How does Google calculate spam rate and what does 'active users' mean in Google Postmaster Tools?

Key findings

• Spam rate calculation: Google's spam rate is generally understood as the percentage of emails users mark as spam relative to the messages delivered to the inbox.
• Active users ambiguity: The definition of 'active users' in GPT is not explicitly clear, leading to varied interpretations across the industry. This ambiguity can affect how senders gauge the actual impact of their spam rates.
• Inbox placement impact: If a significant portion of emails is filtered directly into spam folders, the reported spam rate in GPT might appear low, even if the sender has underlying deliverability issues.
• No recent changes: There have been no recent official announcements from Google regarding changes to their spam rate calculation methodology in Postmaster Tools.
• Distinction from ESP rates: Google's method differs from how some Email Service Providers (ESPs) calculate spam rates, as ESPs often base it on total delivered emails, potentially masking issues if mail is consistently spam-foldered.

Key considerations

• Interpret with caution: Senders should approach GPT data, especially the spam rate, with a critical eye, recognizing that a low rate doesn't automatically imply perfect deliverability if many emails are redirected to spam. You can learn more about this in our guide on how to interpret spam complaints.
• Engagement metrics: Given the 'active users' context, it's crucial to focus on list hygiene and engagement to ensure emails reach engaged recipients, improving overall sender reputation.
• Beyond the rate: A comprehensive understanding of your sending performance requires looking beyond just the spam rate dashboard in GPT, considering other metrics like domain reputation and delivery errors.
• Industry resources: Referencing expert analyses, such as those that delve into a closer look at Postmaster Tools, can provide additional context and strategies.

Key opinions

• Perceived vagueness: Marketers frequently find Google's explanations of spam rate calculation and 'active users' to be vague, making it difficult to pinpoint the exact reasons behind observed fluctuations.
• Impact of unengaged users: Some marketers believe that users who do not open emails, even if they reach the inbox, might not be fully counted in the 'active user' denominator, potentially impacting the reported spam rate.
• Spam folder effect: A common concern is that if emails are heavily filtered into spam folders, the user-reported spam rate in GPT might appear deceptively low, as users cannot report mail they don't see.
• Troubleshooting challenges: When facing sudden spikes in spam rates, marketers often struggle to understand the root cause due to the perceived lack of granular detail in GPT's reporting.

Key considerations

• Holistic view: Marketers should not solely rely on GPT for deliverability insights but combine it with ESP data and other monitoring tools to get a complete picture. This helps identify issues like why GPT rates are higher.
• Focus on engagement: Regardless of the exact 'active user' definition, maintaining high user engagement is key to positive sender reputation and avoiding blocklists, as explored in articles like Understanding Email Spam Rate Thresholds.
• Monitor for spikes: Regularly check GPT for sudden spam rate spikes, even if other metrics seem stable, as this can indicate emerging issues with user perception or filtering. Learn more about why you are seeing spam spikes.

Key opinions

• Lack of detailed clarity: Experts generally agree that Google has never provided exhaustive detail on their spam rate calculation, leading to industry speculation rather than concrete facts.
• Spam folder vs. reported spam: A key point of contention is whether mail landing in the spam folder impacts the user-reported spam rate in GPT. Some experts argue that if mail bypasses the inbox entirely, users can't mark it as spam, thus yielding a falsely low reported rate, while others suggest Google's calculation inherently accounts for this.
• Interpreting 'active users': The term 'active users' is undefined by Google, prompting experts to propose various interpretations, such as users who log into their account, open messages, or see mail on their first page/promotions tab.
• Distinction from ESP calculations: Google calculates the spam rate based on mail delivered to the inbox, which differs from many ESPs that use 'number delivered' as their denominator. This can lead to discrepancies between internal and GPT reports.
• Spam folder placement matters: Despite debate on its direct impact on the reported spam rate, experts agree that high spam folder placement is a clear indicator of poor sending quality and will be noted by ISPs, even if user complaints are low.

Key considerations

• Google's internal knowledge: Remember that Google has complete data on where emails land (inbox or spam folder), allowing them to assess true deliverability irrespective of user complaint rates. This is outlined in our ultimate guide to Postmaster Tools.
• Beyond reported rates: A low user-reported spam rate in GPT does not guarantee good inbox placement. Experts stress the importance of monitoring all deliverability metrics comprehensively.
• Consider all factors: Investigate potential issues like DKIM replay or other authentication failures when inexplicable spam spikes occur.
• Proactive monitoring: Utilize available tools and methods to proactively identify deliverability issues, as discussed in detail on Mailgun's guide to sender reputation.

Key findings

• Core definition: The spam rate is presented as the percentage of emails marked as spam by users compared to emails successfully delivered to the inbox for active users.
• Active user emphasis: The phrase 'active users' is consistently used, implying a subset of users, though its criteria are not explicitly detailed in publicly available documentation.
• Spam folder caveat: Documentation suggests that if a substantial number of emails are delivered directly to spam, a low user-reported spam rate might be observed, even if users are still marking inboxed emails as spam.
• Monitoring tools: Google Postmaster Tools is positioned as a free service offering metrics on delivery errors, spam rates, and domain reputation for Gmail-hosted recipients.

Key considerations

• Contextual understanding: Documentation hints at the complexity of spam rate metrics, encouraging senders to look beyond a single number and consider the full context of their email delivery, as discussed in our guide to the Postmaster Tools spam rate dashboard.
• Reputation correlation: The spam rate is a key indicator of sender reputation, influencing how Gmail filters future messages, underscoring the importance of maintaining a low rate, as highlighted by Amazon Web Services' insights.
• Comprehensive monitoring: While useful, GPT data should be part of a broader deliverability strategy that includes monitoring other factors like DMARC, SPF, and DKIM authentication to ensure emails are correctly delivered.