Childminding : Make Revenue Automation

Revenue Automation Architecture Overhaul A full rebuild of onboarding, retention, recovery, and churn automation with financial accuracy and lifecycle intelligence.

SaaS / Subscription Business / Revenue Operations

Automation Architect

Revenue Systems Engineer

Lifecycle & Churn Intelligence Designer

2 Weeks

Internal automation infrastructure (Make.com scenarios, Stripe webhooks, CRM, Sales, Marketing, and Support sync)

Financially accurate churn and retention metrics

Zero duplicate CRM records

Revenue recovery from trial and payment failures

Sales, Support, and Marketing fully synchronized

Self-healing automation with no silent failures

The client is a growing SaaS company operating on a subscription model. Their revenue engine relies heavily on automation across onboarding, billing, sales outreach, retention, and support. Accuracy, context, and system trust were critical for leadership decision-making.

The automation system had become context-blind and financially misleading. Trial users were counted as churn, failed payments were treated as voluntary cancellations, sales leads were leaking, and support teams were contacting cancelled users. A full logic-first rebuild was executed to restore financial truth, recover lost revenue, and align all customer-facing systems.

Restore financially accurate churn metrics

Distinguish trial dropouts from true lost customers

Separate voluntary churn from involuntary payment failures

Prevent sales lead leakage

Align Sales, Marketing, and Support lifecycle states

Recover lost revenue opportunities

Build a scalable, trustworthy automation foundation

Automation architecture redesign in Make.com

Stripe webhook parsing and lifecycle logic

CRM upsert and lifecycle state modeling

Mailchimp segmentation and recovery flows

Reply.io lead injection and API repair

Intercom lifecycle synchronization

Historical data backfill and recovery

The system treated all exits as churn, regardless of intent or payment status. Trial dropouts inflated churn metrics, failed card payments triggered goodbye emails, admin actions fired customer-facing automations, leads silently failed to enter sales sequences, and six months of historical data loss went unaddressed.

Trust automation outputs and dashboards

Stop incorrect customer communication

Recover lost revenue and leads

Reduce manual cleanup and executive intervention

Align revenue, sales, and support systems

System audit and failure mapping

Lifecycle and financial logic design

Webhook payload inspection and source detection

Scenario rebuild with logic-first routing

Error handling and recovery setup

Cross-platform lifecycle synchronization

Historical data backfill and validation

The automation stack was rebuilt around state, source, and financial reality. Every flow now validates who initiated the action, whether money ever changed hands, and what lifecycle state is commercially correct before triggering any downstream automation.

1. Ghost Customer Logic (Financial Accuracy) Trial users were incorrectly classified as churn, inflating revenue loss metrics. We implemented financial validation logic using lifetime spend to distinguish real churn from failed conversions.

Logic applied:

If Total_Spend > 0 → True Lost Customer

If Total_Spend = 0 → Trial Dropout

Result: Churn metrics became financially accurate and usable for executive decision-making.

2. Active Trial Credit Card Drop-Off Recovery Users who initiated signup but failed to enter card details were previously ignored by the system. We introduced detection logic for incomplete checkout states and routed these users into a dedicated nurturing and recovery campaign.

Result: Recovered revenue opportunities before churn ever occurred.

3. Cancelling “Purgatory” Lifecycle State A custom “Cancelling” status was created for users who selected “Cancel at period end” but were still active subscribers. These users were immediately flagged as high-intent churn risks and entered win-back sequences before subscription expiration.

Result: Retention efforts shifted from reactive to proactive.

4. Voluntary vs. Involuntary Churn Routing The system previously treated failed payments as voluntary churn. We introduced separate lifecycle paths for intent-based exits versus payment failures.

Routing logic:

Voluntary Cancellation → Win-back or Exit Flow

Payment Failed / Uncollectible → Payment Recovery Flow

Result: Failed card users no longer received goodbye messaging, improving recovery and user experience.

5. Admin vs. User Action Detection (Source Awareness) Stripe webhook payloads were inspected to determine action origin.

Logic applied:

request.id present → User/API action

request.id missing → Admin dashboard action

Admin-initiated cancellations silently updated CRM, marketing, and support systems without triggering customer-facing automation.

Result: Automation respects human intent and executive actions.

6. Reply.io Lead Injection & API Repair Critical API authentication errors were fixed, restoring lead flow into Reply.io cold outreach sequences. Previously invisible lead leakage was eliminated.

Result: Sales regained full visibility and control of the outbound pipeline.

7. Intercom Lifecycle Synchronization Lifecycle tags were synced across CRM and Intercom to reflect true customer status. Cancelled users were automatically removed from active support queues.

Result: Support teams stopped contacting churned users, improving operational trust.

8. Historical Backfill (“Time Travel Fix”) Automation failures had caused six months of lost leads. We queried historical Stripe and CRM data, identified missing records, and manually injected them into Reply.io sequences.

Result: The system didn’t just prevent future loss it repaired past revenue damage.

Fully rebuilt Make.com automation scenarios

Lifecycle and churn logic documentation

CRM upset and financial validation logic

Sales, Marketing, and Support synchronization

Historical data recovery scripts and execution

100% elimination of false churn events

Financially accurate churn and retention metrics

Recovered lost sales opportunities

Zero duplicate CRM records

Aligned Sales, Marketing, and Support systems

5–7 hours per week saved in manual cleanup

Executive trust in automation fully restored

No manual CRM cleanup required

Lifecycle states remain consistent across tools

Automation respects intent, payment status, and context

Scalable architecture supports growth without risk

Stripe Webhooks

Make.com

HubSpot CRM

Mailchimp

Reply.io

Intercom

True automation is not about moving data. It is about preserving context, financial truth, and intent across the entire customer lifecycle.