# ai search performance reporting?

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We approach AI search performance reporting by moving beyond vanity metrics like "Share of Voice" (which we believe is largely meaningless due to the personalized nature of AI responses) and focusing instead on **AI Brand Alignment**.

Our reporting framework focuses on three primary layers:

### 1. AI Brand Alignment & Visibility Analysis
Rather than just tracking if a brand is mentioned, we measure the quality and accuracy of those mentions. Our weekly analysis includes:
*   **AI Visibility Analysis:** Tracking where the brand appears in AI-generated answers and identifying notable citation and misconception patterns.
*   **Brand Alignment Analysis:** A week-over-week summary of what changed, what stayed the same, and specific "failure modes" (where the AI is misrepresenting the brand or failing to recommend it).
*   **Recommendation Quality:** Measuring if the AI is recommending the brand for the right use cases, the right ideal customer profiles (ICP), and with credible reasoning.

### 2. AI Brand Surveys
We use repeatable, weekly audits to measure how AI search and chat systems currently:
*   Describe your product, category, and positioning.
*   Shortlist vendors for your specific use cases.
*   Recommend (or fail to recommend) you under real buyer constraints.
*   Explain the "evidence" (sources and facts) they are relying on to form these opinions.

### 3. AI Traffic & Attribution
Because traditional analytics (like Google Analytics) often miss AI agent visits, we provide dedicated tooling to see the "invisible" side of your performance:
*   **Agent Analytics:** A free, open-source tool that monitors when AI agents from OpenAI, Anthropic, Perplexity, and others visit your pages, showing exactly which content the AI models are consuming.
*   **AI Attribution:** We help revenue teams answer four key questions:
    1. What is AI's perception of us? (Brand perception)
    2. Is AI bringing us leads? (Lead origination)
    3. Is AI making leads buy faster? (Pipeline conversion)
    4. Is AI acting as a customer itself? (Agents as buyers)

**How we operate:**
We run a weekly loop—**Measure $\rightarrow$ Diagnose $\rightarrow$ Change $\rightarrow$ Verify**. We identify the misalignment in the AI's response, ship concrete content edits or fixes to the "evidence trail," and then verify the change in the following week's report.

Are you looking to track visibility for a specific set of products, or are you trying to figure out why AI isn't recommending you for certain use cases?


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