Prompt

My bounce rate is high after cleaning the list

Technology / Marketing Automation1 observationLast seen Oct 5, 2026

Latest observation

Oct 5, 2026OpenAI APIWeb search: off

A high bounce rate after cleaning the list usually means one of a few things:

  1. The cleanup missed bad addresses

    • There may still be invalid, misspelled, inactive, or role-based emails in the list.
    • Some verification tools only catch obvious issues and not deeper deliverability problems.
  2. The list is “valid” but not safe to mail

    • Some addresses are technically deliverable but still risky:
      • temporary/accept-all domains
      • recycled addresses
      • spam-trap–like addresses
      • old contacts who no longer engage
  3. The bounce type matters

    • Hard bounces: permanent problems like invalid mailbox/domain.
    • Soft bounces: temporary issues like mailbox full, server problems, or rate limiting.
    • If you’re seeing mostly soft bounces, the issue may be infrastructure or sending reputation, not just list quality.
  4. Your sending domain/IP may have deliverability problems

    • Poor sender reputation can trigger deferrals, blocks, or bounces.
    • Check:
      • SPF, DKIM, and DMARC setup
      • IP/domain reputation
      • complaint rate
      • engagement rate
  5. You may be emailing too many old or unengaged contacts

    • Even after cleaning, stale segments can still produce high bounce rates.
    • Remove contacts that haven’t opened/clicked in a long time.

What to do next

  • Break down bounces by reason code from your ESP.
  • Separate hard vs soft bounces.
  • Re-verify the list with a stronger validation process if needed.
  • Stop mailing risky segments until they’re re-validated.
  • Check authentication and reputation for your sending domain and IP.
  • Warm up slowly if this is a newly cleaned or newly imported list.

If you want, I can help you diagnose it more precisely if you share:

  • your bounce types/reason codes,
  • the percentage bouncing,
  • and what tool/process you used to clean the list.

Brands

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.

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