Summary
Observations and experiences with GPT's subdomain breakdowns and spam rate identifiers indicate inconsistencies and ongoing development. The subdomain breakdown feature exhibits variability, with some users seeing detailed information while others experience simplified views or a lack of data. Spam rate identifier data is also inconsistent, leading to assumptions about complaint counts and the potential for data lags. Key factors influencing these observations include data processing delays, privacy thresholds, accuracy of identifiers, domain authentication, and feedback loop alignment. It is recommended to cross-reference data, focus on root domain reputation, and utilize campaign identifiers for a more comprehensive analysis.
Key findings
- Variable Subdomain Breakdown: GPT's subdomain breakdown feature fluctuates in detail, suggesting it is in a beta stage of development.
- Inconsistent Spam Rate Data: Differing user experiences exist with spam rate identifiers; some see rates, while others see only identifiers, requiring assumptions about data interpretation.
- Data Availability Issues: Some users report never receiving rate data, implying the feature may not be fully implemented or is affected by factors like privacy thresholds.
- Data Accuracy Concerns: The accuracy of postmaster tools data, which GPT relies on, is questionable and can lead to skewed results.
- Spam Filter Influence: The data can also be impacted by how the filters being used are configured. An example of this is the spamfilter being too strict.
Key considerations
- Cross-Reference Data Sources: Cross-reference identifier and spam rate data with other monitoring tools for a more comprehensive analysis due to potential inaccuracies.
- Domain Reputation Focus: Prioritize monitoring and maintaining the reputation of the root domain, as it impacts overall deliverability.
- Use Campaign Identifiers: Utilize unique campaign identifiers to track spam complaints effectively and improve data interpretation.
- Data Processing Delays: Always keep in mind that when analyzing data, there is a potential for processing delays.
- Ensure you're registered with all ISPs: When relying on feedback loops and data, you should ensure that the feedback loop has registered with all ISPs properly.
- Remember IP Reputation: Remember that many deliverability issues may come from IP Reputation and you should focus on that also.
What email marketers say
17 marketer opinions
Observations regarding GPT's subdomain breakdowns and spam rate identifiers indicate inconsistencies and ongoing development. Some users report detailed subdomain breakdowns, while others see a simplified view or no data. Spam rate identifier data is also inconsistent, with some seeing rates and others only identifiers, leading to assumptions about complaint counts. Various factors, including data lags, accuracy of identifiers, and domain authentication, influence these observations. External data and campaign identifiers are recommended for further clarification.
Key opinions
- Inconsistent Subdomain Breakdown: GPT's subdomain breakdown feature varies, sometimes showing detailed information and other times reverting to a simpler view, suggesting ongoing development and potential instability.
- Spam Rate Identifier Data Variance: Users report differing experiences with spam rate identifiers; some see actual rates, while others only see a list of identifiers, prompting assumptions about the data's interpretation.
- Incomplete Data: Some users have never received any rate data, indicating that the feature might be under development or not fully implemented for all domains.
- Potential Data Lags: Gmail Postmaster Tools data (spam identifier data) sometimes lags and may not reflect real-time spam rates, especially for low-volume senders.
Key considerations
- Cross-Reference Data: Due to the variability in spam identifier accuracy, it's recommended to cross-reference the data with other spam monitoring tools for a more comprehensive analysis.
- Proper Domain Authentication: Proper domain authentication is essential for the most complete and accurate results, which can help avoid issues with subdomain tracking and identifier data.
- Focus on Root Domain Reputation: While subdomain monitoring is important, prioritize monitoring and maintaining the reputation of the root domain first, as this can influence the overall deliverability.
- Utilize Campaign Identifiers: Using unique campaign identifiers can help track spam complaints more effectively, making it easier to understand and interpret the identifier data in GPT.
- Consider Data Variability: Be aware that domain reputation and spam data can vary across different monitoring tools and ISPs; GPT relies on the underlying accuracy of this spam data. So data needs to be considered within the context of the tool it is using to measure the data.
Marketer view
Email marketer from Email Geeks states they have never received any rate data for any of the domains they're checking, believing it to be under development.
19 Aug 2023 - Email Geeks
Marketer view
Email marketer from Email Geeks confirms no rate for identifiers, just a list of identifiers per day, assuming one complaint per identifier due to lack of further information.
27 Jun 2024 - Email Geeks
What the experts say
4 expert opinions
Experts have observed varying experiences with GPT's subdomain breakdowns and spam rate identifiers. Subdomains are visible in both V1 and V2 but actual spam rate data may be missing. Inaccuracies in postmaster tools data are highlighted, suggesting a comparison across tools. Spam filtering issues can stem from factors such as IP reputation and overly strict filters, potentially skewing spam rate reports.
Key opinions
- Subdomain Visibility: Subdomains are visible in both the new and old versions of GPT tools
- Missing Spam Rate Data: Despite identifier data existing, an actual spam rate is often absent, represented by a dash.
- Data Inaccuracy: Data from postmaster tools, including Google's, might be inaccurate and should be verified by comparison with other sources such as Microsoft SNDS.
- Filter Influence: Strict spam filters may cause an over-reporting of spam rates within GPT's identifier reports, therefore the source of the data needs to be considered.
Key considerations
- Cross-Verification: Compare data from multiple postmaster tools to get a more accurate view of potential deliverability issues.
- Filter Assessment: Consider the settings and strictness of spam filters used by the systems providing the data, as these can influence reported spam rates.
- Domain Reputation: Pay close attention to overall IP Reputation as this may impact the data you see.
Expert view
Expert from Email Geeks clarifies that after reviewing extensive data, she does not see an actual rate for identifiers, just a dash.
11 Nov 2023 - Email Geeks
Expert view
Expert from Email Geeks states that she's currently seeing subdomains in both v1 and v2 while preparing a report.
5 Apr 2022 - Email Geeks
What the documentation says
4 technical articles
Documentation from Google, Microsoft, SparkPost and Yahoo highlights that spam rate identifiers in postmaster tools and related systems track spam complaints, but the availability and consistency of the data can be affected by various factors. These factors include data processing delays, privacy thresholds, incomplete user reporting, discrepancies in feedback loop participation, and incomplete registration with ISPs.
Key findings
- Identifier Usage: Postmaster Tools identifiers track spam complaints for specific campaigns.
- Data Availability: Spam rate data may not always be available due to processing delays or privacy thresholds.
- Incomplete Reporting: Data inconsistencies may arise due to incomplete user reporting of spam.
- Feedback Loop Discrepancies: Discrepancies in spam data can stem from users not utilizing the same reporting mechanisms as the data being analyzed.
- ISP Registration: Data discrepancies can arise if your feedback loop program does not register with all ISPs properly.
Key considerations
- Data Lag Awareness: Be aware of potential data processing delays when interpreting spam rate identifier information.
- Privacy Thresholds: Recognize that privacy thresholds may limit the availability of detailed spam rate data.
- Holistic View: Consider that not all users report spam, potentially skewing the data; combine with other data sources for a more complete picture.
- Feedback Loop Alignment: Check that all programs are aligning to the same ISP programs as data analysed.
Technical article
Documentation from Yahoo describes that feedback loops are a key aspect to being able to get spam data, which is needed for spam identifiers. Inconsistencies may arrise if a program does not register with all ISPs properly.
20 Jul 2023 - Yahoo
Technical article
Documentation from Microsoft shares that SNDS uses spam complaint data to generate reputation metrics. Data inconsistencies may arise because not all users report spam, or reports may be delayed. Spam identifiers may relate to this data
14 Apr 2023 - Microsoft
