Empty state killed it
Before
First-login screen showed an empty dashboard.
After
ICP didn't know where to start. Sample data added. Activation +33%.
Cold start, no nudge.
Onboarding check
The check before activation drops 30%.
Paste your first three onboarding emails or describe your activation flow. 500 ICP buyers tell you where they'd drop off, where they got confused, and what they were expecting that they didn't get. In 60 seconds.
No card. No signup. Three free checks in your first minute.
How the check runs
Four steps. 60 seconds end to end.
/ 01
Paste
Your first 3 onboarding emails plus a description of the activation flow.
/ 02
Pick an audience
The ICP you're activating. SMB SaaS buyer, indie hacker, dev-tool buyer, etc.
/ 03
Run
500 ICP buyers walk through the flow as they would in real life. They name where they'd drop off.
/ 04
Read the report
Predicted drop-off points, confusion clusters, expectations that weren't met, fixes ranked.
What you get back
A real report, not a vibe check.
Verdict, sentiment distribution, verbatim quotes from 500 simulated ICP buyers, the most common objection, friction points, recommendations. One artifact you can paste into your team Slack and act on tomorrow.
Onboarding check · sample
Run #04219 · 500 buyers
Positive
58%
Neutral
18%
Negative
24%
Top objection
“I don't see a price anywhere, feels like enterprise sales.”
full report
What founders catch
Three real examples of what the check found.
Welcome email had no link
Before
Welcome email celebrated signup, no next-step CTA.
After
32% of buyers expected a 'do this first' link. Added one. Day-1 activation +19%.
Email had vibe, not direction.
Day-3 email asked for feedback too early
Before
Day 3: 'How's it going?' email.
After
Most buyers hadn't activated yet. Reframed as a useful tip + soft check-in. Reply rate +60%.
Wrong question, wrong moment.
Common questions
Things SaaS founders ask before running a check.
Is this just GPT?+
No. Every check runs through nine independent corrections: a multi-model ensemble across multiple independent frontier model families, calibration against historical ground truth, revealed-preference weighting, and distribution-shape matching. One model wrapped in a persona prompt is one model's opinion. We give you 500.
How accurate is this?+
87% median accuracy across calibrated SaaS clusters, audited monthly. Every cluster is dated, sourced, and visible on the validation page. If a cluster drifts below 80%, we pause it automatically.
What audiences are available?+
Pre-built clusters for B2B SaaS buyers (SMB and mid-market), indie hackers, dev-tool buyers, marketing-led SaaS, sales-led SaaS, PLG users, agency owners, and API-first buyers. New clusters land monthly. See the audiences page for status and accuracy.
Does it work for B2C?+
Today the calibrated SaaS clusters are the focus. The same engine powers our enterprise customers' B2C work, see the enterprise page for that. If you're a SaaS founder targeting consumers, the indie-hacker and product-led clusters are the closest fit while we calibrate B2C-specific SaaS audiences.
Test your onboarding flow free.
No card. No sales call. Three live reactions in your first minute.