries and note source attribution

Target: Be cited (not just mentioned) in 30%+ of relevant queries.

4. Referral Demand

Definition: Traffic and conversions that originated in AI but didn't click through immediately.

The Problem: AI users often:

1. Get answer from AI
2. Remember brand name
3. Search directly or visit later
4. No referral attribution

How to Measure: Implement post-purchase survey:

• "How did you first hear about us?"
• Options: "AI assistant (ChatGPT, Perplexity, etc.)"

Survey Placement:

• Post-purchase confirmation
• Onboarding flow
• Trial signup

Target: Track trend over time; aim for growth in AI-attributed discovery.

AEO Scorecard Template

┌─────────────────────────────────────────────────────────┐
│                    AEO SCORECARD                        │
│                    Month: [DATE]                        │
├─────────────────────────────────────────────────────────┤
│                                                         │
│  AI VISIBILITY                          [X]% → Target: 60%
│  ──────────────────────────────────────                 │
│  Priority queries with brand presence: X/Y              │
│                                                         │
│  AI SHARE OF VOICE                      [X]% → Target: Match SEO
│  ──────────────────────────────────────                 │
│  Your mentions / Total brand mentions                   │
│  Competitor A: X%  |  Competitor B: X%  |  You: X%      │
│                                                         │
│  AI CITATIONS                           [X]% → Target: 30%
│  ──────────────────────────────────────                 │
│  Queries where YOUR site is cited: X/Y                  │
│                                                         │
│  REFERRAL DEMAND                        [X]% → Trend: ↑↓
│  ──────────────────────────────────────                 │
│  Post-purchase survey: "Found via AI"                   │
│                                                         │
└─────────────────────────────────────────────────────────┘

Measurement Tools

Tool	What It Measures	Cost
HubSpot AEO Grader	AI visibility audit	Free
XFunnel	Full AEO tracking suite	Paid
Manual Testing	Query-by-query visibility	Free (time)
Google Analytics	AI bot traffic	Free
Post-Purchase Survey	Referral demand	Free

Setting Up AI Bot Tracking

In Google Analytics 4, create a segment for AI crawler traffic:

User Agents to Track:

• GPTBot (OpenAI)
• Anthropic-AI (Claude)
• Google-Extended (Gemini)
• PerplexityBot
• CCBot (Common Crawl, used by many)

Interpreting Results

Scenario Analysis:

Visibility	Share of Voice	Diagnosis
↓ Down	↓ Down	Platform algorithm change (industry-wide)
↓ Down	→ Stable	Your content quality declined
→ Stable	↓ Down	Competitors improved
↑ Up	↑ Up	Your AEO strategy is working

Action Triggers

Metric	Threshold	Action
Visibility < 40%	Critical	Run llm-optimizer on all priority content
Share of Voice < competitor	Competitive gap	Run entity-builder for authority building
Citations < 20%	Authority gap	Add original data, improve fact-density
Referral Demand flat	Attribution gap	Improve survey placement and options

Monthly Review Cadence

1. Week 1: Run visibility audit on priority queries
2. Week 2: Calculate share of voice vs. top 3 competitors
3. Week 3: Analyze citation sources and bot traffic
4. Week 4: Review referral demand survey data
5. Monthly: Update scorecard, prioritize improvements