Track Failed Payments with Resend
Never miss a failed charge again
The problem
Failed payment recovery relies on timely, reliable customer outreach. When dunning and billing emails sent via Resend are not tracked with failure events, teams cannot tell whether users actually received next steps.
You may see the failed charge but miss bounced reminders or low engagement with recovery emails. That delays intervention and reduces recovery rates.
Without integrated visibility, involuntary churn grows even when your billing logic is correct.
The solution
Quicklog combines failed payment events with Resend delivery outcomes so your team can respond with full context. Log the failure reason, amount at risk, and related dunning message status in the same event flow.
With this view, support can prioritize accounts where outreach failed and trigger alternative contact paths quickly. Teams spend less time guessing and more time recovering revenue.
You can also evaluate which dunning messages and sequences actually improve payment recovery.
Why track this?
- Instant alerts on payment failures
- See the failure reason and amount at risk
- Reduce involuntary churn significantly
Quick setup
Handle Resend webhooks:
import { Quicklog } from '@quicklogio/node'
const quicklog = new Quicklog({ apiKey: process.env.QUICKLOG_API_KEY! })
// Handle Resend webhooks
app.post('/webhooks/resend', async (req, res) => {
const payload = req.body
// Log the webhook event
await quicklog.track({
channel: 'payments',
event: 'resend.' + (payload.type || 'event'),
description: 'Resend webhook received',
metadata: {
provider: 'resend',
eventType: payload.type,
payload
}
})
// Process the webhook...
await processWebhook(payload)
res.json({ received: true })
})Track Failed Payments as an operational analytics workflow
This guide is built for teams that need actionable saas analytics, not just passive reports. By instrumenting track failed payments in Resend, you create a reliable signal that product, growth, and support can use in real time.
In Quicklog, these events become part of a shared timeline with user context, channel grouping, and trend visibility. That makes it easier to connect day-to-day operations with larger product analytics saas goals like activation quality, retention improvement, and faster troubleshooting.
If you are evaluating saas analytics tools, this use case is a strong baseline because it combines technical implementation with clear business outcomes. It also supports adjacent workflows such as analytical crm and failed payment monitoring without requiring a separate analytics stack.
Ready to track failed payments?
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