How Google Postmaster Tools Domain Reputation & Spam Rate Works
The complete guide on how google postmaster tools (GPT) works for domain reputation and spam rate. Including the data in spam rate most people misinterpret.
Google Postmaster Tools (GPT), helps you track deliverability and sentiment, specifically to google email users, across email traffic on domains and IPs.
As Google users make up a large portion of most commercial lists, the free application from Google can provide faster, more detailed insights than most other feedback loops. (Especially if your emails are being reported by users as spam or have deliverability issues).
We’ll outline the ins and outs of Google Postmaster Tools in this guide, including some of the most commonly misunderstood details of GPT such as:
How is Reputation & Spam Rate Calculated in Google Postmaster Tools?
Postmaster Tools will provide you with a percentage spam rate. This is calculated based on only the reports that Google users take on your emails. Therefore, the calculation which is being run by Google Postmaster Tools is: (Emails Google Email Users Report as Spam / Quantity of Emails Sent to Google Email Users) * 100
This means each of the percentage points you’re seeing for spam rate in GPT is based on the number of emails you send to google users where they are manually selecting the ‘Report spam’ option in their Gmail interface:
Google specifically outlines this themselves in their documentation, but a lot of users miss this key detail. Simply put, the spam rate analysis you see inside GPT does not give any indication of the percentage of your emails which are automatically being placed/filtered into Spam, Promotion or other unfocused folders (which is where recipients are unlikely to ever see them):
As Google outlines, this means when your emails are directly delivered to spam folders, the spam rate may appear as low, even if a substantial portion of your emails land there. This means that GPT can be used to get an idea of spikes in reports, but not to truly measure if you have an issue with emails not reaching the inbox or your actual placement in spam over time.
Therefore, make sure you’re aware of, and have considered these top 5 mistakes people make - by misinterpreting data in Postmaster Tools:
You see a low spam report rate because large portions of your emails are automatically landing in spam folders. (remember, it’s impossible for a user to manually report your emails as spam if they’re already landing there).
Your emails are landing in folders that most recipients don’t read. There are a bunch of other folders (like promotions) where emails can land, and if prospects aren’t reading your emails, they’re very unlikely to report them as spam.
If you see a decline in spam rate in Postmaster Tools, this might not always be a positive signal. As this could mean more of your emails have started delivering into the spam folder directly.
An Increase in spam rate inside Google Postmaster Tools can occur after your deliverability improves, when your content still needs to be made less aggressive. This occurs because if you overhaul your deliverability, more contacts usually start seeing your messages - which increases your risk of being manually reported.
It usually takes around 48hrs for Google Postmaster Tools to fully populate and display all the data which is available inside your dashboard. Therefore, don’t draw any conclusions from the analysis until this time frame has passed after set-up.
What Google Postmaster Tools Will Provide You
Google Postmaster Tools will provide data sets across seven different areas which impact deliverability. After you've set-up and verified your domain(s) in GPT, you’ll be able to analyze each of the following across the timeline of 7 to 120 days:
Spam Rate in GPT
The percentages being calculated and tracked give you a clear indication of manual user spam reports, not how often your emails are landing in spam folders. Therefore, consider analysing how your content and audience have changed during periods where you see spikes. This will help you highlight the segments and content which is most risky for you to contact so you can iterate your approach for lower future reports. According to Google support, this data should include reports for both Google Workspace users and @gmail users in the rates it reflects. However, this is dependent on your email recipient utilizing a Google server.
The scale of Bad-High on Domain Reputation in Postmaster Tools is designed to give an idea of how Google views the track record of your domain being filtered into spam. Although ‘High’ is of course better than ‘Bad’, this data set does not provide any quantifiable scale on how frequently your emails will be filtered into spam, and Google does state in their documentation that emails can still be filtered into spam when a domain is in each of the categories listed.
Spam Feedback Loop
This chart is available after you set up a Gmail Spam Feedback Loop (FBL), which allows you to see an average spam rate graph based on manual spam reports from @gmail users, as well as see spam reports relating to specific campaigns where you have implemented a unique identifier. This can pariticaly add value for ESPs. It's important to note the documentation on the spam Feedback Loop, specifically states it only includes data on report from personal/free email users (utilizing an @gmail address). This is unusual given Google claim the 'Spam report' rate includes corporate users, however, this may be because the use-case for the feedback loop is primarily for ESPs like sendgrid to identify abuse towards consumers on their own servers.
Authentication in GPT
The authentication dashboard provides an outline of the percentages of your email traffic over a specific time frame which are passing DKIM, SPF and DMARC, respectively (while excluding any spoofed emails). While this functionality can be great for an overview periodically, you will not be notified of issues proactively when they occur. If you’d like an alert whenever a failure occurs, you can check out the additional Allegrow functionality around SPF, DKIM and DMARC checks.
Encryption in GPT
Encryption in Postmaster Tools shows Transport Layer Security (TLS) traffic which passes on an inbound and outbound basis - assuming there is both inbound and outbound traffic on the domain you’re analysing. Therefore, this data summarizes the volume of traffic on a domain you send that is encrypted on an inbound and outbound basis.
Delivery Errors in GPT
The chart for delivery errors in Postmaster Tools shows the percentage of your total email traffic which was rejected or temporarily failed by google as an ISP over the specified time frame. This is when your request to send the message was not fulfilled, due to reasons like the rate limit being exceeded. This is not to be confused with a report of bounces (as this is different to delivery errors in GPT). The complete outline of the ten reasons for delivery errors on your email traffic is available here.
Guide to Setting Up Google Postmaster Tools
After getting a clear understanding of how you’ll interpret data in Google Postmaster Tools and clarifying what is included in the data set, you’ll probably want to progress with setting up the GPT dashboard for free.
To set up Postmaster tools, follow the four steps below:
1. As the first step, go to: https://postmaster.google.com/, then sign in to Postmaster Tools using either your primary G Suite account or a specific team G Suite account you’d like to manage GPT from.
2. Then enter the domain or subdomain you want to track and analyze email activity on. (have multiple domains? Don’t worry you can add the rest later):
3. Proceed to add the TXT record google provides to the DNS of the specific domain in question. Or add a CNAME record as an alternative form for ownership verification. After adding either record, click ‘VERIFY’:
4. After successful verification, you’ll see data populate in your postmaster dashboard for the domain in question. You can then proceed to add any other domains by clicking the ‘+’ symbol in the bottom right-hand corner of the postmaster tools dashboard.
How You Can Calculate Inbox Placement Rate
To receive a real-time view of where emails are being automatically filtered (not just when users are manually moving them to spam), you’ll want to monitor your inbox placement on a network of real email inboxes.
This can be achieved with platforms like Allegrow, which have community networks of real email inboxes which are monitored to see where your emails get automatically placed on average each day.
Why can’t you just send emails to inboxes you created or fake accounts and check? Well, you can, but the data won’t be very accurate or sustainable. In order to provide an accurate reading of where emails are landing on average, you’ll want data to be taken from multiple domains which have real independent owners.
Platforms like Allegrow have the added benefit alongside Postmaster tools of simulating positive interactions to help improve your general sender reputation each day, monitoring your general inbox placement and using an email safety net to automatically prevent highly risk emails being sent by your team.