AgentSkillsCN

aeo-scorecard

答案引擎优化(AEO)的衡量框架。提供 AI 可见性指标、声量追踪、引用监测,以及推荐流量的测量。适用于讨论 AEO/GEO 指标,或评估 AI 可见性表现时使用。

SKILL.md
--- frontmatter
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:

code
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

code
┌─────────────────────────────────────────────────────────┐
│                    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

ToolWhat It MeasuresCost
HubSpot AEO GraderAI visibility auditFree
XFunnelFull AEO tracking suitePaid
Manual TestingQuery-by-query visibilityFree (time)
Google AnalyticsAI bot trafficFree
Post-Purchase SurveyReferral demandFree

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:

VisibilityShare of VoiceDiagnosis
↓ Down↓ DownPlatform algorithm change (industry-wide)
↓ Down→ StableYour content quality declined
→ Stable↓ DownCompetitors improved
↑ Up↑ UpYour AEO strategy is working

Action Triggers

MetricThresholdAction
Visibility < 40%CriticalRun llm-optimizer on all priority content
Share of Voice < competitorCompetitive gapRun entity-builder for authority building
Citations < 20%Authority gapAdd original data, improve fact-density
Referral Demand flatAttribution gapImprove 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