Why do email providers make weird filtering decisions, and what are the assumptions behind them?
Summary
What email marketers say10Marketer opinions
Email marketer from StackExchange shares that sending frequency and volume can influence filtering. Providers assume that sudden spikes in sending volume or excessively frequent emails are indicative of spam campaigns, leading to stricter filtering.
Email marketer from Email Marketing Forum shares that engagement metrics like open rates and click-through rates play a crucial role. Providers assume low engagement indicates irrelevant or unwanted content, resulting in emails being filtered into spam or promotions tabs.
Email marketer from MailNinja Blog explains that high complaint rates (users marking emails as spam) are a strong indicator of unwanted content. Providers assume that senders with high complaint rates are sending irrelevant or harmful emails, resulting in aggressive filtering.
Email marketer from EmailAnalytics.com explains that incomplete or misleading sender information (e.g., incorrect 'From' address or missing contact details) raises red flags. Providers assume that senders trying to hide their identity are more likely to be sending spam, resulting in stricter filtering.
Email marketer from Deliverability.com explains that the reputation of the sending IP address is a critical factor. Providers assume that IP addresses with a history of sending spam are more likely to continue doing so, leading to aggressive filtering.
Email marketer from EmailGeeks shares that poor list hygiene (e.g., sending to inactive or invalid addresses) negatively impacts sender reputation and deliverability. Providers assume that senders with poorly maintained lists are more likely to be sending spam, resulting in stricter filtering.
Marketer from Email Geeks shares their experience that every provider has the capability to make weird filtering decisions, even without errors, and their assumptions are often based on nothing. They explain that providers sometimes put part of the traffic into the spam folder even when a significant portion of recipients actively engage with the emails. They also point out the flawed assumption that users will search the spam folder or provide feedback to the provider.
Email marketer from Reddit explains that filtering decisions are heavily influenced by sender reputation. Providers assume that senders with poor reputation are more likely to send unwanted emails, leading to more aggressive filtering.
Marketer from Email Geeks explains users generally won't open trouble tickets with providers but instead complain to the sender, expecting them to resolve the issue. They also mention Microsoft's organizational issues, where even internal analysts may not have accurate data.
Email marketer from MarketingProfs explains that the content of emails is a significant factor. Providers assume that emails containing spam-like keywords, excessive links, or poor formatting are likely to be unwanted, leading to stricter filtering.
What the experts say2Expert opinions
Expert from Spam Resource shares insight into the 2011 Gmail spam filtering update and the algorithm they use. He mentions about Bayesian-trained algorithm learning senders that send authentic email that recipients want to see.
Expert from Word to the Wise explains that filtering algorithms are complex and influenced by user behavior. They share that providers assume users know how to report spam correctly, and that filtering is often about finding the 'least bad' email to deliver, rather than just blocking spam.
What the documentation says6Technical articles
Documentation from Validity (formerly ReturnPath) describes the use of feedback loops (FBLs) to monitor spam complaints. Providers assume that senders not actively monitoring and responding to FBLs are less concerned about sending unwanted emails, leading to continued filtering.
Documentation from Spamhaus explains that being listed on blocklists (e.g., Spamhaus Blocklist) can severely impact deliverability. Providers assume that IP addresses or domains listed on these blocklists are confirmed sources of spam, leading to immediate filtering.
Documentation from Google Postmaster Tools explains that user feedback, such as marking emails as spam or unsubscribing, directly impacts filtering decisions. Google assumes that negative user feedback indicates unwanted content, leading to lower deliverability.
Documentation from Microsoft Docs details that authentication protocols like SPF, DKIM, and DMARC are critical for establishing sender legitimacy. Microsoft assumes that emails lacking proper authentication are more likely to be spoofed or phishing attempts, resulting in stricter filtering.
Documentation from RFC-Editor explains that adherence to email standards outlined in RFC documents is essential for deliverability. Providers assume that emails violating these standards are likely to be poorly formatted or malicious, leading to filtering.
Documentation from DMARC.org describes that implementing a DMARC policy (especially with a 'reject' or 'quarantine' policy) provides clear instructions to providers on how to handle unauthenticated emails using your domain. Providers assume you want them to enforce this policy, leading to filtering of non-compliant emails.