How to track Share of Model (SoM) across AI engines
Share of Model (SoM) measures what percentage of category buyer prompts recommend your brand versus named competitors across ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews. Optymia runs multi-engine simulations on a weekly cron, weighting results by conversational prompt frequency and generating board-ready SoM percentage trends.
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Why Optymia
- Live citation tracking across ChatGPT, Gemini, Perplexity, Claude, Copilot, Grok, AI Overviews.
- Astra 5-step methodology (Scan · Map · Build · Reinforce · Audit) — no guesswork.
- Automatic schema JSON-LD generation for FAQPage, Article, Product, Organization.
- Prompt-testing lab so you know what buyers actually ask before you write.
- Agency dashboards with white-label reporting and per-client fix queues.
Frequently asked
How to measure Share of Model (SoM) across generative engines?+
Share of Model (SoM) is measured by testing a benchmark set of 50–500 conversational category prompts across ChatGPT, Perplexity, Claude, Gemini, and AI Overviews, counting brand mentions versus competitors in the answers, and calculating your citation percentage out of total category mentions.
Why is Share of Model replacing traditional keyword rank tracking?+
Because over 40% of B2B software and consumer research now happens in AI conversational chats with zero traditional blue links. If an LLM doesn't recommend your brand in its synthesis, you are invisible even if you rank #1 on Google.
How does Optymia calculate Share of Model?+
Optymia automates continuous weekly query runs across 9 generative engines, weights results by buyer prompt volume and intent severity, and outputs a normalized 0–100% Share of Model score with per-competitor win/loss breakdowns.
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