Share of Model vs. Share of Voice: The New AI Search Metric
Your brand could be invisible to AI. While traditional marketing measures Share of Voice (SoV)—your slice of market conversations—AI search demands a new metric: Share of Model (SoM).
SoM measures the probability that ChatGPT, Perplexity, or Claude will cite your brand when answering user questions. According to Hallam Agency, it quantifies AI understanding and recommendation likelihood, making it the core KPI for Generative Engine Optimization (GEO).
Why Share of Voice Fails in AI Search
Traditional Share of Voice calculates your brand's visibility using a simple formula: (Your brand metrics ÷ Total market metrics) × 100. This works for PPC ad impressions and social media mentions, but breaks down in AI search environments. Riff Analytics highlights three critical limitations:
1. Rankings don't exist anymore
AI delivers one unified answer—not 10 blue links. There's no "first page" to rank on, so impression share becomes meaningless.
2. Context matters more than mentions
SoV only tracks whether your brand was mentioned. AI search rewards brands cited as trusted solutions, not just name-dropped. Being called "the best option" differs vastly from appearing in a generic list.
3. Opaque training data
Unlike Google's crawlers, AI model training (inference) operates as a black box. You can't reverse-engineer what data influenced the response.
Bottom line: Measuring SERP pixel share tells you nothing about whether AI trusts and recommends your brand.
What Is Share of Model and How Do You Measure It?
Share of Model tracks how frequently AI models cite your brand when answering relevant queries. Search Engine Land calls it "market share for the AI era."
The Formula
SoM = (Brand mentions ÷ Total generations) × 100
How to Calculate SoM: 4-Step Process
Step 1: Select Golden Prompts
Identify 20-30 high-intent questions your buyers ask during their journey. Focus on informational queries like "recommend enterprise CRM software" or "best marketing automation tools."
Step 2: Run Repeated Tests
Input each prompt into the same AI model at least 10 times. Start a new chat each time to eliminate context carryover. Reddit's SaaS community emphasizes this step to ensure statistical validity.
Step 3: Count Mentions
Track whether your brand appeared in the response. Distinguish between being listed generically versus being recommended as a top solution.
Step 4: Calculate the Ratio
If your brand appeared in 8 out of 10 responses, your SoM for that prompt is 80%.
SoV vs. SoM: Key Differences
Target Platform
Google, social media
ChatGPT, Claude, Gemini
What It Measures
Impressions, clicks, mentions
Citation probability, recommendation frequency
Goal
Visibility
Trust and authority
Optimization Focus
Keywords, backlinks, meta tags
Entity recognition, structured data, E-E-A-T
Strategic Shift: From Rankings to Probability
Adopting SoM transforms your strategy from "rank higher" to "get recommended more often." Ayzenberg emphasizes that brands must become authoritative sources in AI training datasets (corpus).
This requires more than keyword stuffing. You need AI-quotable sentences—clear, factual statements that models can extract and cite. Your brand's definition, features, and benefits must exist as verifiable facts across authoritative sources like news sites, Wikipedia, and official documentation.
Share of Model is your report card for how well your brand has become "digital common sense" in AI ecosystems.
Conclusion
In AI search, winning means being the brand AI trusts and cites most—not ranking first on a SERP. Share of Model quantifies this new reality by measuring citation probability. As AI reshapes search behavior, marketers must shift from chasing impressions to ensuring AI models learn, recognize, and recommend their brands.
Ready to measure your SoM? Start by identifying the questions your buyers ask AI, then audit whether your brand appears in the answers.
FAQs
Does SoM differ across AI models?
Yes. ChatGPT, Claude, and Gemini use different training data and algorithms, producing different SoM scores. Measure each platform your target audience uses.
How do I improve my SoM?
Deploy a GEO (Generative Engine Optimization) strategy. Publish your brand information on authoritative sources like Wikipedia and trusted news sites. Structure your website content for AI parsing—use Q&A formats and schema markup.
Are traditional SEO metrics obsolete?
No. Organic search remains important. As AI search grows, you need a hybrid approach tracking both SoV (traditional) and SoM (AI-native) metrics.
How do I choose Golden Prompts?
Focus on problem-solving questions over brand searches. Effective prompts include "best project management tool" or "compare marketing automation software"—queries where buyers compare solutions.
Can I automate SoM measurement?
Early-stage tools exist, but manual sampling remains most accurate. Run periodic tests on key prompts using scripts or manual checks to track changes over time.
References
Share of Model: A Key Metric for AI-Powered Search | Hallam Agency
Share of Voice Calculation | Riff Analytics
Competitive Audits & AI SERP Optimization | Search Engine Land
I stopped tracking rankings for AI Search. It's a probability game now. | Reddit r/SaaS
The Evolution of Search and the Importance of Share of Model | Ayzenberg
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