STEP 01
Payment event ingestion
Receive failed-payment, overdue-invoice, or billing-status events from Stripe, Chargebee, Recurly, QuickBooks, Xero, or another billing system.
Revenue Operations
Smart Dunning & Payment Recovery Automation
Profitec AI builds payment recovery systems that detect failed payments, segment overdue accounts, personalize follow-up, and help teams recover revenue without relying on manual chasing.
Smart dunning is payment recovery automation — also called dunning automation — that detects failed payments and overdue invoices, classifies the decline type, scores recovery probability, and runs personalized follow-up so revenue is not lost to manual chasing. Profitec AI builds dunning automation on Stripe, Chargebee, Recurly, QuickBooks, or Xero — separating soft declines from hard declines, escalating high-value accounts to a human, and writing status back to CRM and billing. Unlike basic dunning, which sends one fixed retry sequence to everyone, smart dunning adapts timing, channel, and message to each account, with human approval on sensitive cases.
Recovery control centerrecovering
Invoice #4821 · $480
FailedStripe event · 4m ago
Classified
Soft declineInsufficient fundsRetryable
Recovery score72%
Retry in 36h · email + SMSscheduled
Reminder drafted · tone-checked · AM approval
Recovered MTD: $12.4kRate 63% ✓
Where the workflow breaks
Failed payments become lost revenue when recovery is manual
01
Failed payments are noticed late.
02
Teams use the same reminder sequence for every customer.
03
Soft declines and hard declines are treated the same.
04
High-value accounts are not escalated fast enough.
05
Billing, CRM, email, and account ownership are disconnected.
06
Teams keep retrying dead cards and wasting operational effort.
What Profitec builds
What the smart dunning system does
A recovery control center on top of your billing system. It detects failures, classifies and scores them, runs the right sequence per account, and keeps tone, retries, and escalation under explicit control.
Revenue Recovery Control Centeroperating
Smart Dunning Core
orchestrating
Detect
01- Failed payment events
- Overdue invoices
- Soft vs hard decline codes
Score
02- Recovery probability
- Customer value
- Retry timing
- Escalation priority
Orchestrate
03- Personalized reminders
- Billing status updates
- CRM owner tasks
- Human escalation
Measure
04- Recovered revenue
- Recovery rate
- Involuntary churn
- Manual collection hours
Interactive
Payment Recovery Impact Calculator
Model how much revenue a business could recover by improving failed-payment and overdue-invoice workflows, with conservative, practical, and aggressive sensitivity ranges.
Payment Recovery Impact Calculator
Revenue at risk / month
$16,200
≈ 13.5% of monthly revenue.
Baseline recovery
$7,290
At 45% recovery today.
Recovery after automation
$10,206
At 63% recovery.
Annualized upside
$34,992
Retained value ≈ $32,659 incl. LTV.
Payback window
~3.8 mo
Est. build $14,000.
Inputs
Before vs after
MetricBeforeAfter
Recovery rate45%63%
Monthly recovered$7,290$10,206
Decline handlingOne sequence for allSoft vs hard · scored
Manual collection40 h/mo~10 h/mo
Time to recovery5–7 days1–2 days
High-value accountsSame flowEscalated to a human
Sensitivity
Conservative
$17,496
+9 pp lift
Practical
$34,992
+18 pp lift
Aggressive
$55,987
+29 pp lift
Annualized upside across recovery-lift scenarios. Guardrails on complaints, refunds, and chargebacks apply in every scenario.
Directional model. Actual recovery depends on payment provider, decline mix, customer base, message cadence, and retry rules.
Pipeline
How the smart dunning pipeline works
Input
Processing
AI / logic
Human control
Output
Measurement
STEP 02
Decline classification
Classify the event: soft decline, hard decline, expired card, insufficient funds, issuer unavailable, suspected fraud, overdue invoice, or manual payment required.
STEP 03
Account enrichment
Pull CRM and account context: customer value, invoice amount, subscription age, payment history, prior attempts, account owner, support issues, renewal date.
STEP 04
Recovery scoring
An optional ML/rules layer estimates recovery probability, best retry timing, escalation need, communication channel, and customer-value priority.
STEP 05
Sequence selection
Choose the path: automatic retry, email or SMS reminder, account-manager task, finance review, stop-retry / update-card request, or human escalation for high-value accounts.
STEP 06
Personalized message
Generate tone-controlled reminders — no aggressive language, clear payment link, account-specific context, distinct copy for invoice vs subscription, human approval for sensitive cases.
STEP 07
CRM & billing update
Write status back to CRM, the billing platform, the account-owner task, the dashboard, and the reporting system.
STEP 08
Monitoring
Track recovery rate, recovered revenue, failed retries, complaint rate, time to recovery, and churn after recovery.
STEP 09
Experimentation
Optional A/B test: baseline dunning vs smart recovery, primary metric recovered revenue, guardrails on complaints, refunds, chargebacks, and opt-outs.
Integrations
Built around the tools you already run.
Billing
StripeChargebeeRecurlyPaddle
Accounting
QuickBooksXeroNetSuite
CRM
HubSpotSalesforce
Communication
EmailSMSSlack
Automation
n8nMakeWebhooks
AI
Recovery scoringMessage generationLLMs
Tooling is illustrative. The automation is designed around the systems you already use, connected through APIs and orchestration layers such as n8n and Make.
What improves
Metrics we measure against a baseline.
Recovered revenue
/01Revenue retained from failed payments and overdue invoices.
Payment recovery rate
/02Share of failed payments successfully recovered.
Involuntary churn
/03Customers lost to payment failure rather than choice.
Overdue balance
/04Outstanding balance waiting on recovery action.
Time to recovery
/05How quickly a failed payment is resolved.
Manual collection hours
/06Hours spent chasing payments by hand.
Complaint rate
/07Guardrail metric on tone and cadence.
Account manager workload
/08Only the right accounts reach a human.
Controls
Risk controls
Payment recovery touches customer relationships. Tone is controlled, retries are capped, high-value and sensitive accounts route to a human, and reminders stay clearly separate from legal collection.
- No aggressive collection language
- Human approval for high-value or sensitive accounts
- Opt-out handling
- Retry limits
- Billing status verification
- Audit logs
- Account owner escalation
- Fallback if the billing API fails
- Clear separation between reminders and legal collection
Implementation
A controlled path from audit to monitoring.
01
Audit
Review failure volume, decline mix, current dunning sequence, billing and CRM connections, and ownership.
02
Architecture
Design classification, scoring, sequence rules, message templates, and approval and escalation gates.
03
Build
Connect billing events, enrichment, scoring, sequences, and CRM/billing write-back.
04
Test
Validate classification and tone on real events; confirm retry limits, opt-outs, and escalation.
05
Launch
Roll out with guardrails on complaints, refunds, and chargebacks, and a baseline to measure against.
06
Monitor
Track recovery rate, recovered revenue, and complaint rate; run experiments to measure lift.
Common questions
What teams ask before we start.
01Is this only for SaaS companies?
No. Smart dunning fits any business with recurring revenue or invoicing — subscriptions, memberships, services, and B2B invoicing. Wherever payments can fail or invoices go overdue, the same detect-classify-score-recover pattern applies.
02Can this work with Stripe, Chargebee, QuickBooks, or Xero?
Yes. The system ingests payment and invoice events from Stripe, Chargebee, Recurly, QuickBooks, Xero, and similar platforms, then writes status back to billing and CRM. It is built around your existing billing stack.
03What is the difference between basic dunning and smart dunning?
Basic dunning sends one fixed retry-and-email sequence to everyone. Smart dunning classifies the decline (soft vs hard), scores recovery probability, segments by customer value, and adapts timing, channel, and message per account — escalating high-value cases to a human instead of retrying a dead card.
04Do you use machine learning for payment recovery?
Optionally. A scoring layer can estimate recovery probability and best retry timing using rules and, where data supports it, machine learning. It is used to prioritize and time outreach — not to make unsupervised decisions on sensitive accounts, which route to a human.
05How do you prevent aggressive or inappropriate payment reminders?
Tone is controlled by design: no aggressive language, capped retries, opt-out handling, billing-status verification before contact, and human approval for high-value or sensitive accounts. Reminders are kept clearly separate from legal collection, and complaint rate is monitored as a guardrail.
06How is recovery lift measured?
Against a baseline. We measure recovered revenue and payment recovery rate before and after, ideally with an A/B test of the baseline sequence vs the smart sequence, using recovered or retained revenue as the primary metric and complaints, refunds, and chargebacks as guardrails.
Next step
See how much revenue you could recover.
A focused review maps your billing events, decline mix, and current recovery workflow, then shows the recovery range and the first controlled automation worth building.