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.

Stack PostHog Chameleon Stripe
3
Cancellation flows built (Cancel, Downgrade, Delete)
7
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. PostHog tracks every interaction: cancellation_reason_selected, retention_offer_shown, retention_offer_accepted, and cancellation_confirmed — giving the team a live read on save rate by archetype from day one.
Step 6 — Post-Cancellation Win-Back Sequence
For accounts the Chameleon interception couldn’t save, a Customer.io win-back sequence was designed: 8 emails across 90 days — Day 0 (data preservation + immediate return offer), Day 3 (feature reminder), Day 7 (competitor comparison), Day 14 (workflow cost calculator), Day 30 (platform update), Day 60 (testimonial + reactivation), Day 85 (final offer), Day 89–90 (account closure notice with one-click reactivation). The Chameleon system intercepts at the point of intent; the Customer.io sequence catches what gets through.

After.

3
Distinct cancellation flows (Cancel, Downgrade, Delete)
7
Reason branches mapped to targeted retention offers
40-50%
Target save rate on cancellation attempts
$105-155k
Estimated annual MRR protected
27
Chameleon screens across 6 retention branches — real-time, at the point of intent
8
Customer.io win-back emails across 90 days for accounts the interception flow couldn’t save

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.

Delivered via

Churn Prediction Sprint

Retention

Churn Prediction Sprint

$15,000–$25,000

ML model trained on your usage + billing data — at-risk scoring live in your CRM before accounts cancel.

  • At-risk scoring live in your CRM
  • 30–60 days of lead time for CS
  • Segmented churn archetypes
  • Zero-bypass cancellation logic
Book a Scoping Call → See all sprints →

Related Reading.

Case Study ML Analytics Infrastructure: From Dirty Data to ML-Driven Expansion Modelling Blog The 3 Churn Archetypes: Why One Exit Flow Can't Save All Users
Jake McMahon
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.

What this looks like for your company

Chameleon Churn Prevention Flows.

A retention interception system built in Chameleon — triggered by PostHog behavioural signals, branching by cancellation reason, and measured from day one.

  • 3–5 churn signals identified and validated with trigger thresholds defined
  • 3 intervention flows designed and live: low-engagement nudge, feature discovery, CS escalation
  • Message copy, audience targeting, display conditions, and frequency caps configured
  • PostHog integration: flows triggered by behavioural segments
  • Post-Chameleon win-back sequence design for accounts the interception flow doesn’t save
$1,997 · 10 days
Right for you if
  • Using Chameleon (or evaluating it) for in-product messaging
  • Cancellation rate visible in your data but no systematic interception at the point of intent
  • CS team finding out about churn after the fact rather than before the decision is made
See Full Details → Start a Conversation

You find out when they cancel.

A 15-minute call is enough to know whether what we do is relevant to where you are. No pitch. Just a conversation about your specific situation.

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