# Run your first benchmark

> Check your company profile, competitors, and prompt library, then start a run and follow it live.

- Section: Getting started
- Updated: 2026-07-10
- Canonical: https://knitknot.ai/docs/run-your-first-benchmark/
- Publisher: KnitKnot, the AI Presence Management platform (https://knitknot.ai)

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A benchmark run takes your active prompt library and executes every prompt across ChatGPT, Claude, Perplexity, and Gemini, then scores each response. Before your first run, spend a few minutes checking the inputs — they determine what the benchmark measures.

## 1. Check your company profile

The **Prompts** section of the console holds your company identity: features, positioning, products, and personas, each researched from the live web with a source link. This profile is what the scoring judge uses as ground truth, so if a feature is missing or wrong here, fix it before running.

If your company has multiple products, each product gets its own profile, its own competitor set, and its own prompt library — scores are tracked per product.

## 2. Check your competitors

Your competitor set should be the vendors AI actually shortlists against you — not every company in your market. Fewer, credible competitors beat a long speculative list: every competitor you add expands the prompt library and the run.

Competitors are managed per product. Adding one triggers the same deep research your own company got, so its profile is benchmark-ready.

## 3. Review the prompt library

Prompts are the questions buyers ask AI: head-to-head comparisons ("X vs Y for mid-market compliance"), category evaluations ("best automated compliance platforms"), and feature-specific questions. KnitKnot generates them from real Google search queries with monthly volume, layered with your features and buyer personas.

The library is persistent. Archive prompts that don't fit, add your own, and star the ones that matter most — but keep the core set stable so run-over-run trends stay meaningful.

## 4. Start the run

Start a benchmark from the console. Each prompt is sent to each engine as a fresh conversation — no history, no account context — the same way a first-time buyer would ask.

You can follow progress live: each evaluation streams its status, and failed cells (an engine timing out, for example) can be retried individually without re-running everything else.

## 5. What happens during scoring

Every response is scored by an evaluation pipeline, not keyword matching:

- Each claim the AI made about you or a competitor is extracted, with the verbatim quote and the source the AI cited for it.
- Claims are verified against your researched profile — this is where factual errors and outdated information get caught.
- Head-to-head prompts get a win/loss/tie outcome based on which vendor the AI actually recommended.
- Coverage, sentiment, and positioning are scored per response.

Scoring is deterministic: the same response always produces the same score, so movement between runs reflects the AI's answers changing — not scoring noise.

When the run finishes, your report and score update automatically. Next: [read your report](/docs/read-your-report/).