What are "machine opens" and why are they important to consider?

Machine opens are automated interactions with your emails, such as those by security scanners or privacy proxies like Apple Mail Privacy Protection. They are important because they can inflate your open rates, making it difficult to accurately assess true human engagement and potentially leading to incorrect suppression decisions.

Do machine opens hurt my sender reputation?

Not directly. In fact, if an email generates a machine open, it generally means it reached the inbox (or at least a scanning system). For many inbox providers, successful delivery, even if automated, is a positive signal. The risk comes from continued sending to genuinely unengaged users who might eventually mark your emails as spam.

How can I distinguish between human and machine opens?

It's challenging to perfectly distinguish. Focus on combining open data with other engagement metrics like clicks, website activity originating from the email, or replies. If an email shows an open but no other human interaction, it's more likely a machine open.

Should I suppress contacts who only register machine opens?

Blanket suppression of contacts based solely on machine opens is generally not recommended. It can lead to losing legitimate subscribers, especially Apple Mail users. Instead, consider a nuanced approach: reduce frequency, send re-engagement campaigns, and prioritize suppression for contacts who show no engagement (human or machine) over a longer period.

What are the best metrics to focus on when rebuilding reputation?

When rebuilding reputation, focus on metrics that indicate strong human engagement: click-through rates, reply rates, forwarding rates, and importantly, low spam complaint rates. Successful inbox delivery and positive interactions are key signals for ISPs.

How should I handle machine opens when rebuilding IP/Domain reputation and implementing a suppression approach? - Sender reputation - Email deliverability - Knowledge base

Rebuilding IP and domain reputation is a delicate process that demands careful attention to engagement signals. A common challenge arises when considering "machine opens," which are automated interactions with your emails, often indistinguishable from genuine human engagement at first glance.

These automated opens, originating from security scanners, email proxies, or other non-human interactions (NHI), can complicate your data. While they might appear as positive engagement, incorrectly interpreting them can lead to flawed suppression strategies, potentially impacting your deliverability efforts.

My goal is to outline a nuanced approach to managing machine opens, ensuring your suppression policies support, rather than hinder, your efforts to restore or build a strong sender reputation.

Understanding machine opens

Machine opens, also referred to as "non-human interaction" (NHI) image loads, are essentially instances where an email's tracking pixel is loaded by an automated system rather than a human recipient. These can stem from a variety of sources, including corporate security scanners that pre-scan incoming emails for malicious content, or privacy-enhancing features like Apple Mail Privacy Protection (MPP).

It's crucial to differentiate these from traditional human opens. While a human open indicates genuine recipient interest, a machine open primarily confirms that the email reached the inbox and was processed by some automated system. Misinterpreting machine opens as direct human engagement can inflate your perceived open rates, masking deeper issues with actual recipient engagement.

Many email security solutions pre-fetch images within emails before they even hit the user's inbox. This pre-fetching often registers as an "open," even if the recipient never sees or interacts with the email. Similarly, Apple's Mail Privacy Protection proxies all images, making every email appear "opened" regardless of user interaction. Suppressing recipients purely based on these NHI image loads can inadvertently remove legitimate and valuable subscribers from your list.

Apple MPP versus Gmail proxy opens

Some distinguish between

Apple MPP and

Gmail proxy opens. While

Apple MPP proactively opens all emails regardless of user interaction,

Gmail's proxy opens are often tied to emails that have already landed in the inbox due to user behavior. Filtering out

Apple MPP data might be a consideration if your audience predominantly uses

Apple devices, but be cautious not to discard potentially engaged users.

Impact on IP and domain reputation

When rebuilding reputation, inbox providers heavily weigh recipient engagement. Metrics like clicks, replies, and emails moved from spam to inbox are strong positive signals. Conversely, a high volume of emails going to the spam folder or generating complaints significantly harms your IP and domain reputation, potentially leading to a blocklist (or blacklist) status.

The presence of machine opens means your email was likely delivered to the inbox, at least to the initial scanning system. For providers like

Google, emails reaching the inbox, even if opened by a machine, can contribute positively to your sender reputation, assuming they don't subsequently get marked as spam or result in unsubscriptions. The real risk lies in sending to contacts who are truly unengaged, regardless of whether a machine opens their emails. You can find more information on how to improve your domain reputation in this article from SendLayer.

Therefore, while machine opens might not signify human interest, they often indicate deliverability. The challenge is in layering other engagement metrics on top of these automated signals to identify truly active users and those who are silently unengaged or may trigger spam traps. Prioritizing engagement beyond just opens is paramount.

Signal	Description	Impact on reputation
Clicks	Human interaction with links within the email.	Strong positive. Indicates interest.
Replies	Direct human response to your email.	Very strong positive. Highest form of engagement.
Forwards	Sharing your content with others.	Positive. Indicates value and organic spread.
Unsubscribes	Recipient opting out of receiving emails.	Neutral. Expected part of list hygiene. Better than complaints.
Spam complaints	Recipient marks email as spam.	Strong negative. Heavily damages reputation.
Bounces	Email is undeliverable to the recipient.	Negative. Indicates poor list quality.

Strategic suppression and engagement

To effectively manage machine opens, your suppression strategy should focus on genuine user interaction beyond mere image loads. Implement policies that prioritize explicit actions such as clicks, website visits originating from your emails, or direct replies.

For contacts who only show machine opens (non-human interaction), consider a multi-stage approach. Instead of immediate suppression, categorize them into a separate segment. You can then try "are you still there?" re-engagement campaigns or gradually reduce the frequency of emails sent to this group. This allows you to differentiate between genuinely inactive users and those whose engagement is masked by privacy features.

Identifying emails that consistently land in the bulk folder (spam) is critical for reputation recovery. Utilize feedback loops from major internet service providers (ISPs) and analyze your email deliverability reports. If a significant portion of your mail is being marked as spam, it's a clear signal to adjust your sending practices and suppress unengaged segments. For strategies on how to recover from such incidents, see articles like how to recover email domain and IP reputation after a spam incident.

The ultimate goal is to nurture active, engaged subscribers who consistently interact positively with your content. By focusing on true engagement and smart suppression, you can guide your IP and domain reputation back to health. This targeted approach helps avoid accidental blocklisting (or blacklisting) from sending to seemingly "opened" but truly unengaged recipients.

Risks of blanket machine open suppression

Could suppress legitimate, human readers using privacy tools. These users might still be valuable, but their opens are hidden.

Reduces overall list size unnecessarily, potentially impacting reach and future campaign performance.

Benefits of a nuanced approach

Allows you to retain potentially engaged users who utilize Apple Mail Privacy Protection or security scanners.

Focuses resources on truly engaged segments, improving overall return on investment and deliverability.

Long-term reputation management

Recovering and maintaining a strong sender reputation is an ongoing process, not a one-time fix. There's no universal threshold for when to sunset users (e.g., 180 versus 365 days of inactivity), as it highly depends on your specific business model and audience behavior. Some industries might see engagement drop off quickly, while others have longer cycles.

Continuously monitor your sender health using tools that provide insights into your IP and domain reputation. This includes observing bounce rates, complaint rates, and direct feedback from ISPs. Regular list hygiene, proactive re-engagement campaigns, and a keen eye on overall engagement metrics are essential. For guidance on monitoring and improving your domain reputation, an external resource like Understanding IP Reputation from

Trend Micro can be useful.

Ultimately, adapting your suppression approach based on a holistic view of engagement, beyond just opens, will ensure you build a robust and sustainable email program. Consistency and responsiveness to deliverability signals are key to avoiding future blocklisting (or blacklist) issues.

Example suppression logicpseudocode

IF (last_click_date > 365 days_ago) THEN KEEP
ELSE IF (last_open_date > 180 days_ago AND has_website_activity_from_email) THEN KEEP
ELSE IF (last_open_date > 90 days_ago AND !is_machine_open) THEN KEEP
ELSE IF (last_open_date > 60 days_ago AND is_machine_open AND !has_any_click) THEN REDUCE_FREQUENCY
ELSE SUPPRESS

Views from the trenches

Best practices

Prioritize clicks: Focus on click data over open data for true engagement, as clicks are a stronger signal of human interaction.

Analyze behavior: Deeply analyze user behavior beyond just opens, including website activity and purchase history, to identify valuable contacts.

Segment carefully: Create segments for machine-opened users and tailor re-engagement campaigns or sending frequency specifically for them.

Common pitfalls

Blanket suppression: Suppressing all machine opens can remove legitimate subscribers, especially those using privacy-preserving mail services like Apple MPP.

Ignoring context: Not understanding the context of machine opens (e.g., security scans versus privacy proxies) leads to inaccurate deliverability assessments.

Solely relying on opens: Treating opens as the sole engagement metric is misleading, especially with the prevalence of automated pre-fetching.

Expert tips

Focus on inbox delivery: Sending to addresses that demonstrably reach the inbox (even if machine opened) can improve reputation, as it reduces mail going to the bulk folder.

Nuanced reporting: Develop internal reporting that clearly distinguishes between human and non-human interactions to make informed decisions.

Audience specific: Tailor your suppression policies to your specific audience and business context, as there is no single "one-size-fits-all" approach.

Expert view

Expert from Email Geeks says suppressing mail categorized by non-human image loads is generally not a good idea, as it would incorrectly exclude many Apple users.

October 20, 2024 - Email Geeks

Expert view

Expert from Email Geeks says that for Google, addresses showing machine opens are those known to reach the inbox, and mailing to them can improve reputation if it decreases mail ending up in the bulk folder.

October 20, 2024 - Email Geeks

Moving forward with confidence

Navigating machine opens while rebuilding IP and domain reputation requires a thoughtful, data-driven strategy. Blanket suppression based solely on these automated signals risks discarding valuable contacts and can impede your recovery efforts.

Instead, prioritize genuine human engagement signals like clicks and website activity. Employ a nuanced suppression policy that strategically reduces frequency or re-engages segments that only show machine opens, rather than immediately removing them. This approach safeguards your sender reputation while maximizing long-term audience value.