How should I interpret discrepancies between Return Path/DeliveryIndex and Google Postmaster Tools data?

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.

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.

Email marketer from Reddit shares that he interprets discrepancies by prioritizing Google Postmaster Tools data for Gmail users, as it's direct from the source. He uses Return Path/DeliveryIndex for broader insights but understands it's a sample, not a complete picture.

Email marketer from StackOverflow explains that they try to correlate the data with campaign performance metrics like open rates and click-through rates. He says this can help understand if discrepancies are impacting user engagement.

Email marketer from GMass Blog says they look at Google Postmaster Tools to understand the sending reputation within the largest email client. Comparing this data alongside seed list deliverability tests will provide you with insights.

Marketer from Email Geeks shares that Gmail feedback loops do not show 100% of the complaints on the Postmaster site and they do not have a functional Feedback Loops system either.

Marketer from Email Geeks explains that if your list is primarily Gmail, then Return Path data isn't going to correlate with Google Postmaster Tools. A high spam-complaint rate via Return Path is likely based on a small, statistically insignificant subset of subscribers. Deliveryindex doesn't provide complaint/spam report indicators. He continues that if open rates at ISPs are within 2-3% of each other, you likely don't have a problem at a specific ISP.

Email marketer from ReturnPath mentions that deliverability is complicated. Use a mixture of data sources and third party tools in order to keep an eye on deliverability issues.

Email marketer from SparkPost Blog responds that DeliveryIndex (powered by SparkPost) focuses on deliverability metrics like inbox placement and spam filtering. Discrepancies can arise because DeliveryIndex data is based on seed lists and algorithms, while Google Postmaster Tools reflects actual user engagement with your emails.

Email marketer from Litmus Blog shares that differences in the data happen from the fact different data sources are focused on different metrics. Each platform's methodology and focus impact reported data and therefore, should be considered when comparing it.

Email marketer from EmailGeeks Forum states that he focuses on trends rather than absolute numbers. He uses all data points to understand changes, and if there is a large descrepency he trusts Google data the most, but validates deliverability by looking at replies.

Marketer from Email Geeks asks if the spam reporting at Returnpath is spam complaints or spam placement percentage, as those are two different things and comparing such data will not correlate. He continues that If your mails are in the spam folder, then you won't see that much of spam complaints.

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.

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.

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.

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.

Documentation from RFC Standards explains that Feedback Loops (FBLs) provide data about spam complaints from users. Different FBL implementations, like Gmail's, may have varying levels of accuracy and completeness, leading to discrepancies when compared with other data sources.

Documentation from Microsoft explains that they provide data about your sender reputation and spam complaint rates from Microsoft users. Discrepancies can occur if you're comparing this data with platforms that track Gmail or other email providers.