Suped

Do FBL messages get generated from bulk folders and how does this affect understanding email deliverability metrics?

Summary

While some in the deliverability community previously believed Feedback Loop (FBL) messages could not originate from emails sent to bulk or spam folders, a broader consensus, including documentation from major Internet Service Providers, clarifies that FBLs are indeed triggered by a recipient's action of marking an email as spam, regardless of its initial folder placement. However, emails that land directly in bulk folders are considerably less likely to be seen by recipients, which significantly reduces the probability of a user reporting them. Consequently, a low FBL rate often does not accurately reflect true inbox placement, as a substantial volume of emails may be silently routed to spam folders without generating any user complaints. This distinction is crucial for understanding email deliverability metrics, as relying solely on FBLs can lead to a misleadingly optimistic view of sender reputation and inbox performance.

Key findings

  • FBLs Can Originate from Bulk Folders: Feedback Loop (FBL) messages are generated when recipients actively mark an email as spam, and this action can occur even if the email initially landed in a bulk or spam folder, contrary to some prior beliefs among professionals.
  • Lower Likelihood from Bulk Folders: While technically possible, emails directed to bulk or spam folders are significantly less likely to be seen by recipients, which drastically reduces the probability of them being manually reported as spam and generating an FBL.
  • FBLs Measure Active Complaints: FBLs primarily serve as a measure of active user rejection and dissatisfaction. They do not directly indicate initial inbox placement, meaning a low FBL rate doesn't guarantee good inboxing.
  • Misleading Low FBL Rates: A low FBL rate can be highly misleading for deliverability metrics, as it may hide a substantial volume of emails silently filtered to spam folders without generating any complaints, thus obscuring true deliverability issues.
  • Challenges with Granular Data: Accurately calculating comprehensive complaint rates can be challenging due to difficulties in accessing granular data, often leading professionals to rely on simpler, though less precise, methods.

Key considerations

  • Beyond FBLs for True Deliverability: Deliverability professionals must understand that a low FBL rate does not guarantee strong inbox placement. It primarily reflects active user complaints and can mask significant volumes of email silently routed to spam or bulk folders, requiring a holistic view of deliverability metrics.
  • Accurate Complaint Rate Formulas: To gain a clearer picture, employ more precise complaint rate calculations, such as '# complaints / (total delivery - #emails to specific ISPs)' or '# complaints / # opens' per ISP, especially when suspecting that a high volume of mail is being bulked.
  • Identify Root Causes, Not Just Percentages: Focus less on the specific complaint percentage and more on using complaint data to identify underlying issues, such as poor list acquisition practices or content problems, that contribute to unwanted mail.
  • ISP-Specific Analysis: Analyze complaint rates segmented by recipient domain or Internet Service Provider (ISP) to pinpoint specific deliverability challenges with certain mail providers.
  • Acknowledge Knowledge Gaps: Recognize that even experienced professionals may have specific knowledge gaps. Continuous learning and collaborative team environments are crucial for staying informed about evolving deliverability nuances.

What email marketers say

13 marketer opinions

While Feedback Loop (FBL) messages are user-initiated reports that can technically arise from emails in bulk folders, their generation is significantly less probable in such scenarios. This creates a critical challenge for understanding deliverability: a low FBL rate may falsely signal excellent inbox placement, as substantial volumes of email could be silently routed to spam folders without ever being seen, let alone reported, by recipients. Consequently, FBLs primarily indicate active user rejection rather than a comprehensive measure of inbox success, highlighting the necessity for a broader analytical approach to deliverability metrics.

Key opinions

  • FBLs User-Initiated: FBL messages originate solely from recipients actively marking an email as spam, not from automatic system filters.
  • Reduced Visibility in Bulk: Emails landing in bulk or spam folders are considerably less likely to be seen by recipients, drastically reducing the chance of generating a spam complaint.
  • Low FBL Rates Can Mislead: A low FBL rate does not inherently guarantee strong inbox placement; it can obscure significant volumes of email silently filtered into spam folders without user interaction.
  • FBLs Show Active Rejection: These reports primarily measure active user dissatisfaction and explicit rejection, rather than providing a complete picture of an email's initial folder destination.
  • Knowledge Gaps Among Professionals: Despite its importance, the nuanced behavior of FBLs from bulk folders, and the implications for deliverability metrics, is not uniformly understood across all email professionals.
  • Misleading ESP UI Data: Some Email Service Provider user interfaces may present complaint rate calculations that can be misleading, necessitating a deeper, custom analysis for accurate insights.

Key considerations

  • FBLs Alone Are Insufficient: Deliverability professionals should never rely solely on FBL rates as an indicator of inbox success, as they can mask serious filtering issues to spam folders.
  • Assume Silent Bulking Risk: A low FBL rate, especially when coupled with poor open or click-through rates, should prompt suspicion of silent bulking to spam folders.
  • Holistic Metric Evaluation: Combine FBL data with other metrics like open rates, click rates, and direct inbox placement tests across various ISPs for a more accurate deliverability assessment.
  • Advanced Complaint Rate Calculations: Employ more robust formulas, such as comparing '# complaints / # opens' per ISP, to gain a clearer understanding, particularly when suspecting significant bulking.
  • Embrace Continuous Learning: The email deliverability landscape is dynamic; staying updated on nuanced behaviors like FBL generation from bulk folders is crucial for effective strategy.
  • Leverage Team Expertise: Recognize that knowledge gaps are common. Fostering a collaborative environment where team members share insights can collectively enhance understanding and problem-solving.

Marketer view

Email marketer from Email Geeks explains that most delivery professionals know mail in bulk folders doesn't generate FBLs, but end-users often do not. He asserts that a "deliverability engineer" should certainly possess this knowledge.

15 Jul 2022 - Email Geeks

Marketer view

Email marketer from Email Geeks agrees it's common knowledge for deliverability professionals that mail in bulk folders doesn't generate FBLs, stating it's not unreasonable to expect this from someone with that job title.

17 Jan 2024 - Email Geeks

What the experts say

3 expert opinions

Feedback Loop (FBL) messages are indeed generated when users mark an email as spam, irrespective of whether it landed in their inbox or a bulk/junk folder. This means FBLs provide a comprehensive signal of user dissatisfaction across all email placements, making their understanding vital for accurate deliverability metrics. While it is true that emails silently filtered into bulk folders are less likely to be seen and thus reported, any complaints originating from these folders still significantly impact sender reputation, alerting Internet Service Providers (ISPs) to unwanted mail and potentially leading to more aggressive filtering. Therefore, a low FBL rate can still mask underlying deliverability issues if a large volume of mail is being shunted to spam unseen.

Key opinions

  • FBLs From Any Folder: Feedback Loop (FBL) messages are generated from user complaints, whether the email initially landed in the inbox or a junk/bulk folder.
  • Comprehensive Dissatisfaction: FBLs offer a comprehensive measure of user dissatisfaction, providing insights into unwanted mail across all email placements.
  • Reputation Impact: Complaints originating from bulk folders still negatively impact sender reputation and can lead to more aggressive filtering by ISPs.
  • Misleading Low FBLs: Despite FBLs being generated from bulk folders, a low FBL rate can be misleading if significant volumes of mail are routed to spam without being seen or reported by recipients.
  • Complaint Rate Complexity: Accurately calculating complaint rates remains challenging due to the difficulty of accessing granular data, often requiring specific methodologies.

Key considerations

  • Crucial FBL Monitoring: Continuously monitor FBL rates, understanding they are a critical indicator of user dissatisfaction across all email placements.
  • Beyond FBLs Alone: Always combine FBL data with other metrics like open rates and inbox placement tests, as a low FBL rate might not fully reflect true deliverability issues if mail is largely unseen in spam folders.
  • Advanced Calculation Methods: Employ more precise complaint rate calculations, such as '# complaints by recipient domains / sent to domain,' to identify issues with specific ISPs.
  • Focus on List Quality: Utilize complaint data, regardless of its origin, to identify and address fundamental issues like poor list acquisition practices that lead to unwanted mail.
  • ISP-Specific Analysis: Drill down into complaint data by individual Internet Service Provider (ISP) to pinpoint specific deliverability challenges and patterns.

Expert view

Expert from Email Geeks explains that mail in bulk folders cannot generate FBL messages, highlighting that deliverability engineers should be aware of this. She further clarifies that low complaint rates can be misleading if mail is heavily bulked, leading to blocking. She discusses the challenges of accurately calculating complaint rates, proposing a method like "# complaints / (total delivery - #emails to gmail.com)" and noting that the specific percentage is less important than identifying poor list acquisition practices. She acknowledges the difficulty of accessing granular data for more precise calculations, often leading to simpler approaches.

29 Nov 2022 - Email Geeks

Expert view

Expert from Email Geeks suggests calculating "#complaints by recipient domains/sent to domain" to identify issues with specific ISPs. He reiterates that mail already in the spam folder cannot generate reports like FBLs, and advises starting with broad data before drilling down to understand patterns, noting that while data is available, accessing it can be challenging.

26 Jul 2021 - Email Geeks

What the documentation says

4 technical articles

Despite emails frequently landing in bulk folders, Feedback Loop (FBL) messages can still be generated from them when a recipient actively marks a message as spam. This consistent explanation from major email providers, including Google, Microsoft, and Amazon, underscores that FBLs are a direct reflection of user action rather than initial folder placement. While an email routed to a bulk folder is less likely to be seen and thus less likely to generate an FBL, any complaint still negatively impacts sender reputation. Consequently, a low FBL rate should not be the sole indicator of strong deliverability, as it may obscure significant volumes of mail that are silently shunted to spam without ever being reported.

Key findings

  • FBLs from Any Folder: Feedback Loop (FBL) messages are generated when a user marks an email as spam, regardless of whether the email initially landed in the inbox or a bulk/junk folder.
  • User Action Driven: FBLs are solely triggered by active user complaints and explicit actions, such as clicking 'report spam,' rather than automatic system routing.
  • Reduced FBL Probability from Bulk: Emails delivered to bulk or spam folders are significantly less likely to be seen by recipients, which drastically reduces the probability of them generating an FBL.
  • Low FBL Rates Can Be Misleading: A low FBL rate does not guarantee strong inbox placement; it can obscure cases where a high volume of emails are silently filtered into spam without user interaction.
  • Consistent ISP Stance: Documentation from major providers like Google Postmaster Tools, Microsoft Learn (JMRP), Amazon SES, and Server Fault consistently confirms that FBLs arise from user complaints irrespective of initial folder placement.

Key considerations

  • FBLs as Active Complaints: Understand that Feedback Loop (FBL) messages are primarily indicators of active user complaints and explicit rejections, rather than a definitive measure of initial inbox placement.
  • Don't Rely Solely on FBLs: Never use a low FBL rate as the only metric for judging inbox deliverability, as it can hide significant volumes of email silently filtered to spam folders.
  • Holistic Deliverability Analysis: Integrate FBL data with other crucial metrics like open rates, click-through rates, and inbox placement tests to gain a comprehensive understanding of deliverability performance across different Internet Service Providers (ISPs).
  • Reputation Impact Still Occurs: Recognize that even infrequent FBLs originating from bulk folders still negatively impact sender reputation and can contribute to more aggressive filtering in the future.
  • Leverage ISP Documentation: Consult specific documentation from major ISPs like Google, Microsoft, and Amazon to understand their nuanced FBL policies and how they define complaint triggers.

Technical article

Documentation from Google Postmaster Tools explains that Feedback Loop (FBL) reports are generated when users mark messages as spam, irrespective of whether the email initially landed in the inbox or a bulk folder. This means a low FBL rate doesn't guarantee inbox placement, as users are less likely to report spam they don't see in their main inbox. It primarily reflects active user complaints.

20 Dec 2021 - Google Postmaster Tools Help

Technical article

Documentation from Microsoft Learn, detailing their Junk Email Reporting Program (JMRP), indicates that FBL messages are triggered by user actions, specifically when recipients report an email as 'junk' or 'phishing.' While most users might not check bulk folders, an email landing there can still generate an FBL if the user discovers and reports it, making FBL rates a measure of active complaints rather than sole inbox placement.

4 Sep 2021 - Microsoft Learn

Start improving your email deliverability today

Get started
    Do FBL messages get generated from bulk folders and how does this affect understanding email deliverability metrics? - Sender reputation - Email deliverability - Knowledge base - Suped