Summary
Interpreting discrepancies between Return Path/DeliveryIndex and Google Postmaster Tools (GPT) requires understanding the differing methodologies and data sources. Return Path/DeliveryIndex use panel data, seed testing, and algorithms, providing insights into inbox placement based on a sample of users, while GPT offers aggregated, anonymized data directly from Gmail users. Differences in FBL implementations and platform-specific data further contribute to inconsistencies. Experts recommend prioritizing GPT data for Gmail users when assessing issues affecting that audience, using Return Path/DeliveryIndex for broader directional insights. Focus on trend analysis rather than absolute numbers and validate data by correlating with campaign metrics like open rates and CTR. Comprehending each platform's limitations and biases, checking sender reputation, and leveraging multiple data sources for a holistic assessment is crucial for effective deliverability management.
Key findings
- Differing Methodologies: Return Path/DeliveryIndex rely on panel data and seed lists, while GPT uses aggregated Gmail data.
- Data Source Variety: Variations arise from different feedback loops, platform-specific data (Microsoft), and sampling methods.
- GPT Prioritization for Gmail: Prioritize Google Postmaster Tools for assessing Gmail deliverability, as it uses direct Gmail data.
- Trend Over Absolute Value: Focus on identifying trends and significant changes rather than relying solely on absolute numbers.
- Importance of Context: Understanding each platform’s methodology, metric focus, and biases is key for accurate interpretation.
Key considerations
- Sample Size and Representation: Recognize that Return Path/DeliveryIndex data represents a sample and may not reflect the entire audience.
- Correlate with Campaign Metrics: Validate deliverability data by correlating with campaign performance metrics like open rates and CTR.
- Holistic Assessment Approach: Leverage multiple data sources and tools (e.g., MXToolbox for blacklists, seed list testing) for a comprehensive view.
- Understand Data Biases: Acknowledge and account for the inherent biases and limitations of each data source to make informed decisions.
- Gmail Feedback Loop Limitations: Be aware that Gmail feedback loops may not show 100% of user complaints.
What email marketers say
12 marketer opinions
Discrepancies between Return Path/DeliveryIndex and Google Postmaster Tools (GPT) data arise from differing methodologies and data sources. Return Path/DeliveryIndex rely on panel data, seed testing, and algorithms, providing insights into inbox placement and spam filtering based on a sample of users. GPT offers aggregated data directly from Gmail users. Prioritize GPT data for Gmail users, and use Return Path/DeliveryIndex for broader, directional insights, focusing on trends rather than absolute numbers. Correlate this data with campaign performance metrics like open rates and click-through rates to understand the overall impact on user engagement. Understanding the strengths and limitations of each data source is crucial for informed decision-making.
Key opinions
- Data Source Differences: Return Path/DeliveryIndex use panel data and seed testing, while GPT uses direct Gmail user data.
- GPT Priority: GPT data is generally prioritized for Gmail users due to its direct source.
- Trend Analysis: Focus on trends and significant changes rather than absolute numbers across all platforms.
- Correlation with Metrics: Correlate data with campaign performance metrics (open rates, CTR) to gauge user engagement impact.
- Different Metrics: Differences in the data can happen because different data sources are focused on different metrics.
Key considerations
- Methodology Understanding: Understand the data collection methodologies of each platform to interpret data accurately.
- Sampling Bias: Recognize that Return Path/DeliveryIndex data represents a sample and may not reflect the entire user base.
- Metric Focus: Consider the metrics each platform prioritizes and how they align with your overall goals.
- Multiple Data Sources: Use a combination of data sources and third-party tools to monitor and manage deliverability issues effectively.
- Reputation: Consider the sending reputation of the company in the email client.
Marketer view
Email marketer from Validity Blog shares that Return Path data, now part of Validity, is based on a network of consumer inboxes and provides insights into inbox placement and spam complaints. Comparing this with Google Postmaster Tools requires considering that Return Path represents a sample of your audience, not the entire Gmail user base.
20 Nov 2024 - Validity Blog
Marketer view
Email marketer from Mailjet Blog explains that discrepancies can arise due to different data collection methodologies. Return Path/DeliveryIndex rely on panel data and seed testing, while Google Postmaster Tools provides data directly from Gmail users. Comparing these requires understanding their respective strengths and limitations.
26 Jun 2022 - Mailjet Blog
What the experts say
2 expert opinions
Experts emphasize understanding the data sources and methodologies behind different feedback loops and deliverability tools. Discrepancies between platforms like Return Path/DeliveryIndex and Google Postmaster Tools are common due to variations in metrics and data collection. Focus on identifying trends and significant changes rather than relying on absolute numbers. Crucially, comprehending the biases and limitations of each data source allows for more informed decisions regarding email deliverability strategies.
Key opinions
- Methodological Differences: Different feedback loops and platforms use varying metrics and methodologies.
- Trend Focus: Prioritize identifying trends and significant changes over absolute numerical values.
- Data Source Understanding: Comprehend the origin, biases, and limitations of each data source used.
Key considerations
- Validate Deliverability: Check bounce rates and user engagement metrics to validate deliverability assessments.
- Informed Decisions: Use an understanding of data source limitations to make informed decisions about email strategies.
Expert view
Expert from Word to the Wise explains that you have to understand the data sources for the data you are using. If you understand where the data comes from you'll understand the biases and limitations for that data set and be able to make informed decisions.
8 Jan 2023 - Word to the Wise
Expert view
Expert from Spam Resource explains that different feedback loops use different metrics and methodologies, so discrepancies are common. He suggests focusing on trends and significant changes rather than absolute numbers, and validates deliverability by checking bounce rates and user engagement metrics.
1 Jul 2022 - Spam Resource
What the documentation says
4 technical articles
Documentation sources indicate discrepancies between deliverability data platforms like Google Postmaster Tools (GPT), Microsoft SNDS, and third-party providers stem from variations in data collection, scope, and methodology. GPT offers aggregated, anonymized data on Gmail traffic, while Microsoft provides data specific to its users. RFC Standards clarify Feedback Loops (FBLs) report spam complaints, but implementation accuracy varies. A comprehensive assessment necessitates utilizing a mix of tools, like MXToolbox, to monitor email health aspects beyond spam complaints, such as blacklists and DNS settings.
Key findings
- Data Aggregation: GPT provides aggregated and anonymized data about email traffic.
- Platform-Specific Data: Microsoft provides sender reputation and spam complaint data specifically from Microsoft users.
- FBL Variability: Feedback Loop implementations vary in accuracy and completeness.
- Sampling Differences: Discrepancies can occur if comparing data from sources with different sampling methods.
Key considerations
- Scope of Data: Acknowledge that data sources might track only a subset of recipients.
- Holistic Assessment: Use a mix of tools to evaluate email health, including blacklists, DNS settings, and mail server configurations.
Technical article
Documentation from MXToolbox states that to test your email health you can check blacklists, DNS settings, and mail server configuration. Use a mixture of these tools in order to decide what may need attention for your email health.
20 May 2024 - MXToolbox
Technical article
Documentation from Google Postmaster Tools Help specifies that GPT provides aggregated and anonymized data about your email traffic. Discrepancies can occur if you're comparing it with data from sources that use different sampling methods or track only a subset of your recipients.
6 Feb 2022 - Google Postmaster Tools Help
Do Google Annotations impact email deliverability or inbox placement?
How accurate is SNDS and Google Postmaster Tools reputation data?
How accurate is the spam data shown in the new Google Postmaster Tools and how can I get data to appear?
How can I accurately monitor complaint rates for email marketing using Google Postmaster Tools, Yahoo FBL, and my ESP?
How do I interpret 'Rejected' errors in Gmail Postmaster Tools?
How do Sender Score and Google Postmaster Tools differ in measuring email sender reputation, and when should each be used?
