Share of Model (SoM): The New Metric for AI Search Success

TL;DR

Share of Model (SoM) is the percentage of AI-generated responses that mention your brand compared to competitors for relevant queries. If users ask ChatGPT, Perplexity, or Gemini 100 questions about your category and your brand appears in 23 responses, your Share of Model is 23%. SoM is the primary metric for measuring AI Search Visibility in 2026.

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What Is Share of Model?

Share of Model (SoM) is the percentage of relevant AI-generated responses in which a specific brand, product, or website is mentioned, cited, or recommended.

The term "Share of Model" refers to your brand's share of visibility within AI language models—the systems powering ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews.

The Formula

Share of Model = (Responses Mentioning Your Brand / Total Relevant Responses) × 100

Example:

• You track 500 queries relevant to your industry
• Your brand appears in 115 AI responses
• Your Share of Model = 115/500 = 23%

SoM vs. Share of Voice

Share of Model is the AI-age equivalent of Share of Voice.

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Why Share of Model Matters

The Shift in Buyer Behavior

Traditional search shows 10 results. Users might click 2-3.

AI search synthesizes one answer, citing 2-7 sources. If you're not cited, you're invisible.

This creates a winner-take-most dynamic:

Real-World Impact

Research from KnewSearch analyzing 10,000 B2B queries found:

• Brands with 30%+ SoM receive 4.2x more inbound inquiries from AI-researching buyers
• Companies with <5% SoM reported 47% of lost deals involved buyers who researched via AI
• Average deal value from AI-discovered leads: $127,000 in B2B SaaS

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How to Calculate Share of Model

Step 1: Define Your Query Universe

Identify the questions your target customers ask AI:

Category Queries:

• "What is [your category]?"
• "Best [your category] tools"
• "Top [your category] companies"

Problem Queries:

• "How to solve [problem you solve]?"
• "Why is [pain point] happening?"

Comparison Queries:

• "[Competitor A] vs [Competitor B]"
• "Alternatives to [market leader]"

Recommendation Queries:

• "What [solution] should I use for [use case]?"
• "Which [product type] is best for [audience]?"

Aim for 50-200 queries for statistical significance.

Step 2: Query AI Platforms

Run each query across:

• ChatGPT (GPT-4)
• Perplexity AI
• Google Gemini
• Claude
• Google AI Overviews
• Microsoft Copilot

Step 3: Document Mentions

For each response, record:

• Was your brand mentioned? (Yes/No)
• Mention type (Citation with link, Name mention, Category inclusion)
• Sentiment (Positive, Neutral, Negative)
• Position (First mentioned, Middle, Last)
• Competitors mentioned

Step 4: Calculate SoM

Overall SoM = Total Mentions / (Queries × Platforms Tested) × 100

Platform-Specific SoM:

ChatGPT SoM = ChatGPT Mentions / Total ChatGPT Queries × 100

Step 5: Track Competitor SoM

Calculate the same metrics for your top 3-5 competitors. This reveals:

• Your relative position in AI visibility
• Which competitors dominate which platforms
• Gaps and opportunities

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Share of Model Benchmarks by Industry

Based on KnewSearch data from 50,000+ queries across industries:

Key Insight: In most B2B categories, the top 3 brands capture 60-80% of total Share of Model.

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Factors That Influence Share of Model

1. Brand Recognition

AI models reflect the internet's collective knowledge. Established brands with more web presence naturally have higher SoM.

2. Content Volume & Quality

More high-quality, citable content = more training data = higher SoM.

3. Third-Party Mentions

AI weighs external validation heavily. Brands mentioned across many authoritative sources get higher SoM.

4. Recency (for Real-Time AI)

Perplexity and Google AI Overviews pull current data. Fresh content boosts SoM on these platforms.

5. Query Specificity

Generic queries favor market leaders. Specific queries ("best CRM for nonprofits") offer opportunities for niche players.

6. Platform Differences

Each AI platform has different source preferences:

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How to Increase Your Share of Model

Quick Wins (1-2 Weeks)

Optimize existing content with clear, citable statements

Add FAQ sections to key pages

Update outdated statistics to current year

Implement schema markup (Organization, Article, FAQ)

Medium-Term Strategies (1-3 Months)

Publish definitive guides on core topics

Create original research with unique data points

Build comparison pages for "[Competitor] alternative" queries

Pursue press coverage and industry mentions

Long-Term Authority Building (3-12 Months)

Establish thought leadership (speaking, podcasts, bylines)

Build high-quality backlinks from authoritative sites

Expand content coverage across all relevant queries

Create a Wikipedia presence if qualified

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Tracking Share of Model Over Time

Monthly SoM Report

Track and report these metrics monthly:

Leading Indicators

These metrics predict future SoM changes:

• New content published
• Press mentions secured
• Backlinks acquired
• Schema markup implemented

Lagging Indicators

These confirm SoM impact:

• Inbound leads mentioning AI research
• Branded search volume
• Direct traffic growth
• Sales cycle attribution

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Share of Model and Revenue Attribution

Connecting SoM to Pipeline

For B2B companies, track:

Discovery Source: Ask leads "How did you first hear about us?"

Research Behavior: "Did you use ChatGPT, Perplexity, or AI search in your research?"

AI Influence: "Did an AI recommendation influence your decision to contact us?"

The SoM-Revenue Model

AI-Influenced Revenue = Total Revenue × % Leads Using AI Research × AI Influence Factor

Example:

• Total Revenue: $10M
• Leads Using AI Research: 35%
• AI Influence Factor: 60% (AI was significant in decision)
• AI-Influenced Revenue: $10M × 35% × 60% = $2.1M

With 15% Share of Model, you're capturing roughly 15% of that AI-influenced market opportunity.

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Tools for Measuring Share of Model

Manual Tracking (Free)

• Spreadsheet with query list
• Manual testing across platforms
• Weekly/monthly tracking cadence

Pros: Free, customizable

Cons: Time-intensive, doesn't scale, inconsistent

Automated Monitoring (Recommended)

KnewSearch provides:

• Automated SoM tracking across all major AI platforms
• Competitor benchmarking
• Historical trend analysis
• Alert notifications for SoM changes
• Query recommendations

Start your free trial → knewsearch.com

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Key Takeaways

• Share of Model (SoM) = Your brand mentions / Total relevant AI responses
• SoM is the primary metric for AI Search Visibility
• 30%+ SoM correlates with 4.2x more AI-driven inbound
• Different AI platforms have different source preferences
• Track monthly to measure progress and identify opportunities
• Connect SoM to revenue attribution for ROI measurement

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Frequently Asked Questions

What is a good Share of Model?

For most B2B categories, 15-30% Share of Model indicates competitive AI visibility. Market leaders typically achieve 30-50% SoM. Below 5% means you're effectively invisible in AI search.

How often should I measure Share of Model?

Monthly measurement is recommended for most businesses. High-growth companies or those in competitive markets may benefit from weekly tracking.

Does Share of Model differ by AI platform?

Yes. Each platform (ChatGPT, Perplexity, Gemini, Claude) has different source preferences. Track platform-specific SoM to identify where you're strong and where you need improvement.

How long does it take to improve Share of Model?

Quick wins (schema, content optimization) can show results in 2-4 weeks on real-time platforms like Perplexity. Significant SoM improvements typically take 3-6 months of consistent effort.

Is Share of Model the same as Share of Voice?

No. Share of Voice measures traditional marketing visibility (ads, media mentions). Share of Model measures AI search visibility. They're complementary metrics for the AI age.