Billing & Dunning | SaaS Automation

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SaaS & Technology

Automated Billing, Subscription & Dunning Flows

Stripe automation engine to reduce payment failures and improve MRR reliability through smart recovery.

SaaS automation case study featuring workflow automation and integration.

+35%

Payment Recovery

14%

Churn Reduction

Hours Saved/Week

Overview

A subscription SaaS company faced high rates of failed renewals and involuntary churn. Stripe's default retry logic wasn't cutting it, and finance was manually reaching out to failed payments.

Business Context

The company was losing substantial revenue to failed payments and involuntary churn — customers who wanted to stay but whose credit cards had expired, exceeded limits, or experienced temporary holds. Finance team members were spending hours each week manually identifying failed payments, crafting individual outreach emails, and tracking resolution. The problem was growing as the subscriber base expanded, and the manual approach couldn't scale. Board members were asking pointed questions about churn rates, and the finance team couldn't provide clear answers about recovery rates or revenue at risk. The CFO recognized that involuntary churn was a solvable problem that was draining significant revenue from the business each quarter. Analysis revealed that many failed payments were recoverable with the right outreach timing and messaging, but Stripe's default retry logic alone wasn't optimized for their customer profile. ZapWizards was engaged to build an intelligent dunning automation system that would recover more revenue while eliminating manual work and providing comprehensive visibility.

How We Built It

We architected a comprehensive billing intelligence system built on the Stripe API and orchestrated through Make.com. The system monitors subscription events in real-time, immediately detecting failed payments and categorizing them by failure reason — expired card, insufficient funds, bank decline, or fraud flag. A custom retry schedule optimizes timing based on failure type and customer payment history, avoiding the aggressive retry patterns that can trigger bank blocks while ensuring persistent follow-up on recoverable failures. The AI-powered email engine using OpenAI generates personalized recovery messages that reference the customer's specific product usage and value received, dramatically outperforming generic payment failure notifications. High-value accounts at risk trigger immediate Slack alerts to customer success, enabling personal outreach for enterprise customers. The system updates HubSpot CRM with subscription status changes, ensuring sales and success teams always have current billing context. Failed payment data feeds into predictive models that identify customers likely to fail before their next billing cycle, enabling proactive card update requests. A custom Retool dashboard provides finance leadership with comprehensive visibility into MRR, churn rates, recovery rates, and revenue at risk, enabling data-driven decisions about dunning strategy optimization.

Challenges

High rate of failed renewals

No retry logic beyond Stripe's default

Manual outreach by finance team

Lost revenue due to slow follow-up

What We Delivered

Dunning automation engine using Make.com + Stripe API

Custom retry schedule

AI-personalized recovery emails

Slack alerts for high-value accounts at risk

CRM updates on subscription status

Dashboard showing MRR, churn, and recovery rate

Tech Stack

Stripe API, Make.com, HubSpot, Retool, OpenAI

Results

+35%

Payment Recovery

14%

Churn Reduction

Hours Saved/Week

Strategic Impact

The 35% improvement in payment recovery translates directly to preserved MRR that would have otherwise been lost to involuntary churn. The 14% churn reduction combined voluntary and involuntary improvements, as the AI-personalized outreach often reminded customers of value they'd forgotten and prompted them to update payment methods promptly. Ten hours per week saved by the finance team now goes to strategic financial planning rather than manual payment recovery. The automated system recovers more revenue than manual outreach ever could because it operates 24/7 with perfect consistency, never missing a failed payment or forgetting to follow up. Customer experience improved significantly — personalized, helpful payment recovery messages feel like service rather than dunning, preserving relationships even during billing friction. The dashboard visibility has enabled continuous optimization of dunning strategies based on actual recovery data rather than assumptions. Board reporting has improved dramatically as finance can now provide precise metrics on recovery rates, revenue at risk, and churn trends. The infrastructure has proven essential for growth, automatically handling the increased complexity that comes with a larger subscriber base without requiring additional headcount. The predictive capabilities are now being used to proactively reduce payment failures before they occur.