Overview
The platform uses a curated prompt library generated from your brand and category. You cannot edit prompts yet — this keeps scores comparable across accounts and over time. Each prompt is tagged with a category so you can slice evidence by intent.
Prompt categories
Prompts are grouped into five functional buckets. The mix is tuned per category at generation time so every run has balanced coverage.
- Comparison
- "X vs Y" and shortlist-style queries.
- Recommendation
- "Best tool for…" discovery queries.
- Definition
- "What is…" knowledge queries.
- Use case
- Job-to-be-done framing.
- Troubleshooting
- Post-purchase and support framing.
Prompt evidence table
Every row in the evidence table is a single prompt × model pair. Each row records the mention type, position, and the raw excerpt used by the parser. Click the excerpt to see the full response captured during the run.
Mention type definitions
The parser classifies every brand reference into one of four mention types. The classification is deterministic and runs on the captured response text only — no live LLM calls at scoring time.
- Direct
- The brand name appears in the response.
- Linked
- The brand's domain appears as a citation.
- Implicit
- A product or tagline uniquely tied to the brand appears.
- Missing
- No form of mention was detected.