1. Share cohort metrics
Paste monthly or cohort-level signups, trial starts, core feature adoption, and churn. No PII—aggregates only.
Built for founders who already have data
ConversionDX is designed for SaaS companies that:
- run freemium or free trials
- have roughly 50–500 free users
- generate about $0–5k MRR
- already track basic funnel metrics
If you are still looking for your first users, this probably is not the right tool yet.
How it works
2. Match failure patterns
We compare your metrics against recurring SaaS conversion failure patterns—activation friction, messaging mismatch, pricing friction, and expectation mismatch.
3. Get ranked hypotheses
Each hypothesis includes why it was suggested, a likelihood rating, and one experiment to run next.
Common conversion failure patterns
High signup, zero trial start
Likely cause: Messaging or product-market fit misalignment
Suggested experiment: Segment signups by company size or use case. Do qualified leads trial more often?
Trial starts, no core feature use
Likely cause: Activation blocker
Suggested experiment: Measure time-to-first-core-feature. Run an onboarding friction audit.
Feature use, no upgrade
Likely cause: Pricing or value communication
Suggested experiment: A/B test pricing tiers or run a willingness-to-pay survey with power users.
Fast churn post-trial
Likely cause: Expectation mismatch or support gap
Suggested experiment: Exit surveys or cohort-level churn analysis by feature depth.
Example diagnostic output
Illustrative sample—not generated from your data.
Activation blocker
Likelihood: High
Why: Only 12% of trial users reach a core feature within 7 days.
Suggested experiment: Reduce setup before first value.
Messaging mismatch
Likelihood: Medium
Why: Signups cluster on one landing angle, but trials start from another.
Suggested experiment: Segment signups by source and compare trial-start rates.
Value communication
Likelihood: Medium
Why: Power users adopt core features but rarely upgrade.
Suggested experiment: Test an in-app upgrade prompt tied to a measurable outcome.
If this sounds familiar…
- Plenty of signups but almost no paid conversions
- Analytics tell you what happened, not what to test next
- Every experiment feels like an educated guess
If you have said one of those recently, you are who we are building this for.
What you will receive
Ranked hypotheses
Not another dashboard. A prioritized list of the most likely reasons your free users are not converting.
Why each hypothesis was suggested
Every recommendation includes the metrics that triggered it, so you can judge whether it fits your business.
A concrete experiment
Each hypothesis includes one experiment you can run to confirm or eliminate it.
Why not just use Mixpanel or Amplitude?
Analytics answer: What happened?
ConversionDX aims to answer: What should I test next?
You keep your existing analytics. ConversionDX uses your aggregated metrics to generate ranked hypotheses and suggested experiments.
Pricing (planned)
Planned free tier
- 1 diagnostic/month
Planned Pro
- Unlimited diagnostics
- $29/month (target pricing)
FAQ
How should I use the diagnosis?
Treat it as a starting point—not absolute truth. The goal is to reduce the number of experiments you have to guess at, not replace your judgment.
What data do you need?
Monthly or cohort-level aggregates: signups, trial starts, core feature adoption rate, trial length, churn rate. No PII required.
How long will a diagnostic take?
Our target is about 10 minutes from data upload to a ranked hypothesis list. Timing may vary during the concept preview phase.
Is this a replacement for analytics?
No. You keep your analytics stack. ConversionDX uses aggregated metrics to suggest what to test next—not to replace reporting.
How will recommendations improve?
During the preview phase we will use feedback from early users to improve future recommendations.