For years, open rate was the first number anyone checked after sending an email. Today it’s one of the least reliable.
Why open rates are inflated
Opens are tracked with a tiny invisible image. When the image loads, the email counts as opened.
- Apple Mail Privacy Protection (MPP): when turned on in Apple Mail, it loads remote content privately in the background, including tracking images, whether or not the person reads the email. Many Apple Mail users count as “opened”.
- Security scanners and bots: corporate filters open emails and click links to check them for threats. Mailchimp notes bot activity like MPP “can falsely inflate open and click metrics”.
- Images off: some people never load images, so real opens are missed.
Result: open rates look higher than reality, and “who opened” is a weak signal.
Metrics to use instead
| Metric | Why it’s useful | Watch out |
|---|---|---|
| Click rate (clicks ÷ delivered) | Requires an action | Turn on bot filtering if your platform offers it |
| Conversion rate / revenue per recipient | What the email actually produced | Depends on the platform’s attribution window |
| Unsubscribe rate | Content or frequency mismatch | Spikes after a specific email tell you something |
| Spam complaint rate | Deliverability risk | Gmail requires bulk senders to stay below 0.3% |
| Bounce rate | List quality | High hard bounces = old or bought addresses |
| List growth (net) | New subscribers minus unsubscribes and cleaned contacts | Track by source |
For flows (welcome, abandoned cart, post-purchase), look at revenue or bookings per recipient over a month, not per email.
Redefine “engaged subscribers”
Many platforms build engaged segments on opens. Rebuild them using stronger signals:
- Clicked an email in the last 90 days
- Visited the site (tracked through your platform’s site tracking) in the last 90 days
- Purchased or enquired in the last 180 days
- Recently subscribed (last 30 days)
Opens can still be one signal among others, but don’t rely on them alone. See email segmentation for a small team.
Subject line tests
A/B tests decided by open rate are now unreliable. Decide subject line tests by click rate or conversions, and give them enough recipients to mean something.
A monthly scorecard
| Section | Numbers |
|---|---|
| Campaigns | Sent, click rate, conversions, revenue, unsubscribes, complaints |
| Flows | Recipients, revenue or bookings per recipient |
| List health | Net growth by source, bounce rate, share of engaged subscribers |
| Deliverability | Complaint rate in Google Postmaster Tools (if you send to many Gmail users), any blocklist or inbox problems |
Compare against your own previous months rather than industry averages, which mix very different businesses.
Frequently asked questions
Should we turn off open tracking?
Not necessarily. It still gives a rough signal and some features (send-time optimisation) use it. Just don’t make decisions on opens alone.
Our open rate jumped. Is that good news?
Probably not by itself. Check whether clicks and conversions moved too. A jump in opens alone usually means more Apple Mail users or bots.
What about WhatsApp metrics?
WhatsApp reports delivered and read statuses, and replies or clicks are stronger signals. Track opt-outs and blocks per campaign. See WhatsApp marketing.
If you’d like your email reporting rebuilt around metrics that matter, that’s part of our growth funnel service.
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Monthly email scorecard
Record the metrics that still mean something (clicks, conversions, revenue per recipient, unsubscribes, complaints, list growth) per campaign and flow, with automatic rates and warnings.
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