The GEO KPI Framework: Why "Rank" is Dead and "Share of Model" is the New Gold Standard

For twenty years, "Rank" was the absolute truth. You were either Position 1, Position 4, or Page 2. It was deterministic. It was stable.

Generative AI has broken this metric. LLMs are probabilistic, not deterministic. When a user asks Claude "What is the best CRM for startups?", the answer is generated on the fly. Your brand might appear in the first generation, but disappear in the second.

If you are reporting "Rankings" to your board in 2025, you are reporting on a legacy system. We need a new framework.

The Problem with Deterministic Ranking

Search Engines index lists. Answer Engines synthesize context. Because LLMs use temperature settings to introduce creativity, an "answer" is not a static object. It is a distribution of probabilities.

Tracking that you are "Rank #1" implies you are always visible. In the AI era, you are never "always" anything. You only have a probability of inclusion.

Introducing Share of Model (SoM)

Share of Model (SoM) is the percentage of times your brand appears in the response to a specific intent across a statistically significant number of generations.

This metric acknowledges the volatility of AI. It gives you a realistic view of your visibility. If your SoM is 64%, you are dominating the conversation. If it's 5%, you are effectively invisible, even if you have great SEO.

The Secondary Metric: Citation Density

Getting mentioned is step one. Getting cited is step two. Citation Density measures how often your mention is accompanied by a clickable link or a footnote reference.

• Uncited Mention: "Tool X is good for this." (Brand Awareness)
• Cited Mention: "Tool X offers feature Y [1]." (Traffic Driver)

Perplexity and SearchGPT rely heavily on Citation Density. To improve this, your content architecture needs to change from "marketing fluff" to "referenceable facts."

How to Measure SoM Today

You cannot measure this manually. You need to run automated checks against the API endpoints of major models (GPT-4o, Claude 3.5, Gemini Pro).

1. Define your "Golden Prompts": The 20 questions your buyer asks before purchasing.
2. Run 10 iterations per prompt: Do not rely on a single check.
3. Calculate the mean: This eliminates the noise of AI hallucination.