Why does Google Postmaster Tools show delivery errors when emails are delivered?

Key findings

• Temporary failures: GPT includes temporary failures (like 4xx SMTP codes) in its delivery error statistics, even if subsequent retries result in successful delivery.
• Data sampling: The data in GPT is often based on samples rather than exhaustive logs, which can lead to statistical variations and perceived inconsistencies.
• Inconsistent reporting: There can be discrepancies between the aggregate delivery error percentages shown in the main graph and the detailed daily breakdowns, sometimes showing 'no delivery errors' on a specific day despite an overall percentage.
• Delayed updates: GPT data can experience delays, meaning recent improvements or issues may not be immediately reflected, as discussed in why is Google Postmaster Tools data delayed or missing?.

Key considerations

• Rely on internal logs: Your own mail logs and bounce data are typically the most accurate source for determining final delivery outcomes.
• Monitor trends: Use GPT for high-level trends and overall domain/IP reputation, not for pinpointing individual delivery successes or failures. For more on key metrics, see what email deliverability metrics to monitor.
• Understand temporary states: Recognize that a 'delivery error' in GPT might just be a temporary deferral that was later successfully delivered. Google's documentation clarifies that these include rejected or temporarily failed emails to Gmail, as described in their official Postmaster Tools help article on delivery errors.
• Authentication impact: Ensure your SPF, DKIM, and DMARC records are correctly configured, as authentication failures can lead to deferrals or rejections that show up as delivery errors.

Key opinions

• GPT is a signal: Many marketers view GPT data as a 'signal' or an 'indicator' rather than a precise measurement of deliverability.
• Trust internal logs: There is a strong consensus among marketers to always prioritize their own email bounce logs and platform reports over GPT's figures.
• Temporary error confusion: Marketers frequently suspect that the reported delivery errors are due to temporary failures (temp-fails) that eventually resolve upon retry, even if GPT still counts them as errors.
• Data discrepancies: Issues with GPT's API not consistently matching the UI, or general data 'being off', are common complaints.

Key considerations

• Cross-reference: Always cross-reference GPT data with your own sending platform's reports and bounce logs to get the full picture of delivery. This aligns with advice on interpreting discrepancies in deliverability data.
• Don't overreact: Small percentages of delivery errors, especially without corresponding hard bounces in your logs, might not indicate a severe issue.
• Monitor warming: If you are warming up a new domain or IP, spikes in GPT delivery errors can indicate you're sending too fast and need to adjust your pace, as detailed by SendLayer's guide to monitoring email deliverability.
• Review reputation: Pay close attention to your domain and IP reputation scores within GPT, as these often provide more reliable long-term insights than daily error percentages.

Key opinions

• Aggregated data: GPT provides aggregated and sampled data, which may not always align perfectly with the specific, detailed logs from your mail server.
• Temporary vs. permanent: The delivery error metric often includes 'temp-fail' (4xx) responses, indicating a temporary issue that can be resolved by retries, differing from permanent rejections (5xx).
• Trust logs first: Experts universally recommend relying on your own SMTP server logs for the definitive status of individual email deliveries.
• Monitoring tool: GPT is best used for observing long-term trends in reputation and delivery rates, and for identifying potential issues that warrant deeper investigation with your logs.

Key considerations

• Contextual analysis: Interpret GPT data within the context of your overall sending volume and observed bounce rates from your internal systems.
• Authentication checks: Even if SPF and DKIM appear to pass, review GPT's authentication dashboards to ensure consistent alignment and to catch potential issues like advanced authentication failures.
• Focus on reputation: Maintaining a high sender reputation (domain and IP) is paramount, as low reputation can directly lead to deferrals and rejections that GPT reports as errors. SpamResource.com often provides insights into this.
• Investigate spikes: Sudden increases in delivery errors in GPT should prompt an investigation into your sending patterns and recipient feedback, even if initial checks show no hard bounces.

Key findings

• Scope of errors: The delivery errors dashboard explicitly includes both 'rejected' and 'temporarily failed' email messages.
• Authenticated traffic: These metrics apply to all authenticated traffic originating from your domain that targets Gmail recipients.
• Temporary deferrals: Even if a temporary failure leads to a successful delivery on a subsequent retry, the initial deferral contributes to the 'delivery errors' reported by GPT.
• No specific daily breakdown: While an aggregate percentage is provided, detailed reasons for specific daily errors may not always be available within the tool, aligning with general common issues with GPT data.

Key considerations

• Interpret definitions: Carefully read Google's definitions of 'rejected' and 'temp-failed' to understand what each category signifies in their reporting.
• Holistic view: Combine GPT's insights with a broader understanding of SMTP error codes (like RFC 5321) to discern true deliverability issues from transient network conditions.
• Data accuracy: Be aware that GPT data can sometimes be delayed or incomplete, as highlighted in why Google Postmaster Tools data is not updating.
• Sender reputation impact: Persistent temporary failures can negatively impact your sender reputation, even if emails eventually get delivered, potentially leading to more significant rejections in the future.