Case Study — HIPAA-Compliant Healthcare Forms SaaS

3 churn archetypes. 3 cancellation flows. Accounts saved at the moment of intent — not after.

How a healthcare forms platform stopped finding out about churn after the fact — by building 3 archetype-specific cancellation flows that intercept intent before accounts leave.

Cancellation flows built (Cancel, Downgrade, Delete)

Reason branches mapped to targeted retention offers

40-50%

Save rate target on cancellation attempts

$105-155k

Estimated annual MRR protected

Before.

The platform had a single cancellation path. Every type of churning account — whether they had a pricing objection, a missing feature, or simply never activated — hit the same exit flow. Intent was invisible until after the account was gone.

Every lost account was a surprise. Without visibility into the "why" behind churn, the team couldn't offer the right intervention at the right time.

The Situation

Single-path cancellation flow serving all user types
Zero visibility into churn reasons until after account loss
Price objectors and feature-gap churners treated with the same exit experience
No mechanism to intercept cancellation intent in real-time

What we did.

Identified churn archetypes and built targeted interception flows.

Step 1 — Churn Archetype Identification

Categorised churning accounts into 3 archetypes (Price Objection, Engagement Gap, Feature Need) from PostHog behavioural data and exit survey signals.

Step 2 — Signal Mapping

Defined the behavioural triggers that identify each archetype in real time, including usage thresholds and billing interval logic.

Step 3 — Flow Design per Archetype

Built 3 distinct Chameleon cancellation flows: price objectors get an offer, feature-gap churners get a roadmap touchpoint, low-engagement users get a re-engagement sequence.

Step 4 — Dev Specification

Drafted full technical spec for Chameleon implementation including 7 branches for the core cancel flow, event tracking bridge, and Stripe webhook logic.

Step 5 — Phased Build & Rollout

Established a multi-branch retention system in Chameleon, followed by a 20-day build and soft launch (10% → 100%) to monitor save rates.

After.

Distinct cancellation flows (Cancel, Downgrade, Delete)

Reason branches mapped to targeted retention offers

40-50%

Target save rate on cancellation attempts

$105-155k

Estimated annual MRR protected

Real-time

Signal triggers identifying churn intent early

Total screens across 6 retention branches

The Installed System.

Archetype-Specific Exit Paths

The system identifies why a user is leaving (Price vs. Feature vs. Engagement) and triggers a logic-specific save offer before they reach the Stripe cancellation webhook.

PostHog-Chameleon Bridge

A verified event taxonomy that feeds real-time usage signals into the exit flow, ensuring offers are grounded in actual user behavior, not guesses.

Revenue Protection Reporting

Churn is no longer one number; the team reads "Protected MRR" by archetype, allowing them to see exactly which product gaps are costing the most revenue.

Jake McMahon

ProductQuant

10 years building growth systems for B2B SaaS companies at $1M–$50M ARR. BSc Behavioural Psychology, MSc Data Science. This engagement required architecting a multi-branch retention system in Chameleon that synthesized PostHog behavioral data with real-time billing triggers to intercept churn at the point of intent.

You find out when they cancel.

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