How are metrics normalized across ESPs?

If you move from one ESP to another and expect your open rate to look the same, you're likely to be disappointed. ESPs don't all define and count metrics the same way. The number you see in one platform's dashboard may not be directly comparable to the number in another's, even if they're both calling it "open rate."

Where the differences come from

What counts as "delivered." Some ESPs count a message as delivered if it wasn't hard-bounced. Others subtract soft bounces too. The denominator changes the rates.

Unique vs. total events. If the same person opens an email five times, some ESPs count that as one open (unique), others count it as five. Click rate has the same issue. Unique clicks and total clicks tell different stories.

How they handle Apple Mail Privacy Protection. Since 2021, Apple pre-loads tracking pixels for Apple Mail users, inflating opens. Some ESPs filter known Apple MPP signals from their open rate calculations. Others report them as opens. An ESP that filters them will show a lower open rate than one that doesn't, even from the same send.

Bot and machine-click filtering. Security gateways scan links in emails before the recipient sees them. That shows up as a click in raw event data. Better ESPs filter these out. Others don't, which inflates click rates.

How to normalize your own metrics

When comparing across ESPs or across time periods after a platform change, use click rate as your primary engagement metric. It's more consistently defined and harder to inflate than open rate. Click-to-open rate (CTOR) is even more useful for content effectiveness, because it compares clicks against opens from the same population.

If you're migrating between ESPs and want to make sure you're comparing apples to apples, ask each ESP directly: how do you define a delivered message, do you report unique or total opens, and how do you handle Apple MPP? The answers tell you how much adjustment to apply.