Canonical GEO metrics

Understanding Surfgeo's Metrics

Understanding Surfgeo's metrics is crucial for measuring and improving your GEO performance. Each metric serves a specific purpose in your optimization strategy.

LLM Mention Rate

  • Formula: Brand Mentions in LLM Responses ÷ Total Prompts Tracked × 100

  • Example Calculation: If your brand appears in 150 responses out of 3,000 tracked prompts, your mention rate is 5.0%.

  • Why It Matters:

    • The mention rate is your fundamental visibility metric.

    • It tells you what percentage of relevant conversations include your brand.

    • A low mention rate indicates opportunity for improvement.

    • A high rate suggests strong brand presence.

    • Track this metric over time to measure the impact of your GEO efforts.

    • Industry leaders typically maintain mention rates between 8–15% for their core topics.

Share of Voice (SOV)

  • Formula: Brand Mentions ÷ Total Competitor Mentions × 100

  • Example Calculation: If your brand has 200 mentions and all competitors combined have 1,000 mentions, your SOV is 20%.

  • Why It Matters:

    • Share of Voice measures your relative dominance in the competitive landscape.

    • Unlike mention rate, which measures absolute visibility, SOV tells you how you stack up against competitors.

    • A rising SOV indicates you're gaining ground, even if overall industry mentions are declining.

    • This metric is particularly valuable for board reporting and competitive benchmarking.

Brand Rank

Brand Rank represents your position relative to competitors based on visibility metrics. The calculation considers multiple factors:

  • Primary Ranking Factor: Overall visibility percentage across all tracked prompts.

  • Tie-Breaking Rules:

  1. Higher absolute mention count takes precedence.

  2. More consistent performance across different LLM models.

  3. Historical performance trend (improving brands ranked higher).

  • Per-Model vs Aggregate Ranking:

    • Surfgeo calculates both model-specific rankings (how you perform on ChatGPT vs Claude vs Gemini).

    • And aggregate rankings across all models.

    • This dual approach helps identify model-specific optimization opportunities.

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