Prompt

Mailgun bounces are hard to debug

Technology / API Platforms1 observationLast seen Oct 5, 2026

Latest observation

Oct 5, 2026OpenAI APIWeb search: off

Yes — Mailgun bounce handling can be painful because the useful details are often buried in webhook payloads, SMTP response codes, or provider-side logs.

A practical way to debug them:

  1. Check the event type

    • bounced vs dropped vs complained
    • dropped often means Mailgun never attempted delivery, or rejected it early.
  2. Inspect the bounce code and error

    • SMTP status codes matter a lot:
      • 4xx = temporary failure
      • 5xx = permanent failure
    • The error field usually has the best human-readable clue.
  3. Look at the recipient domain’s behavior

    • Some domains rate-limit, greylist, or block based on reputation.
    • Try sending to a known good mailbox at the same domain if possible.
  4. Verify SPF, DKIM, and DMARC

    • Misalignment can cause silent reputation issues or outright rejection.
    • Especially important if bounces are inconsistent across providers.
  5. Check Mailgun logs

    • Search by recipient, message ID, or timestamp.
    • Compare accepted vs rejected deliveries.
  6. Test with a controlled mailbox

    • Send to Gmail, Outlook, Yahoo, and a custom domain.
    • Different providers fail in different ways, which helps isolate the issue.
  7. Watch for content-related blocks

    • Spammy subject lines, links, or malformed HTML can trigger rejections.
    • Try sending a minimal plain-text message.
  8. Correlate with webhook retries

    • Sometimes the bounce event arrives later than the original send.
    • Make sure your system isn’t treating delayed events as duplicates or ignoring them.

If you want, I can help you build a bounce triage checklist or show you how to decode a real Mailgun bounce payload.

Observation history

How did Obsurfable measure this prompt?

Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.

Which AI systems does Obsurfable collect answers from?

OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, Meta AI, Qwen.

How can brands improve their AEO?

Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.

Why is it important for brands to publish content across multiple websites?

Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.

Want this interpreted for your brand?

Explorer is the free public corpus. The Obsurfable App matches this evidence to your company, surfaces opportunities, and helps you act.