Terms used for measuring AI-driven content

Optimising web content for AI Agents is called AEO (Answer Engine Optimisation). See how to prepare web copy for AI Agents.

This pages describes key terms for measuring AEO (Answer Engine Optimisation).

1. Definition for ‘Featured Snippets'

Featured Snippets are concise, high-authority excerpts from web pages that search engines and AI platforms extract to directly answer user queries – often without requiring a click. They’re a key metric for Answer Engine Optimisation (AEO) because they signal that your content is structured, relevant, and trusted enough to be cited by AI.

What is a Featured Snippet?

A Featured Snippet is a highlighted block of text that appears at the top of Google’s search results (Position Zero) or is extracted by AI platforms like ChatGPT, Copilot, or Perplexity to answer a question.

It typically includes:

• A direct answer to a query
• A source citation (your website link)
• Sometimes an image, table, or list

Why it matters for AI-driven content

How to win with Featured Snippets

• Answer questions directly in the first paragraph
• Use structured formats: lists, tables, definitions
• Apply FAQ and HowTo schema markup
• Target long-tail, question-style keywords
• Ensure clarity and brevity—AI prefers clean, extractable text

 

2. Definition for ‘Long-Tail Keywords’

Long-tail keywords are highly specific, multi-word search phrases that reflect natural language queries, making them essential for AI-driven content and Answer Engine Optimisation (AEO). They help your content match the way users actually ask questions in platforms like ChatGPT, Copilot, and voice assistants.

What Are Long-Tail Keywords?

• Typically 3+ words long, often phrased as questions or conversational queries.

Examples:

• Short-tail: “AI ethics”
• Long-tail: “How does AI impact ethical decision-making in multicultural councils?”
  
  

Why They Matter for AI-Driven Content

How to Use Long-Tail Keywords for AEO

• Frame content around questions users might ask.
• Use natural language in headings and subheadings.
• Include direct answers followed by supporting context.
• Optimise for voice search by mimicking spoken queries.
• Use tools like AnswerThePublic, AlsoAsked, or Google Search Console to discover long-tail opportunities. 

3. Definition for 'GA4 Referral Tracking’

GA4 Referral Tracking is the process of using Google Analytics 4 to monitor how users arrive at your website—especially from AI platforms like ChatGPT, Copilot, Perplexity, or voice assistants. It helps measure the impact of AEO by identifying traffic sources that don’t behave like traditional search engines.

What Is GA4 Referral Tracking?

• In GA4, a referral is any traffic that comes from another website or platform (excluding search engines and direct visits).
• For AI-driven content, this includes:
• ChatGPT browser plugin referrals
• Bing Copilot citations
• Perplexity.ai links
• Voice assistant-triggered visits (via mobile browsers)

Why It Matters for AI-Driven Content

   
How to Set It Up

• Enable Referral Tracking in GA4
• Go to Admin → Data Streams → Web → Tagging Settings
• Ensure referral exclusions are properly configured
• Create Custom Reports
• Use Exploration to filter by session source or referrer
• Track traffic from domains like perplexity.ai, bing.com, chat.openai.com
• Tag AI-Cited Pages
• Add UTM parameters to links you share in AI platforms
• Example: ?utm_source=chatgpt&utm_medium=referral&utm_campaign=ai_citation
• Monitor Voice Search Traffic
• Segment by device category = mobile
• Filter for long-tail queries or FAQ page visits

4. Definition for ‘Sentiment Analysis’

Sentiment Analysis is the process of evaluating the emotional tone or attitude expressed in AI-generated content, especially when your brand, message, or website is mentioned. It helps measure how AI platforms perceive and present your content, which is crucial for reputation management and AEO.

What Is Sentiment Analysis?

It categorises mentions as:

• Positive: supportive, enthusiastic, or favourable tone
• Neutral: factual, balanced, or emotionless tone
• Negative: critical, dismissive, or unfavorable tone

In AI-driven contexts, it applies to:

• ChatGPT responses
• Copilot citations
• Perplexity summaries
• Voice assistant answers

Why It Matters for AEO

How to Measure Sentiment in AI Mentions

Use tools like:

• Superprompt.com: Tracks sentiment across multiple AI platforms
• AIclicks.io: Provides tone analysis for brand mentions in ChatGPT and Claude
• Brandwatch or Talkwalker: For broader sentiment tracking across web and social

Set up dashboards to monitor:

• Tone of AI citations
• Sentiment trends over time
• Comparison with competitors

5. Definition for ‘Prompt Mapping’

Prompt Mapping is the strategic process of identifying which user queries (or ‘prompts’) trigger AI platforms to cite, summarise, or link to your content. It’s a key metric for AEO because it reveals how well your content aligns with real-world questions asked in tools like ChatGPT, Copilot, Perplexity, and voice assistants.

What Is Prompt Mapping?

It involves tracking and analysing the prompts that lead AI platforms to reference your website, brand, or message.

These prompts are often:

• Conversational: “What’s the best way to improve digital inclusion?"
• Instructional: “How do multicultural councils use AI?”
• Comparative: “AI ethics vs human rights frameworks”

Why It Matters for AI-Driven Content

How to Track and Use Prompt Mapping

Use tools like:

• Superprompt.com: Tracks which prompts trigger citations across AI platforms
• AIclicks.io: Maps prompt-to-content relationships and sentiment
• Google Search Console: For traditional keyword-to-click mapping (still useful for AEO)

Create a prompt library:

• Document prompts that lead to citations
• Group by theme (e.g., AI ethics)