You see the problem
Signups are good. Trial conversions are near zero. But why?

10-minute diagnostic. Ranked hypothesis list. Experiment ready.

You have free users. You have data. You don't have time to hire a conversion analyst or build dashboards.
ConversionDX runs your usage data against 500+ known SaaS conversion failure patterns and tells you which one you're hitting—with confidence scores and a specific experiment to test.
Run your first diagnostic freeSignups are good. Trial conversions are near zero. But why?
Is it pricing? Messaging? Product-market fit? Onboarding? You pick one and run an experiment.
You optimize the wrong thing. Conversion doesn't budge. You pivot to the next guess.
Upload your data. Get a diagnosis. Run the highest-confidence experiment first.
Most likely: Messaging or PMF misalignment
Test: Segment your signups by company size or use case. Are messaging-qualified leads more likely to trial?
Most likely: Activation blocker
Test: Time-to-first-core-feature. Run an onboarding friction audit or feature discovery experiment.
Most likely: Pricing or value communication
Test: A/B test pricing tiers or run a willingness-to-pay survey with power users.
Most likely: Expectation mismatch or support gap
Test: Exit surveys or cohort-level churn analysis by feature depth.
If you're running a freemium or free-trial model with 50–500 free users and $0–5k MRR, you have the data but not the time. ConversionDX gives you the diagnosis so you can spend your time on the experiment.
Not a dashboard. A prioritized list of what's most likely blocking your conversion—with confidence scores.
Why this hypothesis is likely. What pattern in your data triggered it.
A specific test you can run today to validate or eliminate the hypothesis.
Upload data. Get results. No setup. No onboarding.
1 diagnostic/month. Test the model risk-free.
Unlimited diagnostics. Slack integration. Export findings.
API access. Team seats. Custom pattern library updates.
Run the experiment. You'll know in 1–2 weeks. If the hypothesis doesn't hold, re-diagnose. The pattern library improves with each test.
No. We need cohort-level or monthly aggregates: signups, trial starts, core feature adoption, churn rate. No PII.
No. We're diagnostic-first, not analytics-first. You keep your analytics stack. We surface the most likely conversion blocker from your data.
After each major experiment, or monthly. Most founders run 1–2 diagnostics, execute the top experiments, then re-diagnose to see what shifted.
Yes, on Pro and Enterprise plans. Reports are posted to a channel you choose.
We read every message. No spam — one focused update when we ship.