How to Measure Email Campaigns: Eight Metrics and Why Open Rate No Longer Works

Open rate stopped being a reliable signal: Apple mail privacy protection loads email content automatically, and an open registers even when nobody saw the message. Measure clicks, conversion and revenue per email instead. Below are eight metrics with a note on how far each can be trusted, and thresholds for each campaign type.

What broke in open rate

The mechanism is simple. An open is recorded by loading an invisible image inside the email. Privacy protection pre-fetches that image on the provider side, whether or not the person ever opens the message.

The scale of the distortion is set by the share of clients where this protection is on. The client leading opens is precisely the one where it runs by default.

Two practical consequences follow. First, the absolute open rate is meaningless and cannot be compared with industry figures, which are measured differently and vary several-fold. Second, the trend is still informative. If open rate held steady and suddenly halved, that signals a delivery problem rather than a weak subject line.

Eight metrics and how far to trust them

Here is every metric ranked by trust. The "what it is good for" column matters more than the metric itself: each has its own job and they should not be mixed up.

On clicks specifically. There are two ways to count: against emails sent and against emails opened. The first shows overall effectiveness, the second the quality of the content given that someone opened it. Since the denominator in the second case is distorted, the first is more reliable.

The metric that matters most

If you keep only one metric, make it revenue per email sent. It links the whole chain — delivered, opened, clicked, bought — and converts the result into money.

Its main virtue is letting you compare the incomparable. A welcome email and a promotional campaign have different open rates, different conversion and different audiences, but revenue per email brings them onto a common scale.

This is the metric that shows why automated email beats regular campaigns: the gap in revenue per email between them runs into tens of times, while by open rate it looks far more modest.

Spam complaints: the one hard threshold

Of all the metrics, only one has a hard external threshold set not by your judgement but by mailbox providers.

A spam complaint rate above 0.1% — one complaint per thousand emails — starts affecting the deliverability of everything you send afterwards. Crossing that threshold is more dangerous than any dip in open rate, because it hits the entire list at once.

• keep the unsubscribe link visible: an unsubscribe beats a complaint
• do not send to lists collected without explicit consent
• watch the frequency: a sharp increase in volume raises complaints
• segment: an irrelevant email draws a complaint more often than an unsubscribe

A paradox worth accepting: a rise in unsubscribes is sometimes good. Someone who unsubscribes instead of complaining preserves your sender reputation.

Different emails need different measures

There is no single set of thresholds, because emails do different jobs. An order confirmation and a promotional campaign are not comparable on any measure.

• transactional — watch delivery rate and conversion to the intended action: did they open tracking, reset the password
• welcome — conversion to a first purchase, around two percent
• abandoned cart — share of carts recovered, low single digits is normal
• re-engagement — share won back, between three and twelve percent
• promotional — revenue per email and unsubscribe rate
• digests — clicks and depth: how many links get opened from one email

What to compare your numbers against

The most common evaluation mistake is comparing yourself against someone else numbers. Industry benchmarks are computed with different methods, on different lists and in different segments. The spread between sources for the same metric reaches several-fold.

The right reference point is you, a month ago. Record current values for each email type and compare against them next month. A change on your own list is more informative than any comparison with a stranger.

A second reference is the difference between email types inside your own programme. If automated flows do not beat regular campaigns on revenue per email, something is wrong with them, and that is visible without any benchmark.

How to set up measurement

Technically, measurement needs two things: link tagging and a goal in your analytics. UTM parameters must be structured identically across every email, or the data will not assemble into a report. The analytics goal must record the final action, not the visit to the site.

In Mailvex, UTM parameters are configured once for the whole email and applied to every link automatically, so the structure stays consistent without manual work. The pre-send validation panel flags links without tags.

Frequently asked questions

Should I ignore open rate entirely?

Watch it, but as a delivery indicator rather than an engagement one. A sudden halving means a problem reaching the inbox. The absolute value and comparisons with industry figures are meaningless.

Which metric matters most if I pick one?

Revenue per email sent. It links the entire chain and lets you compare different email types against each other, which neither opens nor clicks can do.

What should I do if spam complaints go up?

Cut sending frequency immediately and check where new addresses come from. The 0.1% threshold is one complaint per thousand emails, and crossing it damages deliverability for the whole list, not just the problem segment.