Fixing trial onboarding for clinicians who weren’t ready yet.
When we started analyzing trial conversion, it appeared healthy on the surface. Around 28 percent of clinicians who started a trial ended up paying — reasonable for healthcare SaaS. But the number had stalled for months. We needed to understand the underlying causes.
Discovery & survivorship bias
// CONTEXTWe analyzed the behaviors of users who converted and found that trialers who booked a session within their first 7 days converted at over 80 percent. This seemed promising initially, but deeper analysis revealed survivorship bias. These users weren’t new clinicians getting started — they already had active practices and were testing our platform with existing clients.
This discovery led us to reconsider how we measured early value. Rather than focusing on final actions like booking appointments, we mapped the complete trial journey to identify repeatable steps that correlated with conversion before clients were even involved.
What actually moved the needle
// THREE ACTIONSAfter analyzing 90 days of onboarding data and conducting user interviews in collaboration with our data science team and marketing analytics, we identified three key patterns. Trialers who completed all three actions had significantly higher conversion rates.
-
Added practice details (name, address, timezone)
Basic information that helped them feel established, even before their first client.
-
Enabled a client intake form that included “Reason for Visit”
Gave structure to their client interactions and helped them prepare for sessions.
-
Launched a basic public-facing website
One-click publish that made them look professional to potential clients.
Rollout & results
// A/B TESTWe conducted an A/B test with ~12,000 trialers. The control group continued using the existing checklist approach, while the test group experienced the new guided onboarding flow.
- Trial-to-paid conversion 28.1 → 35.7% (+27% relative, +7.6 pp)
- Onboarding completion 53 → 86% (+33 pp)
- Time to first appointment 6.4 → 3.2 days (−50%)
- NPS in first 30 days 30 → 65 (+35 points)
- Onboarding support tickets −38% (self-serve resolution)
We measured impact using logged product events, changes in survey responses, and tagged support issues. We ran significance testing to confirm each result before reporting it. These numbers shaped pricing strategy and onboarding headcount. All metrics were pulled directly from our data stack and validated by the product and marketing data teams.
How we gathered insights
// RESEARCHBefore rebuilding onboarding, we ran structured research across both quantitative and qualitative channels. The goal was to understand not just what users did, but why they hesitated.
- Cohort-level funnel tracking using Amplitude, focused on trial day 0–7
- Continued engagement tracking through full 30-day trial period
- Drop-off event clustering to identify where users stalled (e.g. practice setup, client intake)
- Conversion rate analysis from trial to paid subscription
- Booking rates for onboarding calls after in-app setup completion
> “What’s stopping you from creating your first appointment?”
12 moderated interviews (45–60 min each) with new solo practitioners who signed up but didn’t create an appointment. Mix of therapists, counselors, and social workers, mostly early-career or launching a private practice.
Interview prompts included:
- “Walk me through what you expected when you signed up.”
- “What were you hoping to get done in the first session or two?”
- “At what point did you feel stuck or unsure what to do next?”
- “What kind of info do you need from a client before you’ll agree to meet with them?”
- “What would make this software feel ready-to-use instead of overwhelming?”
- Users needed structure without friction. Most didn’t want hand-holding, just a clear path.
- Clinicians feared liability exposure early in the intake process, especially around self-harm disclosures.
- Several admitted to “abandoning the setup and planning to come back later,” then never did.
- The ones who published a site or intake form said it helped them “feel legit” and created momentum to keep going.
These findings directly shaped the onboarding flow. We surfaced the right forms earlier, previewed what clients would see, made the experience linear without being rigid, and built subtle safeguards into the process.
The redesigned flow
// DIAGRAM— google places API integration
— automatic timezone setup
— legal disclaimers added
— specialty customization
In-flow checkpoints
Deeper impact analysis
// 30-DAY WINDOWThe changes gave new clinicians a clearer path. Within 30 days, more felt in control, understood the platform, and used it with confidence.
Time to first appointment dropped by 50%, from 6.4 days to just over 3. This helped trialers reach a moment of clarity: “This platform works.”
> 3.2 days average to first appointment
NPS among new users climbed from 30 to 65 in 90 days. We weren’t just converting more — we were creating advocates.
> +35 point NPS improvement
Impact beyond metrics
// REFLECTIONWe redesigned the onboarding experience to guide new clinicians through essential tasks while allowing them to focus on their core work. By reducing clutter and distractions, we provided just enough structure to help users get set up and recognize value quickly. This approach improved conversion rates, boosted NPS scores, and reduced support ticket volume.
Following the successful launch, I worked with over 15 product managers across the organization to share these methodologies: start with small experiments, test everything systematically, and maintain close contact with user feedback.
Ready to transform your product growth?
I work on PLG strategies that drive real conversion improvements — systematic experimentation, user-focused design, and measurement that holds up.