Summary
Many email marketers are puzzled by high open rates that do not translate into meaningful engagement, such as clicks or conversions. This discrepancy is a common challenge in modern email marketing, especially with the widespread adoption of privacy-enhancing features by major mailbox providers. While a high open rate might traditionally suggest success, it can often be misleading, masking underlying issues or simply reflecting automated interactions rather than genuine subscriber interest. Understanding the causes of this phenomenon is crucial for accurate performance assessment and effective strategy adjustments.
Key findings
- Inflated opens: High open rates, particularly from Gmail and GSuite (at 65% in some cases), are frequently attributed to pre-fetching or bot activity rather than direct human interaction. These automated opens skew performance metrics.
- Low engagement: A significantly low click-through rate (CTR), such as 0.65%, is a strong indicator of poor engagement, despite any inflated open rates. This suggests that recipients aren't interacting with the content.
- Data reliability: Email open rates have become less reliable due to privacy features like Apple Mail Privacy Protection (MPP) and pre-fetching by mailbox providers. These technologies automatically open emails to enhance user experience or scan content.
- List hygiene nuances: While a low bounce rate (e.g., 0.3%) indicates a healthy list regarding deliverability, some verification tools may report a higher percentage of invalid emails (e.g., 10%) without necessarily reflecting a genuine deliverability issue.
Key considerations
- Verify engagement: Shift your focus beyond open rates to actual user actions, such as clicks, conversions, and website visits. These provide a more accurate picture of how engaged your audience truly is. You can learn more about why email clicks decline despite high open rates.
- Identify bot activity: Analyze the time difference between email delivery, the reported open, and any subsequent clicks to identify automated interactions. A very short time gap can indicate non-human activity.
- Data granularity: If your ESP allows (like Klaviyo), explore API access to differentiate between human and bot-driven opens. This can help segment your data more accurately.
- Segmentation: Improve your segmentation strategies based on genuine engagement metrics (e.g., past purchases, website activity, or previous clicks) to target active users effectively. For details on how to explain poor performance despite good open rates, see how to explain poor email performance.
- Focus on what matters: As noted by VerticalResponse, open rates are now unreliable, and click-through rates (CTR) are a more accurate measure of engagement. Prioritize optimizing for clicks. Find out why open rates are dying.
What email marketers say
Email marketers often grapple with the paradox of high open rates that don't align with actual engagement. Many agree that open rates are increasingly unreliable due to privacy changes and pre-fetching technologies. The consensus among marketers is to look beyond this metric and concentrate on more concrete indicators of subscriber interest, such as clicks, website visits, and purchases. They highlight that inflated open rates can be a 'new normal' for campaigns, especially those with a high proportion of Gmail or GSuite users.
Key opinions
- Misleading metrics: Email open rates are often considered a less reliable metric for true engagement due to the impact of privacy features and mail client pre-fetching.
- Focus on clicks: Click-through rates (CTR) and other downstream engagement metrics are far more indicative of genuine interest and content resonance than opens alone. High open rates indicate subscriber value.
- Automated opens: High open rates from providers like Gmail are frequently attributed to their systems pre-fetching emails based on perceived user likelihood to open them, not actual user interaction.
- List hygiene limits: While email validation tools can identify invalid addresses, they might not effectively flag or prevent bot-like activities that still result in a 100% delivery rate.
- New normal: Open rates in the 50-60% range, even with low clicks, are now considered normal for many accounts due to the combined effects of Apple MPP and Gmail pre-fetching.
Key considerations
- Segment by engagement: Prioritize building audience segments based on actual engagement behaviors, such as website activity, past purchases, or verified email clicks, to target active subscribers. This can help with declining open rates for political campaigns, for example, even with strong engagement.
- Analyze click behavior: Investigate users who click every link in an email, as this behavior can sometimes signal bot activity rather than genuine interest. This applies to improving deliverability too.
- Leverage ESP data: Utilize your ESP's features or API to gain deeper insights into open events, differentiating between human and automated interactions where possible.
- Historical trend analysis: While not a perfect engagement metric, use your open rate as a trend line to detect significant drops that might signal underlying deliverability issues requiring investigation.
Marketer view
Marketer from Email Geeks suggests that marketers look at their ESP's real or human open rates, rather than total unique opens. This is because many opens are due to prefetch or pre-caching, like Apple's Mail Privacy Protection.
Marketer view
Marketer from Email Geeks suggests building an analysis to identify emails with strange behavior, particularly those that are opened and clicked within a very short time window. This approach helps in detecting automated interactions.
What the experts say
Email deliverability experts generally concur that a high open rate, while seemingly positive, is an increasingly inaccurate indicator of true engagement due to automated pre-fetching and privacy features. They emphasize that while low bounce rates are crucial for list health, other metrics must be examined to pinpoint genuine human interaction. Experts advise a deep dive into data beyond just opens, focusing on behavioral patterns that differentiate between real subscriber activity and non-human interactions (NHI). They also highlight the limitations of traditional list hygiene tools in detecting sophisticated bot activities from major mailbox providers.
Key opinions
- Prefetching/caching: Many reported opens, particularly from Gmail, are likely due to automated prefetching or pre-caching by mail clients, not direct human engagement.
- Garbage metric: Open rates are widely considered an unreliable metric for true engagement. However, sudden downward trends can still indicate underlying delivery issues.
- List hygiene nuances: While essential for removing invalid addresses, traditional list scrubbing may not effectively address bot-like activity, especially for major providers where such accounts can still show 100% delivery. Low open rates signal poor reputation.
- Bounce rate indicates health: A very low bounce rate (e.g., 0.3%) typically signifies a healthy list. This makes high invalid email reports from third-party tools (like 10%) suspicious if not correlated with bounces.
- Time-based analysis: Analyzing the time difference between email delivery, the reported open, and any subsequent clicks is a robust method to detect automated engagement and non-human interactions.
Key considerations
- Identify NHI: Implement advanced analysis to identify non-human interactions by closely examining timing patterns and click behaviors within your email campaigns. This will reveal if all-image emails truly have reliable open rates.
- API data analysis: If using an ESP like Klaviyo, leverage their API to access granular data that can help distinguish between automated (MPP) and genuine human opens.
- Question suspicious tools: Be cautious of email verification tools that report a high percentage of invalid emails (e.g., 10%) when your actual bounce rates are consistently very low. This contradiction suggests further investigation is needed. You may need to explain poor email performance.
- Historical context: Examine historical data to determine if the pattern of high open rates with low engagement is a new trend or a long-standing characteristic of your email program. This context can help identify root causes.
Expert view
Expert from Email Geeks suggests that if your ESP provides the functionality, marketers should prioritize checking 'real' or 'human' open rates rather than total unique opens. They explain that a significant portion of opens are often due to prefetch or pre-caching scenarios, such as Apple's Mail Privacy Protection (MPP).
Expert view
Expert from Email Geeks explains that while Google is relatively easy to validate via SMTP, Yahoo does not permit it. They highlight that accounts exhibiting bot-like activities frequently show a 100% delivery rate, indicating that validation alone will not solve this particular problem.
What the documentation says
Official documentation and industry guides increasingly acknowledge the declining reliability of email open rates as a standalone performance metric. This shift is primarily driven by the introduction of privacy-enhancing features by major email clients and the prevalence of automated pre-fetching technologies. The documentation emphasizes the importance of moving beyond simple open counts and adopting a more holistic approach to measuring engagement. This involves focusing on metrics that truly reflect subscriber interaction and content value, thereby ensuring more accurate campaign performance assessments.
Key findings
- Open rate unreliability: Privacy changes have made open rates unreliable, positioning click-through rates (CTR) as a more accurate measure of email engagement.
- Privacy protection: Features like Apple Mail Privacy Protection can automatically open emails, inflating reported open rates without actual user interaction, as explained by Digital Culture Network.
- Sender reputation impact: Despite high reported opens, low actual engagement can signal to mailbox providers that users don't want the emails. This can negatively impact sender reputation, potentially leading to future blocklist issues.
- Traditional indicators: Historically, high open rates suggested compelling subject lines and a strong sender reputation, indicating emails were well-received.
- Transactional email high opens: Transactional emails consistently show higher open rates because they contain information that recipients need and tend to view immediately or revisit.
Key considerations
- Prioritize CTR: Focus on optimizing and tracking click-through rates as a primary key performance indicator (KPI) for email campaign success, reflecting genuine interest. Learn more about declining clicks and conversions.
- Beyond open rates: Evaluate overall campaign success using a broader set of metrics. These include conversions, website activity, and unsubscribe rates, to gain a more comprehensive understanding of performance. This will help address increasing open rates.
- Content relevance: Ensure that your email content and subject lines are highly relevant and engaging to your audience. This encourages genuine clicks and active interaction rather than just an open.
- Audience segmentation: Refine your audience segmentation strategies to send targeted content that resonates with specific user interests. This approach can lead to significantly higher engagement rates.
Technical article
Documentation from VerticalResponse explains that open rates have become unreliable metrics due to recent privacy changes. They suggest that click-through rates (CTR) now provide a more accurate measure of email engagement, reflecting genuine subscriber interest and interaction.
Technical article
Documentation from Digital Culture Network clarifies that the primary effect of Apple's latest privacy updates is a decrease in the accuracy of email open rates. It is highly probable that your average reported open rate will increase due to these changes.
Related resources
15 resources
Related pages
Why do all-image emails have higher open rates and are open rates a reliable KPI?
Why are email open rates declining for political campaigns acquired through Facebook ads despite strong engagement?
Why are my email open rates low and how can I improve deliverability?
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How do I explain poor email performance despite a good open rate?
Why are open rates increasing and what does it mean for email marketing analysis?
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Why are email clicks declining despite high open rates?
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