Share of Model: The New B2B Metric for Measuring Success in Perplexity, Gemini, and ChatGPT

The "Zero-Click" Crisis and the Rise of Answer Engines

For the last two decades, the contract between search engines and B2B marketers was simple: we create content, Google indexes it, and users click through to our websites. That contract is breaking.

In 2025, we are witnessing the mass migration from Search Engines (which provide lists of links) to Answer Engines (which provide synthesized solutions). Platforms like Perplexity, ChatGPT Search, and Google’s AI Overviews are effectively intercepting the user journey. Instead of clicking ten blue links to compare software, a user simply asks, "What is the best GEO software for B2B SaaS that integrates with GitHub?"

The AI reads the top results, synthesizes the information, and presents a direct answer. If your brand is mentioned in that answer, you win. If you are buried in the source links but not cited in the text, you are invisible.

This shift demands a new metric. Click-Through Rate (CTR) is declining across the board as "zero-click" searches rise (some estimates suggest over 60% of searches now end without a click). The new metric that matters is Share of Model: the frequency with which your brand owns the narrative inside the AI's response.

In this guide, we will unpack exactly what Share of Model is, why it is the most critical KPI for modern SaaS growth, and how you can systematically increase it using Generative Engine Optimization (GEO) strategies.

What is Share of Model?

Share of Model (SoM) is a metric that quantifies a brand’s presence within the output of Generative AI models. It represents the likelihood of an LLM (such as GPT-4, Gemini, or Claude) citing your brand as a primary solution, example, or authority when prompted with a relevant query. It is the generative equivalent of "market share" for the AI era.

If a user asks Perplexity to "list the top 5 tools for automated SEO content generation," and your tool appears in 3 out of 5 variations of that prompt, you have a high Share of Model. If you appear in organic search results but the AI never mentions you in its summary, your Share of Model is zero.

SoM is driven by citations and semantic proximity. It is not enough to have a blog post; that post must contain the specific informational nutrients—statistics, unique definitions, and structured data—that the AI needs to construct its answer.

Why Share of Model Matters in 2025

1. The Shift from Discovery to Recommendation

Traditional SEO was about discovery: getting found. AI Search is about recommendation: getting vetted. When an LLM cites your brand, it acts as a third-party validator. Users inherently trust the synthesis of the AI, viewing it as an objective analysis of the available data. A citation in ChatGPT is often perceived as a "top ranking" endorsement.

2. The Winner-Takes-All Dynamic

In a Google SERP, being position #4 was still valuable. You could still get 5-10% of the clicks. In an AI answer, the real estate is much smaller. The AI might only list three solutions. If you are #4, you effectively do not exist in the conversation. This concentrates the value of visibility into the hands of the brands with the highest Share of Model.

3. Lower CAC, Higher Intent

Traffic coming from AI citations tends to have significantly higher intent. A user who asks detailed follow-up questions to an AI and then clicks a citation link is deep in the research phase. They aren't browsing; they are verifying. Optimizing for SoM is optimizing for bottom-of-funnel conversion.

The Mechanics of AI Citation: How to Rank in LLMs

To increase your Share of Model, you must understand how Retrieval-Augmented Generation (RAG) works. RAG is the process where an AI searches its database (or the live web) for facts before generating an answer.

To be retrieved and cited, your content must be:

1. Entity-Dense: The AI must recognize your brand as a distinct "Named Entity" associated with specific attributes (e.g., "B2B SaaS," "Content Automation," "GitHub").
2. Structurally Sound: The content must be formatted in a way that is easy for a machine to parse (Markdown, JSON-LD, clear headings).
3. Fact-Rich: LLMs crave "Information Gain"—unique stats, original quotes, and distinct frameworks that cannot be found elsewhere.

The Role of "Citation Bias"

Research into Generative Engine Optimization (GEO) suggests that LLMs have a "citation bias." They prefer sources that look authoritative. This means content that includes data tables, formal definitions, and clear "How-to" lists is more likely to be cited than vague, opinionated fluff.

How to Measure Share of Model

Measuring SoM is more complex than tracking keyword rankings, but it is possible. Here is a three-step framework for B2B teams:

Step 1: Define Your "Golden Prompts"

Identify the 20-50 questions your bottom-of-funnel prospects are asking. These aren't just keywords; they are full conversational queries.

• "Who are the competitors to Jasper for enterprise?"
• "Best markdown-first content platforms for developers."
• "How to automate structured data for SaaS blogs."

Step 2: Conduct a "Share of Chat" Audit

Run these prompts through the major Answer Engines (Perplexity, ChatGPT, Gemini, Claude). Record:

• Mention: Did the AI mention your brand?
• Position: Was it the first recommendation or the last?
• Sentiment: Was the context positive, neutral, or negative?
• Citation: Did it provide a clickable link to your site?

Step 3: Calculate Your Score

If you tested 50 prompts and appeared in 10 answers, your Share of Model for that topic cluster is 20%. Your goal is to increase this percentage month over month through targeted content updates.

Strategies to Increase Share of Model (The GEO Framework)

Increasing SoM requires a fundamental shift in how you produce content. You are no longer writing just for humans; you are writing for the machine that serves the human.

1. Optimize for "Direct Answers"

Every article should contain concise, definitional paragraphs immediately following a heading. If you are writing about "Generative Engine Optimization," the section should start with: "Generative Engine Optimization (GEO) is the process of..."

This makes it incredibly easy for the RAG system to "snip" that definition and serve it as the answer, citing you as the source.

2. Leverage Structured Data and Markdown

LLMs are code-literate. They understand Markdown and JSON-LD better than they understand visual HTML rendering. Writing content in clean Markdown (the native language of LLMs) and wrapping key entities in Schema.org markup reduces the "cognitive load" on the crawler.

• Pro Tip: Use comparison tables. LLMs love extracting data from tables to present to users. If you don't have a table comparing you to competitors, the AI might generate one using data from their site, not yours.

3. Publish High-Volume, Entity-Rich Clusters

To be seen as an authority, you need "Topical Authority." This means covering a topic from every conceivable angle. A single post isn't enough. You need a cluster of 20+ interlinked articles that define the relationships between concepts (e.g., relating "AEO" to "B2B Marketing" and "Content Automation").

This is where manual writing fails. It is difficult for a human team to produce the sheer volume of high-quality, structured content needed to dominate an entity graph. This is why teams use platforms like Steakhouse Agent. Steakhouse acts as an automated content colleague, generating comprehensive, markdown-formatted content clusters that are pre-optimized for GEO. It ensures that every piece of content is tagged, structured, and interlinked to maximize the signal strength sent to the AI models.

Comparison: Traditional SEO vs. Share of Model (GEO)

The metrics of success have changed. Here is how the old world compares to the new.

Advanced Strategies: Co-Occurrence and Knowledge Graphing

For advanced marketing teams, "Share of Model" can be manipulated by understanding Co-Occurrence. This is the frequency with which two words appear together in the training data.

If you want your brand (e.g., "Steakhouse") to be associated with a high-value term (e.g., "Enterprise GEO Platform"), you must frequently use them in close proximity across your entire digital footprint. But you must also associate your brand with other established authorities.

• Strategy: Create content that compares your solution to industry giants (e.g., "Steakhouse vs. Jasper for Developers"). By placing your brand in the same semantic neighborhood as a known entity, you "borrow" their relevance in the Knowledge Graph. When a user asks about Jasper alternatives, the AI's vector search is more likely to retrieve your brand because of the established semantic link.

Common Mistakes That Kill Share of Model

Avoid these pitfalls if you want to be cited by Perplexity and Gemini:

• Mistake 1: Gating Your Best Content. If your white papers and case studies are behind a PDF wall, the LLM cannot read them. Ungate your core knowledge. Make it crawlable text.
• Mistake 2: Using Generic "AI Writing". Paradoxically, using generic AI tools to write content hurts your SoM. If your content sounds exactly like the average of the internet (which is what base LLMs produce), you offer zero "Information Gain." You need unique insights, data, and proprietary frameworks.
• Mistake 3: Ignoring the "About" Page. Your "About" page is the primary source of truth for your brand entity. Ensure it clearly states who you are, what you do, and who you serve, using clear schema markup. If the AI doesn't know who you are, it won't cite you.

Conclusion: The Race for Generative Authority

The era of "ten blue links" is fading. We are entering the age of the synthesized answer. In this new reality, Share of Model is the only metric that accurately reflects a brand's influence. It measures not just visibility, but authority.

To win, B2B brands must evolve. They must move beyond simple keyword targeting and embrace a holistic GEO strategy—focusing on structured data, entity density, and high-volume, high-quality content production. Whether you build this capability in-house or leverage automation platforms like Steakhouse Agent to scale your specialized knowledge, the goal remains the same: become the default answer.

The brands that adapt to this metric today will define the market conversations of tomorrow. Those that don't will be left fighting for clicks that no longer exist.