AI Answer
Best CRM for a growing sales team?
AI recommends
Northstar CRMPipedeckClearloop
You: not mentioned
See who AI names instead
We run the buying-intent prompts buyers ask and show which rivals AI recommends over you.
The measurement, written down
Most AI visibility scores are a number with no stated method. Here is ours: what we ask, how often, how the uncertainty is calculated, and what we do when an engine does not answer.
See it. Earn it. Prove it.
AI is where buyers decide, so we show who it names instead of you, earn you into the sources it cites, and prove the lift.
Run a free checkGap Map
g2.comEarned
reddit.comGap
capterra.comGap
trustradius.comGap
Earn into the sources AI cites
We map the sources AI cites in your category, then earn you into the ones you're missing.
Your Score
Recommendation score
38/100
Prove the lift
We re-scan after each change, so every gain in your Recommendation Score is dated proof.
The questions we actually ask
The same questions in the same order, every scan. That's what makes a before and after mean something.
Plus “alternatives to” prompts for your two closest rivals, once we know who they are.
One scan is a snapshot. The trend is the proof.
These engines drift on their own. We re-scan over time so you can tell a real move from noise.
Nothing moves unseen
Your score, your rivals, and the sources AI cites, re-scanned across every engine on a schedule.
Monitoring
0
AI engines watched
0
Questions asked
0
Rivals ranked
Weekly
Auto re-scan
What moved this week
Every re-scan logs the change, so you can see exactly what moved and what earned it.
Your visibility recap
Week of Jul 13
Recommendation score+6
Sources earned+1 (g2.com)
Rankto #4
Questions a sceptic should ask
- Why is the prompt basket fixed?
- Because a basket that changes between scans measures two things at once: the engines, and our own edits. A fixed set of questions means a change in the score is a change in the answers, not a change in what we asked. It also means two customers in the same category are asked the same question, so the numbers are comparable.
- What is the confidence band?
- Asking an engine the same question five times does not give the same answer five times. The band is the 95% confidence interval on that sampling: half-width 1.96 times the standard deviation over the square root of the number of runs. A score of 40 with a band of plus or minus 8 means the honest reading is somewhere between 32 and 48.
- Why do you not alert on every change?
- Because most changes are noise. An alert fires when a scan-to-scan move is larger than the drift that domain's own history shows is normal, which needs at least five scans to establish. Before that we use a deliberately wide provisional band rather than guessing.
- What happens when an engine fails?
- It is reported as degraded and excluded from the score rather than counted as a zero. An engine that did not answer is missing data, not evidence you are unmentioned, and scoring it as absence would show a drop that never happened.
- Do you use an aggregator to reach the engines?
- No. Each engine is called through its own API with search grounding explicitly asserted, and a call that cannot confirm grounding fails rather than returning an ungrounded answer. Routing through an aggregator would silently break that, because the grounding setting is not something an aggregator can guarantee on our behalf.