Measuring Your Brand's AI Share of Voice
How often does your brand appear in AI-generated answers? Introducing the Lander AI sentiment score framework...
In traditional SEO, marketers had clear metrics: keyword rankings, impression data from Search Console, and click-through rates. In the Generative AI landscape, these metrics are obsolete. An LLM doesn't "rank" you on page 1 or page 2. It either includes you in its synthesized answer, or it ignores you entirely.
At Lander AI, we utilize a custom metric called "AI Share of Voice" (AISOV). Here is how you can begin tracking it for your own business.
The Baseline Audit
Begin by identifying your top 20 "intent-driven" conversational queries. Instead of short-tail keywords like "London Accountant," formulate them as questions you would ask an AI: "Who are the most reliable corporate accountants for mid-sized tech companies in London?"
Feed these queries into the top four generative engines on clear, incognito instances (to avoid personalized caching): ChatGPT-4, Perplexity AI, Google Copilot/SGE, and Claude Opus.
The Three-Tier Sentiment Score
For every generated response across the four engines, evaluate your brand's presence:
- Tier 1: Explicit Recommendation (3 points). The AI directly recommends your brand as a primary solution.
- Tier 2: Co-Citation (1 point). The AI lists you alongside several competitors in a generic list.
- Tier 3: Invisible (0 points). The AI does not mention you at all.
- Tier 4: Negative Hallucination (-3 points). The AI generates incorrect or damaging information regarding your brand.
Building the Index
By mapping this data over time, you build your AISOV dashboard. You can benchmark exactly which models you are struggling with and where your competitors dominate the dataset. This framework transitions GEO from theoretical guesswork into a precise, measurable science.