About 100 Questions

A clearer way to measure whether AI finds your brand.

100 Questions turns a vague concern—“do AI systems recommend us?”—into a reviewable benchmark with frozen questions, web-grounded answers, source evidence, and explicit limits.

Why it exists

AI visibility should be inspectable, not mystical.

AI answer systems can mention a brand, omit it, cite its website, or favor a competitor. A single unexplained score cannot show which of those events occurred or whether the underlying provider calls were usable.

The benchmark keeps visibility, prominence, selected-competitor share of voice, claimed-domain citations, and provider coverage separate. Reports link those measures back to the buyer questions, answers, and sources that produced them.

Measurement principles

Trust comes from showing the work.

These principles shape the product, the public methodology, and the way every result is described.

Evidence before conclusions

Reports retain normalized answers and source URLs so metrics and recommendations can be reviewed against the underlying evidence.

Comparable tests

Each provider receives the same frozen question set. Failed or ungrounded answers remain visible in coverage instead of silently changing a score.

Limits in plain sight

A benchmark is a time-stamped directional snapshot, not proof of causation, factual accuracy, or parity with consumer chat products.

Private by default

Runs belong to the authenticated account owner. The default answer-retention window is 30 days, and reports are not public profile pages.

What it is—and is not

Directional evidence for better decisions.

The benchmark is
A frozen, source-backed comparison across four model providers.
The benchmark is not
A guarantee of future mentions or a ranking factor sold as certainty.
Reports include
Coverage, citations, competitor evidence, retained answers, and prioritized actions.
Reports do not claim
Statistical representativeness, model causation, or consumer-chat parity.

Verify the details

Read the definitions before trusting the score.

The methodology documents question construction, grounding eligibility, denominators, coverage rules, retention, and known limitations.

Open the methodology