# How to Track AI Mentions: KPIs and Metrics for Generative Engine Optimization

**Tracking AI mentions is the process of measuring a brand's presence in generative responses using metrics like Share of Model (SoM) and AI-Generated Visibility Rate (AIGVR).** Unlike traditional SEO rankings, which are static, AI visibility is dynamic and conversational. Research by **Onely** indicates that legacy SEO tools often fail to capture this visibility gap, as they cannot analyze generated text. This guide outlines the essential KPIs for GEO and methodologies—from manual testing to automated platforms—to accurately measure AI performance.

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## How to Track AI Mentions

**Tracking AI mentions differs from SEO ranking checks because AI responses are dynamic and personalized.** There are three primary methods to track your brand's presence in Large Language Models (LLMs):

### 1. Manual Prompt Testing (The "Secret Shopper" Approach)

This involves manually entering your **Target Prompts** (e.g., "What is best AI marketing tools for agencies") into major engines like ChatGPT-4, Claude 3, and Perplexity Pro to see if your brand is recommended.

* **Pros:** Zero cost; provides qualitative insight into *how* the AI describes you.
* **Cons:** Extremely time-consuming; results can vary by user history (personalization); impossible to scale.

### 2. Share of Model (SoM) Analysis

**Share of Model** is the GEO equivalent of "Share of Voice." It measures the percentage of times your brand is cited as a solution for a specific category of prompts compared to your competitors.

* **Calculation:** (Total Brand Mentions / Total Category Queries Tested) × 100.
* **Context:** According to [Marketing Association NZ](https://marketing.org.nz/resource-hub/share-of-model-a-new-metric-for-marketing-strategies)'s 2024 guide, SoM is becoming a **key metric** for brand health in the age of AI.

### 3. Automated GEO Analytics Platforms

Tools like [**DECA**](https://www.decageo.ai/) or RivalSee automate the manual testing process. They run thousands of Target Prompt variations through multiple LLMs simultaneously to provide a dashboard of your "Citation Authority."

* **Advantage:** Automated tracking creates a historical record of performance, showing trend lines that manual checking misses. These platforms simulate neutral user environments to ensure data accuracy.

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## **What Are the Key Metrics for GEO Success?**

**To prove the ROI of GEO, you need to report on metrics that reflect the "Answer Engine" mechanism.**

### 1. AI-Generated Visibility Rate (AIGVR)

* **Definition:** The percentage of times your brand appears in the AI's generated answer for your Target Prompts.
* **Why it counts:** This is your "Zero-Click" visibility. If AIGVR is low, your content structure may not be [AI-Citable](https://www.decageo.ai/features).
* **Insight:** Data from [Authoritas](https://www.authoritas.com/blog/state-of-generative-search) (2025) indicates high volatility in AI answers (up to 70% change over 3 months), making frequent tracking essential.

### 2. Citation Authority Score

* **Definition:** A qualitative score (1-100) measuring the *trust* the AI places in your brand. Does it cite you as a "leading expert" or just mention you in a list?
* **Insight:** High-authority citations are increasingly correlated with higher click-through rates compared to simple mentions, as users trust the AI's "expert" recommendation.

### 3. Sentiment Analysis

* **Definition:** The emotional tone of the AI's description (Positive, Neutral, Negative).
* **Critical for B2B:** AI models can sometimes "hallucinate" negative traits. Tracking sentiment ensures you catch and correct misinformation early.

### 4. Referral Traffic from AI

* **Definition:** Traffic arriving from "referral" sources like ChatGPT, Perplexity or Google SGE (specifically from SGE snapshots).
* **Note:** This traffic often has a higher conversion rate because the user has already been "pre-sold" by the AI's recommendation.

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## **Why Does GEO Tracking Matter?**

**Tracking AI mentions is no longer optional—it is the only way to see the search market that is shifting to conversational interfaces.** By focusing on **Share of Model (SoM)** and **Citation Authority**, you move beyond the vanity metrics of traditional SEO and start measuring real influence. Start by auditing your top 10 Target Prompts today to see if your brand is the answer, or if it remains invisible.

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## FAQs

### Q1. Can I use Google Search Console to track AI mentions?

**No, GSC only tracks clicks from traditional Google Search results.** It does not currently differentiate impressions from AI Overviews (SGE) effectively, nor does it track visibility in ChatGPT or Perplexity. You need specialized GEO tools or manual tracking for these platforms.

### Q2. How often should I track my Share of Model?

**We recommend a monthly audit for general trends and a weekly check for high-priority campaigns.** AI models update their weights and indices frequently (e.g., ChatGPT's knowledge cutoff updates or RAG integration), so visibility can fluctuate faster than traditional SERPs.

### Q3. What is a "good" AI-Generated Visibility Rate (AIGVR)?

**A score above 20% for broad category terms is excellent.** For branded or specific "long-tail" Target Prompts (e.g., "How to track AI mentions with automated tools"), you should aim for 90%+ visibility.

### Q4. Why is my brand invisible in ChatGPT even though I rank #1 on Google?

**Ranking #1 does not guarantee AI citation.** LLMs prioritize content that is semantically structured for **AI readability** (clear definitions, data tables, direct answers), not just keyword density. Your content might need to be rewritten in a "Citation-Ready" format.

### Q5. Is there a free tool to track AI mentions?

**Currently, the most reliable "free" method is manual checking.** You can manually query ChatGPT and Perplexity. However, for accurate, non-personalized data at scale, professional automated platforms are required to simulate neutral user environments.

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## References

* [Onely](https://www.onely.com/blog/generative-ai-search-study/)'s research + significant disconnect between organic rankings and AI citations + meaning traditional tools fail to capture visibility
* [Authoritas](https://www.authoritas.com/blog/state-of-generative-search)' 2025 data + indicates high volatility in AI answers + making frequent tracking essential
* [Marketing Association NZ](https://marketing.org.nz/resource-hub/share-of-model-a-new-metric-for-marketing-strategies)'s 2024 guide + SoM is becoming a key metric + for brand health in the age of AI
* [ELCA](https://www.elca.ch/news/generative-engine-optimization-geo-kpis)'s GEO KPI overview + measuring success involves tracking AI mentions + moving beyond traditional SEO
* [Neville Hobson](https://nevillehobson.com/2024/07/18/share-of-model-marketing-metric/)'s 2024 article + Share of Model measures brand presence in AI datasets + vital for brand awareness
* [Seeders](https://seeders.com/blog/how-to-measure-success-in-generative-search-key-geo-kpis/)'s 2025 metric guide + AI-Generated Visibility Rate quantifies brand appearance + in zero-click environments
* [Mention](https://mention.network/learn/ai-visibility-the-metrics-that-matter-in-ai-search/)'s visibility guide + Attribution Rate tracks frequency of brand citations + indicating AI trust
* [Obility](https://www.obilityb2b.com/blog/geo-resources/geo-kpis-to-measure-success/)'s B2B metrics + Conversational Engagement Rate measures user interaction + with AI-generated content
* [Hallam](https://hallam.agency/blog/share-of-model-a-key-metric-for-ai-powered-search/)'s 2024 strategic insight + Share of Model quantifies brand representation + compared to competitors in LLMs
* [RivalSee](https://www.rivalsee.com/blog/how-to-track-ai-mentions)'s tracking methodology + Content Gap Analysis identifies competitor mentions + revealing optimization opportunities
