Dashboard & KPIs
Understand the metrics and visualizations that make up your BuzzView Brand Overview dashboard.
Overview
Each project has a dedicated dashboard that gives you a complete picture of how your brand appears in AI search. The dashboard is organized around five core KPIs — split across two layers: Reach (are you being mentioned and cited?) and Quality (how prominently and positively?), plus a Competition lens via Share of Voice.
Every metric is filterable by AI platform, prompt tag, competitor, and date range — so you can slice the data to answer the specific question you're investigating.
The Five Core KPIs
The Brand Overview dashboard surfaces five KPIs. Each measures a distinct dimension of your AI presence. For full formulas, examples, and score interpretation, see the Brand Performance KPIs reference.
| KPI | What it measures | Range |
|---|---|---|
| Visibility | % of AI responses that mention your brand by name across all tracked prompts and LLMs | 0–100% |
| URL in Sources | % of AI responses where your website/domain was cited as a source | 0–100% |
| Average Position | Average rank of your domain in AI source lists — lower is better, 1.0 is best | 1.0 = best |
| Share of Voice | Your brand's % of all brand mentions vs. every brand mentioned (incl. competitors) | 0–100% |
| Sentiment | Weighted score (Positive=100, Neutral=50, Negative=0) of how LLMs talk about your brand | 0–100 |
Platform Breakdown
Per-Platform Metrics
The platform breakdown panel shows your KPIs split by AI platform (ChatGPT, Google AI Mode, Perplexity, etc.), so you can see where you perform strongest and where gaps exist. A brand might have strong Visibility on ChatGPT but be largely absent from Google AI Mode.
Use platform filters to isolate the view to a single platform and dig into prompt-level results for that channel specifically.
Prompt-Level Drilldown
Click any prompt row to see the exact AI-generated response for that query across each platform. For every result you can inspect which brands were mentioned, what sources were cited, the sentiment classification, and the full response text.
This is especially useful for understanding why certain prompts return low Visibility or poor Average Position — you can read the AI response verbatim and see which competitors are being recommended instead.
Time Comparison
Tracking Progress Over Time
If you've run multiple analyses on the same project, use the date selector to compare performance across runs. This lets you track whether your Visibility, Share of Voice, and Sentiment are improving over time, and correlate changes with marketing activities.
Run analyses on a regular cadence — weekly or monthly — to build a meaningful trend dataset.
