Understanding Email Open Rates in Modern Campaigns

Email open rates still appear in every campaign report, but what they tell you has changed. Privacy features, image proxying, and automated opens mean email open rates no longer work as a clean measure of interest or engagement. You can still use them, but only if you understand their limits and read them in context.  

This guide explains what email open rates mean today, why they became less reliable, and how you should use them in modern campaigns. 

What an email open rate measures  

To understand modern open rates, it helps to look at how email opens are tracked.  

Email open rates measure the percentage of delivered emails that register an open. Most email platforms track this using a small invisible tracking pixel.  

An open is recorded when:  

  • The tracking pixel loads  
  • Images are enabled in the email client  
This method never measured human behaviour perfectly. It simply detected image loading. That limitation matters much more now than it did a few years ago.

Email Open Rate Timeline Infographic

Why email open rates are less reliable than they used to be  

A common question we hear is: are email open rates accurate anymore?  

Apple Mail Privacy Protection (MPP)  

Apple introduced Mail Privacy Protection in iOS 15. When enabled, Apple:  

  • Pre-loads email images automatically  
  • Loads the tracking pixel whether or not the user opens the email  
This behaviour causes Apple MPP open rate inflation, where opens are recorded even when no human action takes place and makes several data points unreliable:  

  • Time of open  
  • Location data  
  • Device-based behaviour  
In many B2C lists, Apple Mail often represents a large share of observed opens (commonly around 50% in industry datasets), which can skew averages.  

Gmail image proxying  

Gmail uses image caching and proxying:  

  • Images load through Google’s servers  
  • Pixel loads can be delayed or batched  
  • “Real-time” opens become less accurate  
The result: opens no longer represent a clear moment when a person viewed your email.

Segmenting Apple Mail Users Affected by MPP  

One practical way to reduce confusion in reporting is to separate Apple Mail users affected by Mail Privacy Protection.  

A common approach is to create a segment such as:  

  • “Apple Mail (MPP likely)”  
For this group:  

  • Treat open rates as estimated, not factual  
  • Avoid using opens for automation triggers  
  • Rely more heavily on clicks and onsite behaviour  
This does not remove Apple users from reporting. It simply applies the correct level of caution to how their data is interpreted.  

Segmentation does not fix open rate inflation, but it does prevent inflated data from distorting wider performance analysis.

How email open rates should be explained to clients  

If we explain this to a client, the framing matters.  

  • Email open rates still have value, but only as a directional signal  
  • They do not prove interest, attention, or engagement  
  • Privacy features inflate opens, especially on Apple Mail  
  • Open rates should always sit alongside clicks, conversions, and revenue  
Treat open rates as context, not evidence. 

What email open rates are still useful for  

Despite their limits, email open rates still help in specific situations.  

They work well for:  

  • Tracking trends over time  
  • Comparing campaign A vs campaign B  
  • Spotting sudden spikes or drops  
  • Identifying possible deliverability issues  
  • A/B testing subject lines within the same audience segment  
When you compare like-for-like campaigns, open rates can still highlight relative performance.  

The engagement timeline below shows this in practice, making it easier to see trends, spikes, and drops in activity after a campaign is sent.

Email Engagement Timeline

What email open rates are no longer good for  

Open rates should not drive decisions that rely on individual behaviour or precise timing.  

They perform poorly for:  

  • Tracking individual user engagement  
  • Send-time optimisation based only on opens  
  • Location-based insights  
  • Triggering automations based purely on opens  
Open-based automation now introduces risk, especially on Apple-heavy lists.

How to Adapt Automations Away from Open-Based Triggers  

Open-triggered automations now carry real risk. Privacy features like Apple Mail Privacy Protection can trigger opens automatically, even when no human action has taken place.  

This can cause:  

  • Premature follow-ups  
  • Incorrect lead scoring  
  • Broken nurture flows  
In modern campaigns, automation should trigger on observable behaviour, not estimated signals.  

Replace open-based triggers with:  

  • Clicks on specific links  
  • Product views  
  • Add-to-cart events  
  • Purchases  
  • Onsite actions or events  
These signals reflect intent far more accurately than opens and remain stable across email clients.

Open-based triggers are not wrong; they are just unreliable. Using them as a primary decision point now introduces noise into automation logic. 

Factors that still influence email open rates  

Even with privacy changes, some fundamentals still matter.  

List quality  

  • Permission-based lists outperform purchased lists by a large margin  
  • Old or disengaged contacts drag averages down  
  • Regular list cleaning improves all metrics, not just opens  

Subject line relevance  

  • Clear subject lines outperform clever ones  
  • Personalisation works when it reflects real context  
  • Overuse of urgency or gimmicks reduces trust over time  
Examples of urgency that can lift opens short-term:  

  • “Last chance”  
  • “Don’t miss out”  
Used too often, these lose impact.  

Sender name and trust  

  • Recognisable sender names matter  
  • Sudden sender changes hurt consistency  
  • Stable sender identity improves inbox confidence  

Inbox placement and authentication  

Inbox placement affects opens more than wording.  

Authentication matters:  

  • SPF  
  • DKIM  
  • DMARC  
Spam complaints damage deliverability far more than low open rates ever will. 

Metrics that matter more than email open rates  

If open rates no longer show true engagement, the next question becomes what to use instead of open rates.  

If you want to understand performance, these metrics carry more weight:  

  • Click-through rate (CTR)  
  • Click-to-open rate (CTOR)  
  • Conversion rate  
  • Revenue per email (for ecommerce)  
  • Unsubscribe rate  
  • Spam complaint rate  
Open rates support these metrics, they do not replace them.  

The example below shows how this looks in practice inside iocea mailer’s campaign overview, where open rates sit alongside delivery, clicks, and engagement trends.

Email Performance Overview

How to Report Email Performance in 2026  

When reporting email performance in 2026, the goal is clarity, not volume. Clients do not need every metric an email platform can surface. They need a structure that shows cause, effect, and outcome.  

A simple, client-ready reporting flow looks like this:  

  1. Deliverability
    Are emails landing in inboxes or being blocked, bounced, or filtered?  
  2. Clicks 
    Are recipients taking meaningful action inside the email?  
  3. Conversions 
    Do clicks lead to sign-ups, enquiries, or purchases?  
  4. Revenue 
    What commercial value did the campaign generate?  
  5. List health
    Is the audience growing, disengaging, or churning?  
This order reflects how email actually works. Opens sit outside this flow because they no longer represent a reliable user action.  

Email open rates can still be mentioned, but only as a trendline, not a performance headline. We use opens to answer questions like “Is something materially changing over time?” not “Did this campaign succeed?” 

How we recommend using open rates at iocea  

We treat email open rates as: 

  • Indicative  
  • Comparative  
  • Best used alongside other metrics  
Inside iocea mailer, open rates work best when paired with:  

  • A/B testing results  
  • Click behaviour  
  • Conversion tracking  
  • Automation triggers based on actions, not opens  

This avoids decisions based on inflated or automated signals.

Frequently Asked Questions

What is an email open rate?

The percentage of delivered emails that register an open, usually tracked when a small invisible image loads.

Are email open rates still accurate?

They are less accurate than they used to be due to privacy features like Apple Mail Privacy Protection and image caching. They work best as directional data, not exact measurement.

Why do my open rates look higher than before?

Some email clients trigger tracking pixels automatically, even if the email is not actively opened by the user.

Can open rates still measure performance?

Yes, but only in context. They help compare campaigns, spot trends, and test subject lines within the same audience.

What affects email open rates the most?

List quality, subject line relevance, sender recognition, inbox placement, and consistency.

Should automations still trigger based on opens?

Open-based triggers are increasingly unreliable. Clicks, page visits, or purchases provide more dependable signals.