In the rapidly evolving SaaS landscape, subscription businesses face a persistent challenge that silently erodes revenue: payment failures. While executives often focus on customer acquisition and retention rates, the efficiency of your payment operations can significantly impact your bottom line. Research from Recurly indicates that the average transaction decline rate across industries is approximately 13%, translating to substantial revenue leakage for growing businesses.
This article explores how to effectively measure payment failure and retry rates, providing SaaS executives with the knowledge to optimize payment operations and recapture lost revenue.
Why Payment Failures Matter to Your Bottom Line
Payment failures occur when attempted transactions don't complete successfully. According to a study by ProfitWell, involuntary churn—cancellations resulting from failed payments rather than customer choice—accounts for 20-40% of overall churn in subscription businesses. This silent revenue killer demands attention from the C-suite, not just the finance team.
When a payment fails, your business faces multiple consequences:
- Immediate revenue loss
- Potential permanent customer loss
- Increased operational costs for recovery efforts
- Negative customer experience
Understanding and measuring payment failure metrics allows executive teams to quantify this impact and implement strategies to minimize revenue leakage.
Essential Payment Failure Metrics Every SaaS Executive Should Track
1. Initial Payment Failure Rate
This foundational metric represents the percentage of attempted charges that fail on the first try.
How to calculate:
Initial Payment Failure Rate = (Number of Failed Initial Charges / Total Charges Attempted) × 100
Industry benchmarks from GoCardless suggest healthy businesses typically see rates between 5-15%, though this varies by payment method, geography, and industry. Credit card transactions generally experience higher failure rates than direct debit or ACH payments.
2. Retry Success Rate
After an initial failure, most billing systems attempt to recover the payment through automated retries. This metric measures the effectiveness of your retry strategy.
How to calculate:
Retry Success Rate = (Number of Successful Retries / Total Retry Attempts) × 100
According to data from Churn Buster, an optimized retry strategy can recover 45-70% of initially failed payments, highlighting the importance of this metric.
3. Dunning Effectiveness Rate
Dunning refers to the communication process aimed at recovering failed payments, typically through email notifications to customers.
How to calculate:
Dunning Effectiveness Rate = (Number of Payments Recovered Through Communications / Total Failed Payments) × 100
4. Payment Recovery Rate (Overall)
This comprehensive metric indicates your organization's total effectiveness at recovering revenue from initially failed payments.
How to calculate:
Payment Recovery Rate = (Total Revenue Recovered / Total Failed Payment Value) × 100
Research from FlexPay suggests that best-in-class SaaS businesses achieve payment recovery rates of 70-85%.
5. Time-to-Recovery
Beyond recovery percentages, the time taken to recover payments is crucial for cash flow management.
How to calculate:
Average Time-to-Recovery = Sum of (Recovery Date - Failure Date) / Total Recovered Payments
Segmentation: The Key to Actionable Insights
Raw failure and retry rates only tell part of the story. To extract actionable intelligence, segment your payment failure data by:
Payment Method
Credit cards typically show different failure patterns than ACH, PayPal, or direct debit options. According to Recurly, credit cards have an average failure rate of 15%, while ACH is closer to 3-5%.
Geography
Regional banking systems, regulations, and consumer behaviors significantly impact failure rates. European transactions using SEPA often experience different failure patterns than North American credit card transactions.
Subscription Tier
Enterprise customers may exhibit different payment behavior than SMB or individual subscribers, with corresponding differences in recovery strategies.
Failure Reason Codes
Categorizing failures by reason (insufficient funds, expired card, processing error) enables targeted recovery strategies for each scenario.
Implementing an Effective Measurement Framework
To develop robust payment failure and retry metrics:
1. Establish a Unified Data Environment
Connect your payment processor, subscription management platform, and customer database to create a single source of truth for transaction data.
2. Build Real-Time Dashboards
Develop executive dashboards that visualize key payment metrics, allowing for quick identification of concerning trends.
3. Implement Cohort Analysis
Track how payment failure metrics evolve over customer lifetimes, identifying any correlation between tenure and payment reliability.
4. Set Alert Thresholds
Establish warning systems for significant deviations in failure rates, which may indicate systemic issues requiring immediate attention.
Optimizing Your Strategy Based on Metrics
With robust measurement in place, focus on these areas to improve performance:
Smart Retry Sequencing
Data from Churn Buster indicates that the timing of retry attempts significantly impacts recovery rates. Rather than using fixed intervals, implement dynamic retry logic that accounts for:
- Specific failure codes
- Historical patterns of customer payment behavior
- Day of week and time of day
- Payment method constraints
Intelligent Dunning Communications
Leverage payment failure data to personalize recovery communications:
- Tailor messaging based on customer segment and failure reason
- Adjust communication timing based on historical recovery patterns
- Provide multiple resolution options (update card, use alternative payment method)
Payment Method Optimization
If your data shows consistently higher failure rates for specific payment methods, consider:
- Incentivizing customers to use more reliable payment methods
- Implementing account updater services for credit cards
- Offering preemptive card update workflows before expiration
Conclusion: From Measurement to Revenue Impact
Payment failures represent a significant but often overlooked revenue opportunity for SaaS executives. By implementing comprehensive measurement of failure and retry rates, your organization can:
- Quantify the true revenue impact of payment operations
- Identify specific points of friction in your payment ecosystem
- Implement targeted strategies for revenue recovery
- Create a better customer experience through smoother payment processes
For SaaS businesses operating at scale, even a modest improvement in payment recovery rates can translate to millions in annual recurring revenue. As one executive from subscription management platform Chargebee noted, "A 5% improvement in payment recovery often exceeds the revenue impact of a full percentage point of growth in new customer acquisition."
In today's competitive landscape, optimizing what you already have is just as important as acquiring what's new. Payment failure metrics provide a clear path to capturing revenue that's already been sold but not yet collected.