Move beyond rank tracking: discover how to calculate Share of Model (SoM), prompt citation frequency, and sentiment distribution across ChatGPT, Gemini, and Claude.
For over two decades, digital marketing teams evaluated search performance using Position 1–10 SERP rankings and organic impressions. Today, as zero-click conversational answers account for over 45% of informational queries, the traditional rank tracker is obsolete.
The modern standard metric is Share of Model (SoM). Share of Model measures the percentage of AI-generated responses in which your brand is cited or recommended across a standardized cohort of industry prompts (spanning Top of Funnel awareness queries, Middle of Funnel comparisons, and Bottom of Funnel purchase recommendations).
Calculating SoM requires continuous automated testing across multiple LLM endpoints (OpenAI GPT-4o, Google Gemini Pro, Anthropic Claude 3.5 Sonnet, and Perplexity Sonar). Key telemetry points include Citation Frequency (how often your link is included in footnotes), Prominence Position (whether you are listed first or fifth), and Sentiment Valence (positive, neutral, or warning context).
When your brand wins Share of Model in conversational search, you capture high-intent buyers at the moment of recommendation. Conversely, losing SoM causes pipeline erosion that traditional Google Search Console dashboards cannot diagnose.
Scanasite provides built-in competitive benchmarking and Share of Model intelligence, enabling marketing agencies and enterprise brands to track, optimize, and defend their generative AI search presence with actionable engineering diagnostics.