How can I identify which users marked my emails as spam in Gmail?

Email marketer from Sender Score indicates that closely monitoring your IP reputation is important. Sender Score analyzes various metrics to determine your sending reputation, and a low score can indicate issues such as high spam complaint rates, although the specific users are not identified.

Email marketer from Email Geeks shares that using the Feedback-ID header may provide some spam complaints per identifier in Google Postmaster Tools (GPT). Deciphering these identifiers may help identify some complainers, although these are just samples, not all complaints.

Email marketer from HubSpot indicates that implementing a double opt-in process is crucial to improve the quality of your list. You cannot see who marks your emails as spam, instead by having legitimate users who have confirmed their subscription, the chances of being marked as spam are reduced.

Email marketer from Neil Patel emphasizes the importance of monitoring your sender reputation. While you can't directly see who marked your email as spam in Gmail, a sudden drop in sender reputation is a strong indicator of increased spam complaints. Use tools like Google Postmaster Tools (GPT) to monitor reputation and identify potential issues.

Email marketer from Reddit user u/EmailGuru123 mentions that focusing on email list hygiene is crucial. Remove inactive users and those who haven't engaged in a while. While you can't see who marked you as spam, a cleaner list reduces the likelihood of complaints.

Email marketer from Email on Acid shares that regularly cleaning your email list is essential for reducing spam complaints. Removing unengaged subscribers and those who haven't opened or clicked in a while improves your sender reputation, even if you can't identify individual spam reporters.

Email marketer from Email Marketing Forum user User42 suggests segmenting your email list and sending targeted content to improve engagement. This can help reduce spam complaints, as recipients are more likely to find the content relevant. This will help improve your sender reputation and engagement metrics. This won't directly tell you who marks your emails as spam.

Email marketer from Mailjet discusses using one-click unsubscribe options and List-Unsubscribe headers as crucial elements for maintaining a healthy sender reputation. Although not directly revealing spam reporters, offering easy unsubscribe options can reduce the likelihood of users marking emails as spam.

Email marketer from Email Marketing Forum user EmailExpert suggests regularly reviewing the content of your emails. Ensure your content is relevant and not misleading. Even if you can't identify specific spam reporters, improving content quality can significantly reduce complaints.

Email marketer from Reddit user u/EmailPro mentions that using a dedicated IP address will help you monitor the spam rate if you keep the IP address warm, so the reputation will be highly associated with your email practices. You can't see who marked your emails as spam, however you will know your email practices lead to a low or high rate of spam reports.

Expert from Email Geeks shares an example where Google identified an 'L' within a structured data string (message ID or mail identifier) as a FBL identifier because it was consistently present across mailings for a specific list. This was visible in the GPT interface under 'FBL identifiers'. If you have a structured data string and it is consistent across mailings there is a chance that google will pick it up.

Expert from Spamresource.com explains that Feedback Loops (FBLs) are essential for identifying and responding to spam complaints. While FBLs don't reveal individual reporters, they provide aggregate data on which mailings are generating the most complaints. This allows senders to pinpoint problem areas and address them, such as list hygiene or content issues. In essence, focusing on the 'what' (which campaigns are causing issues) is more actionable than the 'who' (individual complainers, which is not provided).

Expert from Word to the Wise emphasizes that attempting to identify individual users who mark emails as spam is largely futile and often counterproductive. Instead, the focus should be on addressing the underlying issues that lead to spam complaints in the first place. These include ensuring proper list hygiene (removing unengaged subscribers), obtaining explicit consent, sending relevant and valuable content, and making unsubscribing easy. Rather than trying to find 'who' complained, work on 'why' they complained and fix it.

Expert from Email Geeks explains that using a unique link in the list unsubscribe header can provide an approximation of spam complaints, as Gmail may prompt users to unsubscribe when marking a message as spam. However, it's a fuzzy metric since the list unsub header is present in the mailbox, meaning not every click is a spam complaint.

Documentation from RFC2369 explains that a List-Unsubscribe header provides a way for users to easily unsubscribe from mailing lists. Although it does not directly help identify users marking emails as spam, it reduces the chance of this happening by enabling users to opt-out easily.

Documentation from Microsoft explains how they calculate sender reputation based on spam complaints, among other things. While they don't provide the list of users marking as spam, they advise to follow best practices in order to avoid ending up on blocklists.

Documentation from Google explains that Google Postmaster Tools (GPT) can provide aggregated feedback loop (FBL) data, allowing senders to identify campaigns generating high volumes of spam complaints. While it doesn't reveal individual users, it helps pinpoint problematic mailings for investigation and improvement.

Documentation from SparkPost explains that setting up feedback loops (FBLs) with major ISPs like Gmail allows you to receive aggregated data about spam complaints. While it doesn't provide user-level details, it identifies campaigns triggering high complaint volumes so you can address deliverability issues.