“AI visibility” is a new and crowded label, and the tools wearing it vary wildly — from simple mention counters to full measurement platforms. If you’re evaluating options (including Cypress), here’s a vendor-neutral checklist to judge them by, and how we think about each.
The eight-point checklist
1. Multi-model coverage
Buyers don’t all use the same assistant. A tool that only checks one model gives you a partial, possibly misleading picture. Look for: coverage across the major assistants — ChatGPT, Claude, Gemini, Perplexity — measured separately so you can see where you’re strong and where you’re not.
2. Run-variance handling
AI answers change run to run. A tool that checks each prompt once is reporting noise. Look for: repeated runs per prompt and an appearance rate, not a single yes/no.
3. Recommendation scoring, not mention counting
Being named at the bottom of a list with a caveat is not a win. Look for: a score that reflects position, endorsement strength, sentiment, and context — not just a tally. (This is what Cypress calls the Recommendation Score.)
4. Competitor share of voice
Visibility is relative. Look for: the ability to track your appearance and strength alongside named competitors, per question, so you can see who’s winning the category.
5. Prompt / category coverage
Branded prompts (“is Acme good?”) flatter you; category prompts (“best tools for X”) find new buyers. Look for: a real library of buyer-intent prompts and a coverage metric across them — not just the handful where you already win.
6. Source attribution
A score with no explanation isn’t actionable. Look for: insight into the sources behind a recommendation, so the output is a to-do list (where to earn coverage) rather than just a number.
7. Trend tracking over time
Consensus shifts; a one-day snapshot can’t show momentum. Look for: historical tracking so you can tell whether your work is moving the needle.
8. Honest data handling
You’re sending prompts to third-party models. Look for: clarity on how data and any API keys are handled. Cypress, for example, is bring-your-own-key (BYOK) — you use your own LLM API keys, so usage stays under your control.
How to use the checklist
| Capability | Why it matters | Red flag |
|---|---|---|
| Multi-model | Buyers use different assistants | Single-model only |
| Run variance | Answers fluctuate | One check per prompt |
| Recommendation score | Mentions ≠ endorsements | Mention count only |
| Share of voice | Visibility is relative | No competitor view |
| Coverage | Find new demand | Only branded prompts |
| Source attribution | Makes it actionable | A number with no “why” |
| Trend tracking | Proves progress | Snapshots only |
| Data handling | Trust and control | Vague on keys/data |
Where Cypress lands
Cypress was designed against exactly this list: multi-model benchmarking across the major assistants, repeated runs with appearance rates, a Recommendation Score that weighs position and endorsement, competitor share of voice, a buyer-prompt library with coverage analysis, source intelligence, trend tracking over time, and a BYOK model for data control.
We’d rather you use the checklist than take our word for it. Whatever tool you choose, hold it to all eight — a mention counter dressed up as “AI visibility” will only clear two or three.