Share of LLM is the percentage of times your company appears in AI-generated responses compared to competitors when prospects research your category. Think of it as share of voice, but measured across large language model outputs instead of traditional search results. When a CFO asks ChatGPT “What are the best ERP systems for manufacturing companies?” your Share of LLM is how often you’re mentioned versus SAP, Oracle, or NetSuite across that query and similar ones.
How is Share of LLM measured in practice?
B2B companies build a library of 50-100 relevant buyer queries, then systematically test them across multiple LLMs. A cybersecurity vendor might query “enterprise firewall solutions,” “network security for remote teams,” or “best practices for zero trust architecture.” They track mentions across ChatGPT, Claude, Gemini, and Perplexity, counting both direct recommendations and contextual mentions.
The calculation is straightforward: your mentions divided by total category mentions, multiplied by 100. If Palo Alto Networks appears in 40% of security-related responses while Fortinet appears in 25%, Palo Alto has higher Share of LLM. Dedicated tracking tools now automate this, though most revenue teams still run manual audits quarterly. For a full walkthrough of how to build and run this process, see How to Measure Share of LLM.
Why does Share of LLM matter for B2B revenue leaders?
Your prospects increasingly start vendor research with AI. If you’re invisible in LLM responses, you’re missing early-stage consideration entirely. Unlike traditional SEO, where you might rank on page two, LLMs typically surface three to five vendors maximum. You’re either in the consideration set or you’re not. Each time you appear, that’s an LLM citation — and the frequency of those citations across relevant buyer queries is exactly what Share of LLM tracks. Where you appear within those responses is measured by LLM Position.
High Share of LLM correlates with pipeline quality. Companies that appear consistently in AI Discovery scenarios report shorter sales cycles because prospects arrive at demos already familiar with their positioning. Low Share of LLM means your sales team fights uphill battles against vendors who shaped initial buyer assumptions.
Share of LLM becomes your new competitive intelligence dashboard, revealing not just who dominates AI-mediated research, but which messaging frameworks actually influence buyer consideration. When you identify gaps — queries where competitors appear and you don’t — the AEO Trifecta helps diagnose whether the gap is a relevance, authority, or extractability problem.
Share of LLM is also a direct output of a well-built signal-based revenue system. Playbooks structured around the exact moments your buyers experience — a merger, a reorganization, a post-event debrief — answer the precise queries AI systems surface when those signals fire. Building Share of LLM and building signal-based outbound assets are the same motion done once. See the Signal-Based Revenue Systems framework on A6 Group.
Share of LLM is the percentage of times your company appears in AI-generated responses compared to competitors when prospects research your category. It is the AI-era equivalent of share of voice, measured across LLM outputs rather than traditional media channels.
Build a library of 50-100 relevant buyer queries and test them systematically across multiple LLMs. Count how often your company is mentioned versus competitors. Divide your mentions by total category mentions and multiply by 100. Track this monthly to identify trends over time.
LLMs typically surface three to five vendors maximum per query. If you are not in that set, you miss early-stage consideration entirely. High Share of LLM correlates with pipeline quality because prospects arrive at sales conversations already familiar with your positioning, shortening sales cycles.
Share of Voice measures brand presence in human-distributed media: press coverage, social mentions, advertising reach. Share of LLM measures presence in AI-generated responses where buyers conduct private vendor research. Share of Voice is a lagging brand awareness indicator. Share of LLM is a leading pipeline influence indicator.
Share of LLM measures citation frequency — how often you appear across relevant queries. LLM Position measures citation prominence — where you appear when you do show up. Both metrics matter: high Share of LLM with consistently late position still means weak buyer influence during the research phase.