aeo-scorecard

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.

16 stars

Best use case

aeo-scorecard is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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.

Teams using aeo-scorecard should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/aeo-scorecard/SKILL.md --create-dirs "https://raw.githubusercontent.com/diegosouzapw/awesome-omni-skill/main/skills/development/aeo-scorecard/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/aeo-scorecard/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How aeo-scorecard Compares

Feature / Agentaeo-scorecardStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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

Related Skills

bgo

10
from diegosouzapw/awesome-omni-skill

Automates the complete Blender build-go workflow, from building and packaging your extension/add-on to removing old versions, installing, enabling, and launching Blender for quick testing and iteration.

Coding & Development

Buffer Overflow Payload Generator

16
from diegosouzapw/awesome-omni-skill

Generates a buffer overflow attack payload with a specific stack layout (padding, return address, NOP sled, shellcode) and saves it to a file.

browser-testing

16
from diegosouzapw/awesome-omni-skill

Use when testing web applications, debugging browser console errors, automating form interactions, or verifying UI implementations. Load for localhost testing, authenticated app testing (Gmail, Notion), or recording demo GIFs. Requires Chrome extension 1.0.36+, Claude Code 2.0.73+, paid plan.

browser-fetch

16
from diegosouzapw/awesome-omni-skill

Delegate browser automation to a lightweight subagent (Haiku) to reduce context consumption. Also provides web clipping (HTML→Markdown) via clipper.

Browser Automation Expert

16
from diegosouzapw/awesome-omni-skill

浏览器自动化与网页测试专家。支持基于 MCP 工具(Puppeteer/Playwright)的实时交互,以及基于 Python 脚本的复杂自动化流实现。

bronze-layer-setup

16
from diegosouzapw/awesome-omni-skill

End-to-end Bronze layer creation for testing and demos. Creates table DDLs, generates fake data with Faker, copies from existing sources, and configures Asset Bundle jobs. Covers Unity Catalog compliance, Change Data Feed, automatic liquid clustering, and governance metadata. Use when setting up Bronze layer tables, creating test/demo data, rapid prototyping Medallion Architecture, or bootstrapping a new Databricks project. For Faker-specific patterns (corruption rates, function signatures, provider examples), load the faker-data-generation skill.

brand-identity

16
from diegosouzapw/awesome-omni-skill

Provides the single source of truth for brand guidelines, design tokens, technology choices, and voice/tone. Use this skill whenever generating UI components, styling applications, writing copy, or creating user-facing assets to ensure brand consistency.

brainstorming

16
from diegosouzapw/awesome-omni-skill

Use when creating or developing anything, before writing code or implementation plans - refines rough ideas into fully-formed designs through structured Socratic questioning, alternative exploration, and incremental validation

boxlog-frontend-design

16
from diegosouzapw/awesome-omni-skill

BoxLog専用のフロントエンドデザインスキル。「装飾のない基本体験」を実現するためのUI設計ガイドライン。STYLE_GUIDE.mdを補完し、フォント・アニメーション・デザイン判断基準を提供。

bounty-hunter

16
from diegosouzapw/awesome-omni-skill

Find, evaluate, and submit online bounties and hackathons for prize money. Use when user mentions "bounties", "hackathon", "earn money", "Superteam Earn", "prize money", "submissions", "freelance bounties", or asks to find paid opportunities. Covers discovery, eligibility filtering, content drafting, and submission workflows.

bootstrap-phase-workflow

16
from diegosouzapw/awesome-omni-skill

Integrate the vibe/mature phase workflow into a project

bootstrap-auto

16
from diegosouzapw/awesome-omni-skill

[Implementation] Bootstrap a new project automatically