Summary
The impact of specific email keywords on spam filters and unsubscribe rates is a nuanced topic in email deliverability. While some words are historically associated with spam, modern spam filters (also known as blocklists) are far more sophisticated, relying heavily on sender reputation, engagement metrics, and overall email context rather than isolated keywords. High unsubscribe rates are typically driven by recipient dissatisfaction or automated mail client actions, not direct keyword-triggered spam filters.
Key findings
- Keyword context: Modern spam filters evaluate keywords within the broader context of the email, rather than flagging individual words in isolation. Words like 'scam' or 'abuse' might not trigger a filter if the overall message is legitimate and the sender's reputation is strong.
- Reputation focus: Sender reputation, encompassing IP and domain reputation, is a far more critical factor in email deliverability than specific keywords. A strong sender reputation can often override the minor impact of a few potentially suspicious words. Understanding why emails go to spam involves looking beyond simple keyword lists.
- Unsubscribe drivers: Unsubscribe rates are primarily influenced by recipient engagement, content relevance, user expectations, and the email acquisition process. Spam filters generally do not cause unsubscribes directly. These are explicit actions taken by the recipient.
- Automated unsubs: In rare cases, automated systems (like security scanners) might trigger unsubscribe links. This is often mitigated by requiring a two-click unsubscribe process or by platforms that prevent automated unsubscribes from being processed.
- Holistic scoring: Email service providers (ESPs) and ISPs use complex algorithms that consider a multitude of factors, including sender authentication (SPF, DKIM, DMARC), email content, formatting, images, links, and recipient interaction history. Concentrating solely on avoiding 'spam words' can be misleading without addressing broader deliverability best practices.
Key considerations
- Content relevance: Ensure your email content is relevant and provides value to your audience. Irrelevant content, regardless of keywords, can lead to low engagement and higher unsubscribe rates.
- Audience expectations: Manage subscriber expectations from the start (during acquisition). If the email content deviates significantly from what subscribers signed up for, unsubscribes are likely.
- Email authentication: Prioritize proper SPF, DKIM, and DMARC setup. These foundational elements significantly impact your sender reputation and are far more influential than keyword choices.
- Monitoring engagement: Regularly monitor your engagement metrics, including opens, clicks, and unsubscribes. Analyze trends to understand what resonates with your audience and what might be causing disengagement.
- Unsubscribe process: Test your unsubscribe process to ensure it requires user confirmation, thereby preventing automated systems from inadvertently unsubscribing recipients. This also means making it easy and clear for users to opt out when they genuinely want to.
What email marketers say
Email marketers often express concern about specific keywords triggering spam filters. While many are aware that sender reputation plays a significant role, the fear of certain words still influences content strategy. Discussions frequently revolve around unexpected unsubscribe spikes, leading to questions about whether automated systems (like spam filters) might be responsible for user opt-outs, especially when direct user action seems unlikely.
Key opinions
- Keyword apprehension: Many marketers are cautious about using words traditionally labeled as 'spam trigger words', even if their overall email practices are legitimate. There's a persistent belief that these words alone can send emails to the junk folder.
- Reputation importance: A common sentiment among marketers is that sender reputation (IP and domain) outweighs the impact of individual keywords. A strong reputation, high sender score, and robust IP are seen as critical for inbox placement.
- Unsubscribe confusion: Some marketers find it perplexing when high unsubscribe rates occur shortly after a send, particularly from engaged audiences or specific domains, leading them to question if filters or automated systems are causing these unsubscribes rather than individual recipient actions. This is why it's important to understand how the List-Unsubscribe header affects deliverability.
- Automated unsubscribe mitigation: Marketers value features that require a two-click unsubscribe process or those designed to prevent spam filters from inadvertently unsubscribing users by clicking all links in an email. This is crucial for accurate reporting and list management.
- User experience focus: It's recognized that actual unsubscribes are driven by recipient actions based on their expectations, satisfaction with the content, and the overall copywriting. This underscores the importance of sending valuable and anticipated content to minimize unsubscribes, as highlighted by various deliverability guides.
Key considerations
- Review email content holistically: Instead of fixating on isolated keywords, review the entire email for signs of spamminess (e.g., excessive capitalization, poor formatting, irrelevant links). Even the word 'free' alone may not be an issue.
- Investigate unusual unsubscribe patterns: If you observe sudden, clustered unsubscribes from specific domains, investigate whether these are legitimate user actions or system-generated. This might involve looking at recipient domains or contacting your email service provider for more detailed logs.
- Test unsubscribe flow: Regularly test your own unsubscribe process to understand the user experience and verify that it requires a confirmation step, if desired, to prevent automated unsubscriptions.
- Align content with user expectations: Ensure your email content consistently meets the expectations set when subscribers opted in. Misalignment is a primary cause of legitimate unsubscribes.
Marketer from Email Geeks questions the impact of specific keywords on spam filters. They inquire if words like 'scam', 'abuse', and 'waste', when used together in an email, would lead to it being flagged as spam. This reflects a common concern among marketers about content-based spam triggers and how aggressively filters interpret certain terms. Despite the sophistication of modern filters, the perception of 'spam words' persists.
Marketer from Email Geeks shares an observation regarding a client's email performance. The client, despite having a high sender score (99) and a strong IP reputation, experienced a 5% unsubscribe rate from their most engaged audience. The email's content, which discussed medical fraud, sparked concern about whether content keywords might have played a role in the unexpected unsubscribes.
What the experts say
Experts in email deliverability consistently highlight that modern spam filtering is highly sophisticated, moving beyond simple keyword matching. They emphasize that sender reputation, user engagement, and email authentication (SPF, DKIM, DMARC) are far more influential factors than specific 'spam words'. Experts also clarify that unsubscribes are typically user-initiated actions, although automated systems or security scanners can sometimes inadvertently trigger unsubscribe links, leading to unexpected list attrition.
Key opinions
- Keyword secondary: Experts generally agree that while certain words might contribute to a spam score, they are not primary triggers in isolation. The overall email structure, sender reputation, and recipient engagement carry much more weight.
- Holistic scoring: Spam filters assess emails comprehensively, looking at numerous elements beyond just keywords. This includes links, images, HTML quality, authentication records, and sender history. This approach makes it difficult for senders to game the system by simply avoiding a list of words.
- Unsubscribe origination: Unsubscribes are almost always initiated by the recipient, after they have seen at least the subject line and pre-header. They are not direct outcomes of spam filtering, but rather a reflection of recipient sentiment and content relevance.
- Automated system impact: There's an acknowledgment that certain email systems (like security scanners or internal mail filters, e.g., in Office 365 environments) might interact with unsubscribe links automatically. This can lead to rapid, clustered unsubscribes that appear non-human initiated. This is a technical nuance for understanding your domain reputation.
- Multi-click unsubscribe: Implementing a two-click unsubscribe process (where a user clicks the link then confirms on a landing page) is recommended to prevent automated systems from accidentally unsubscribing users by crawling links. This strategy helps ensure that reported unsubscribes are genuine user actions, as discussed by deliverability experts.
Key considerations
- Prioritize reputation management: Focus on building and maintaining a strong sender reputation through consistent engagement, proper list hygiene, and robust authentication. This is more impactful than simply avoiding a list of 'spam words'.
- Analyze unsubscribe patterns: Investigate sudden or clustered unsubscribes. Determine if they are actual user actions, feedback loop hits, rejections, or automated system interactions. Identifying common factors among the domains generating these unsubs can provide insights.
- Implement confirmed unsubs: Ensure your unsubscribe process requires a second click or confirmation. This helps prevent unintentional unsubscriptions caused by automated link-crawling spam filters, providing more accurate unsubscribe data.
- Audit email practices: Regularly audit your email acquisition, content relevance, and sending frequency to ensure they align with subscriber expectations, reducing the likelihood of genuine unsubscribes. This also includes understanding and avoiding spam traps.
Expert from Email Geeks explains that using keywords like 'scam', 'abuse', or 'waste' will generally not trigger a spam filter on their own. However, they caution that if these words are combined with a 'very spammy email structure', the email might receive a slightly higher spam score. This scenario is considered an edge case, and senders should not be overly concerned unless they are involved in sending highly dubious content, such as payday loan spam.
Expert from Email Geeks clarifies that unsubscribes are rarely the result of spam filters. Instead, they are almost always a direct action taken by the recipient after they have viewed at least the email's subject line and pre-header. This means unsubscribe rates are primarily driven by factors such as user expectations, satisfaction with the content, the subscriber acquisition process, and the effectiveness of the email copywriting.
What the documentation says
Official documentation from major email service providers and industry bodies outlines a sophisticated approach to spam filtering. While content analysis is part of this, the emphasis is heavily placed on sender reputation, authentication protocols (SPF, DKIM, DMARC), and user engagement signals. Documentation often provides guidelines on what constitutes a good sending practice, which collectively aims to ensure legitimate emails reach the inbox while filtering out unwanted messages.
Key findings
- Multi-factor filtering: Documentation confirms that spam filters employ complex algorithms that consider hundreds of factors, not just keywords. These include IP/domain reputation, bounce rates, spam complaint rates, email authentication, and overall email structure.
- Content analysis parameters: Content is analyzed for suspicious keywords, phrasing, excessive punctuation, image-to-text ratio, and malicious links. However, these are weighed against other signals, meaning a few keywords alone are unlikely to be the sole cause of blocking.
- Sender authentication importance: Strong email authentication (SPF, DKIM, DMARC) is consistently highlighted as fundamental. Failing authentication can lead to emails being flagged as spam, regardless of content, as outlined in new sender requirements.
- Unsubscribe best practices: Documentation encourages clear, easy-to-use unsubscribe mechanisms, often supporting the List-Unsubscribe header. It also subtly acknowledges that automated systems may interact with links, necessitating careful implementation to avoid false unsubscribes. Mailmodo's guide on spam words touches on this by discussing link impact.
Key considerations
- Adhere to sending guidelines: Regularly review and comply with the sending guidelines provided by major ISPs (e.g., Google, Microsoft, Yahoo) as these offer the most authoritative insights into their filtering mechanisms.
- Implement robust authentication: Ensure your SPF, DKIM, and DMARC records are correctly configured and monitored. These are foundational for establishing trust and positive sender reputation.
- Monitor delivery data: Utilize Postmaster Tools (e.g., Google Postmaster Tools) to gain insights into your sending reputation, spam rates, and delivery errors, as this data is directly from the ISP.
- Optimize unsubscribe flow: Ensure your unsubscribe process is clearly visible, functional, and ideally supports a two-step confirmation to minimize accidental opt-outs by automated systems.
Documentation from Kinsta explains that emails can end up in spam folders due to a variety of factors, including content issues like suspicious keywords, but also technical problems such as poor sender reputation, lack of authentication, or even broken HTML code. It highlights that spam filtering is not solely about specific words. A holistic evaluation of the email's characteristics and sender's behavior determines its spam score.
Documentation from Mailmodo clarifies the common belief about 'spam words' by stating that while links with 'spammy' words can affect deliverability, they do not automatically trigger spam filters in isolation. The impact of links is part of a broader assessment of the email's overall quality and intent. Filters examine context, sender reputation, and other indicators to make a comprehensive decision.
