How LostChurn Recovered $2.3M in Failed Payments Last Quarter
A transparent look at aggregate recovery data across our merchant base: what worked, what surprised us, and the patterns that drove the highest recovery rates.
The Numbers at a Glance
In Q3 2025, LostChurn processed over 180,000 failed payment events across our merchant base and recovered $2.3 million in revenue that would otherwise have been lost to involuntary churn. The overall recovery rate was 62%, up from 54% in Q2 as our AI models continued to improve. The median time to recovery was 3.2 days, with 40% of recoveries happening on the first smart retry attempt, before any dunning email was needed.
What Drove the Highest Recovery Rates
Three factors consistently separated high-recovery merchants from the rest. First, merchants who enabled both smart retries and email dunning recovered 2.4 times more revenue than those using retries alone. Second, merchants with custom email branding saw 35% higher email recovery rates, suggesting that brand recognition builds trust during the update process. Third, merchants who responded to card-update declines within 4 hours recovered 70% of those payments, compared to 25% for merchants who waited more than 24 hours.
Surprising Patterns in the Data
Several findings challenged conventional wisdom. Weekend retries outperformed weekday retries for B2C subscriptions, likely because consumers check personal finances on weekends. For B2B, the opposite was true. Dunning emails sent between 9 AM and 10 AM local time had the highest click-through rates regardless of customer segment. And counter-intuitively, shorter dunning sequences (3 emails over 7 days) outperformed longer ones (5 emails over 14 days). Customers who did not act within a week rarely acted at all.
Recovery by Decline Category
Insufficient funds declines had a 58% recovery rate with smart retries alone. Card expiry declines reached 65% recovery when paired with a fast email response. Processor errors recovered at 89% since these are typically transient. Hard declines, as expected, recovered at under 5%, confirming that resources should be directed elsewhere. The biggest opportunity for most merchants was in the insufficient funds category, which represented 42% of all failures by volume.
Looking Ahead
As our recovery AI processes more data, it continues to find new timing and messaging patterns that improve outcomes. We are investing in predictive failure detection, identifying at-risk payments before they fail based on card expiry dates, historical decline patterns, and issuer behavior. Early results show that proactive card update reminders sent 7 days before expiry reduce card-expiry failures by 45%. Our goal is to prevent failed payments entirely, not just recover them after the fact.
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