Why do email providers make weird filtering decisions, and what are the assumptions behind them?
Matthew Whittaker
Co-founder & CTO, Suped
Published 2 Jul 2025
Updated 16 Aug 2025
8 min read
Email filtering can often feel like a black box, with messages sometimes landing in unexpected folders or disappearing entirely. It is a common experience for senders to grapple with decisions made by email providers that seem, at best, counterintuitive. These 'weird' filtering outcomes are not random; they stem from complex algorithms and a set of underlying assumptions that dictate how emails are evaluated and routed.
Understanding these mechanisms is crucial for anyone involved in email marketing or communication. While the primary goal of email filters is to protect users from unwanted mail, their methods can sometimes inadvertently block legitimate messages. The challenge lies in deciphering the logic behind these systems and adapting sending practices accordingly.
I've spent years observing how these systems operate and the impact their decisions have on deliverability. It's a continuous learning process, as providers frequently update their algorithms to combat evolving threats and user behaviors. Let's delve into why these filtering decisions occur and what assumptions drive them.
The complex world of email filtering
Email filtering is a multi-layered process designed to categorize incoming messages and route them appropriately, whether to the inbox, spam folder, or even to silently drop them. This process involves sophisticated systems that analyze numerous data points, ranging from sender reputation to message content. For a detailed overview of what email filtering entails, you can refer to Darktrace's explanation of email filtering.
The core of modern email filtering relies heavily on machine learning (ML) algorithms. These algorithms learn from vast datasets of emails, identifying patterns associated with spam, phishing, and other malicious content. While incredibly powerful, their inherent 'opacity' can make it difficult to pinpoint exactly why a specific email was filtered in a particular way. This characteristic of ML algorithms is discussed in academic research on understanding opacity in machine learning.
These filters assess various signals. These include technical authentication records like SPF, DKIM, and DMARC, content analysis, sender reputation, and user engagement. When an email gets blocked or sent to spam, it's usually due to a combination of these factors triggering a negative score within the system. Understanding how complex inbox filters are can help shed light on these intricate processes.
Technique
Description
Impact on deliverability
Content scanning
Analyzes keywords, phrases, and formatting for spam characteristics.
Poorly crafted content can trigger spam filters.
Sender reputation
Evaluates sender's history, IP, and domain health.
A low reputation can lead to inbox placement issues.
Authentication checks
Verifies SPF, DKIM, and DMARC records to prevent spoofing.
Failure to authenticate often results in messages being rejected.
User engagement
Monitors recipient interactions such as opens and replies.
Low engagement can signal unwanted mail, affecting future delivery.
Assumptions shaping filter decisions
Mailbox providers often operate on assumptions about how users interact with email and what constitutes spam. One critical assumption is that if an email is not opened or interacted with, it's likely not important. This can lead to a 'halo effect' where even for highly engaged users, a general low engagement rate for a campaign can negatively impact delivery, leading their emails to spam.
Another assumption is that users will actively search their spam folders for legitimate mail or take the initiative to mark misclassified emails as not spam. However, most users are trained to believe the spam folder is exclusively for junk and rarely check it. They also may not know how to provide feedback to their email provider. This disconnect between provider assumption and user behavior is a significant source of frustration for senders.
User expectations
Users expect important emails, especially those they subscribe to or frequently interact with, to consistently land in their inbox.
Immediate access: Legitimate messages should appear directly in the primary inbox.
Spam folder purpose: The spam folder is for unwanted or malicious emails only.
Provider assumptions
Providers assume users will actively manage their inbox, including checking spam folders and providing feedback on misclassified emails.
User engagement metrics: Low overall engagement signals disinterest, even for active subscribers.
Feedback mechanisms: Users are expected to report spam or mark legitimate mail as not spam.
Providers like Yahoo or AOL and even Microsoft sometimes flag legitimate emails as spam due to these underlying assumptions about user behavior and content. This can be particularly frustrating when the same email is treated differently for different users, which can happen with providers like Yahoo.
The impact of filter anomalies
When filters make 'weird' decisions, the consequences for legitimate senders can be severe. Emails may be silently dropped, meaning they never reach the recipient's inbox or even the spam folder, making troubleshooting incredibly difficult. This can lead to missed opportunities, poor customer communication, and a damaged sender reputation. Understanding why emails go missing or get silently dropped is a critical step in diagnosing these issues.
Getting placed on a blocklist (or blacklist) is another significant consequence. Even if an email doesn't contain outright spam, certain patterns, content, or sending behaviors can trigger blocklist inclusion. Once on a blocklist, it can be challenging to get removed, impacting deliverability across many providers. A practical guide to understanding your email domain reputation is invaluable here.
The silent drop problem
One of the most insidious filtering decisions is the silent drop, where an email is accepted by the recipient's server but never delivered to their inbox or spam folder. This often occurs when a sender's reputation is severely compromised or when the email triggers highly sensitive internal filters. Unlike a bounce, there's no explicit notification, leaving senders unaware of the problem. This can be particularly prevalent with Microsoft's email filters, where internal organizational systems can further complicate deliverability. Issues with Microsoft 365 and Google Workspace DMARC are common.
The sheer volume of emails processed daily means that some legitimate messages inevitably get caught in the net. This isn't always malicious intent from providers but rather an unfortunate side effect of their broad efforts to protect users. Even established providers can face internal challenges that affect filtering. We have seen how Microsoft's email filters can affect inbox placement, which demonstrates the organizational complexity that can contribute to these issues.
Navigating the filtering landscape
To improve deliverability, senders must adopt a proactive and adaptive approach. This involves not only adhering to best practices but also continuously monitoring and analyzing email performance. Key strategies focus on improving your sender reputation and ensuring proper email authentication.
Maintain high sender reputation: Ensure low bounce rates, minimal spam complaints, and consistent engagement.
Implement strong email authentication: Set up SPF, DKIM, and DMARC correctly to prove your emails are legitimate. A simple guide to DMARC, SPF, and DKIM can help.
Segment audiences: Send relevant content to engaged subscribers to boost interaction metrics.
Monitor blocklists (blacklists): Regularly check if your IP or domain is listed on any common email blocklists using a blocklist checker.
Email authentication protocols are your first line of defense against being misidentified as spam. SPF (Sender Policy Framework), DKIM (DomainKeys Identified Mail), and DMARC (Domain-based Message Authentication, Reporting, and Conformance) help providers verify that an email truly originated from your domain. Proper configuration of these records is crucial. You can find DMARC record and policy examples to guide your setup.
Beyond technical setup, continuous monitoring of your email performance is non-negotiable. Tools like Google Postmaster Tools provide insights into your domain's reputation and deliverability issues with Gmail. Regular email deliverability tests can help identify problems early.
Views from the trenches
Best practices
Actively manage your sender reputation by monitoring engagement, bounce rates, and spam complaints.
Always implement and maintain strong email authentication protocols, including SPF, DKIM, and DMARC.
Regularly segment your email lists to ensure you are sending targeted content to engaged users, which boosts positive signals for filters.
Common pitfalls
Assuming users will check their spam folders for legitimate emails, leading to lost messages.
Believing that users will go through complicated feedback processes to report misclassified emails to providers.
Ignoring the collective engagement metrics of a campaign when assessing deliverability, even if individual users are highly active.
Expert tips
Be aware that filtering decisions can seem arbitrary, even to those deeply entrenched in email operations.
Remember that email providers prioritize spam reduction and security, which can sometimes impact legitimate senders.
Focus on consistent, high-quality sending practices as the most reliable way to navigate filter complexities.
Expert view
Expert from Email Geeks says that Microsoft, in particular, often struggles with consistent filtering, sometimes messing things up unexpectedly. It highlights the unpredictable nature of some provider systems.
2021-05-12 - Email Geeks
Marketer view
Marketer from Email Geeks says that every provider has the capability for filtering decisions to appear strange, even without outright errors, and that their underlying assumptions often lack clear reasoning.
2021-05-12 - Email Geeks
Moving forward with deliverability
The seemingly 'weird' filtering decisions made by email providers are a product of sophisticated, often opaque, systems and ingrained assumptions about user behavior and spam. While these systems aim to protect users, they can inadvertently create significant challenges for legitimate senders. Successfully navigating this landscape requires a deep understanding of these underlying principles.
By focusing on strong authentication, maintaining a stellar sender reputation, and continuously monitoring your email performance, you can significantly improve your chances of reaching the inbox. Adapting to the evolving rules and assumptions of email providers is not just about avoiding the spam folder; it's about ensuring your message effectively reaches your audience.
Ultimately, deliverability is a dynamic field that demands constant vigilance. As providers continue to refine their filters, senders must remain flexible and committed to best practices. This ensures that your important communications land where they belong, despite the inherent complexities of email filtering.
Yahoo or 
AOL and even 
Microsoft sometimes flag legitimate emails as spam due to these underlying assumptions about user behavior and content. This can be particularly frustrating when the same email is treated differently for different users, which can happen with providers like Yahoo.
Gmail. Regular email deliverability tests can help identify problems early.
