How to Analyze and Benchmark Competitor GEO
How to Analyze and Benchmark Competitor GEO Strategies
Competitor analysis in Generative Engine Optimization (GEO) requires shifting from tracking keyword rankings to measuring "Share of Model" (SoM) and entity authority. Unlike traditional SEO, where success is defined by a position on a list, GEO success is defined by being the answer or a cited reference in AI-generated responses.
To benchmark effectively, you must audit how often competitors appear in AI answers (Frequency), how they are portrayed (Sentiment), and which authoritative sources are fueling their visibility (Citation Ecosystem). This shift turns competitor analysis from a linear ranking game into a multi-dimensional "brand footprint" audit within Large Language Models (LLMs).
Measuring "Share of Model" (SoM)
Share of Model (SoM) is the percentage of times a brand is mentioned in AI-generated responses for category-relevant prompts. It is the GEO equivalent of "Market Share" or "Share of Search."
To calculate SoM, you cannot rely on standard rank trackers. You must perform a "Prompt Audit" across major engines (ChatGPT, Perplexity, Gemini, Claude).
The Manual Prompt Audit Protocol
Define Query Categories:
Discovery Prompts: "What are the best CRM tools for startups?"
Comparison Prompts: "Compare HubSpot vs. Salesforce for small teams."
brand-Specific Prompts: "What are the pros and cons of [Competitor Brand]?"
Execute & Regenerate:
Run each prompt 5–10 times per engine (to account for AI variability).
Metric: If Competitor X appears in 7 out of 10 responses, their SoM is 70%.
Score the Visibility:
Primary Recommendation: The AI suggests them as the #1 choice.
List Inclusion: They appear in a bulleted list.
Citation Only: They are linked in the footnotes but not mentioned in the text.
Reverse-Engineering the "Citation Ecosystem"
AI models do not "know" facts; they retrieve them from authoritative sources. If a competitor dominates the AI answers, it is because they dominate the sources the AI trusts.
How to Map Competitor Sources
Instead of analyzing backlinks, analyze "Corroborative Sources."
Use Citation-Heavy Engines: Use Perplexity.ai or Bing Chat (Copilot).
Ask for Sources Explicitly: Prompt the AI: "Who are the top competitors to [Our Brand], and what sources are you using to evaluate them?"
Analyze the Footnotes:
Are they being cited from Tier 1 media (Forbes, TechCrunch)?
Are they cited from user review sites (G2, Reddit, Capterra)?
Are they cited from their own documentation (indicating strong technical SEO)?
Strategic Insight: If a competitor is consistently cited via a specific review site or industry report, your GEO strategy must pivot to securing coverage in that specific "Seed Source."
Benchmarking Entity Strength and Sentiment
Entity Strength determines whether an AI understands what a competitor is, while Sentiment determines how it describes them.
The "Who is..." Test
Ask the AI: "Who is [Competitor Name] and what are they best known for?"
High Entity Strength: The AI provides a detailed, accurate paragraph with specific features and use cases.
Low Entity Strength: The AI hallucinates, gives vague descriptions, or says "I don't have enough information."
Sentiment Analysis
Analyze the adjectives used in competitor descriptions.
Positive Bias: "Reliable," "Industry-leading," "Robust."
Negative/Neutral Bias: "Expensive," "Complex," "Legacy."
Benchmarking Table Example:
Share of Model (SoM)
20%
60%
40%
Primary Citation Source
Blog
G2 Crowd
Wikipedia
Entity Sentiment
Neutral
Positive
Mixed
Key Adjectives
Affordable
Powerful, Enterprise
Outdated
Conclusion
Effective GEO benchmarking requires auditing the "Black Box" of AI output rather than the "Glass Box" of search rankings. By measuring Share of Model, mapping citation ecosystems, and analyzing entity sentiment, brands can identify exactly why a competitor is winning the AI conversation and which "Seed Sources" must be targeted to reclaim visibility.
FAQs
What is the difference between Share of Search and Share of Model?
Share of Search measures query volume (how many people search for a brand), while Share of Model (SoM) measures output frequency (how often an AI mentions a brand in answers). SoM is a qualitative metric of AI visibility.
Can I automate GEO competitor analysis?
Yes, emerging tools like SE Ranking (AI Overviews tracking), Profound, and Otterly.AI are beginning to offer automated tracking for AI mentions and citations, though manual verification is still recommended for sentiment analysis.
Why does my competitor appear in ChatGPT but not Perplexity?
This is due to Source Bias. ChatGPT (depending on the version) relies heavily on its training data and Bing search, while Perplexity prioritizes real-time web retrieval. Your competitor likely has strong "Knowledge Graph" presence (training data) but weaker active news coverage (real-time retrieval).
How often should I benchmark GEO performance?
Due to the rapid update cycles of LLMs, a monthly audit is recommended. However, for highly volatile industries (e.g., tech, finance), bi-weekly checks on "Discovery Prompts" can provide early warning of shifts in AI preference.
What if a competitor has negative sentiment in AI answers?
If a competitor has negative sentiment, it is an opportunity to position your brand as the solution to their specific weakness. Create content that explicitly contrasts your strength against their AI-identified weakness (e.g., "Easier to use than [Competitor]").
References
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