Email Marketing Metrics: What to Actually Track
Email marketing metrics fall into four groups with different roles: deliverability, engagement, revenue, and list health. The problem with most reports is not a lack of data but how it gets mixed up: diagnostic metrics treated as goals, and business metrics ignored because they are harder to calculate.
Why is open rate no longer a reliable metric?
Because the privacy protection features in some email apps preload the images in messages, including the pixel that records the open. As a result, some of the reported opens happen without anyone actually reading the message, and the share differs from one provider to another.
That doesn't mean the metric should be ignored completely. It stays useful for internal comparisons, between similar sends made in the same period, and as an alarm signal when it drops suddenly. What it can no longer do is serve as the judge in a test or as a performance goal.
What does click rate show, and how do you interpret it?
Click rate is the first metric of real interest, because it requires a deliberate action. It is calculated either against delivered messages or against opened ones; the first option is more stable, precisely because it doesn't depend on a metric affected by preloading.
Interpreting it correctly takes context. A low rate on a broad segment can be more valuable than a high one on a narrow segment, and an informational message can't be compared with a promotional one. Comparisons only make sense between sends of the same type, to comparable segments.
Which deliverability metrics should you track?
These are the metrics that flag problems before they affect revenue:
- Hard bounce rate, as a share of sends.
- Complaint rate, tracked separately across the main email providers.
- Performance differences between recipients' email providers, which point to selective filtering.
- The share of contacts who haven't engaged in a long time, across the whole list.
Track these values as a trend, not as isolated numbers. A slow, steady rise in complaints is a more important signal than a one-off spike caused by a single atypical send.
How do you measure revenue correctly?
The revenue generated by a send, divided by the number of recipients. It is the metric that lets you compare sends of different sizes, unlike total revenue, which automatically favors large segments.
Total revenue generated by the channel is useful for reporting to management, but it doesn't allow comparisons. A campaign sent to a large list will always have higher total revenue; that doesn't mean it was better.
The second important distinction is between attributed and incremental revenue. The platform credits the message with any order placed within a time window after an open or click, including orders that would have happened anyway. The difference is measured with control groups and matters most for recovery flows.
Which list health metrics should you track?
The list is the program's core asset, so its evolution deserves to be tracked separately from send results. The useful metrics are net growth, meaning the difference between sign-ups and losses, unsubscribe rate by send type, the share of active contacts in the total, and the share of new subscribers who go on to place a first order.
The last one is the best indicator of how well your collection methods work. A list that grows fast but where the share of buyers keeps falling signals that your sources bring volume without intent, which costs money in the platform every month and hurts deliverability.
How do you track customer lifetime value?
Through cohort analysis: customers acquired in the same period and tracked over time, looking at how many placed a second order, how soon, and how much they spent cumulatively. It is the only way to see whether the program really changes buying behavior or just redistributes orders that would have happened anyway.
Two metrics deserve constant tracking: the share of customers who reach a second order and the average time until it. Both react directly to the quality of the post-purchase flow and are far more relevant to the business than the click rate of a single campaign.
What do you compare between flows and campaigns?
The two can't be compared directly, because they work differently. Flows reach one person at the moment of intent, so their engagement metrics are much better; campaigns reach a group, at a time the store picks.
How do you attribute orders correctly between email and the other channels?
Attribution is where different reports tell different stories about the same order. The email platform claims an order placed after a click on a message; the ad platform claims the same order if the person also saw an ad; the web analytics tool may credit everything to the last traffic source. Added together, the figures exceed the store's actual sales.
The practical solution is not to pick one system as the correct one, but to understand what each one measures. Platform reports are useful for internal comparisons, between sends, while budget decisions across channels are made on consolidated data, with the store's total revenue as the reference point and with control groups where the real contribution is uncertain.
Which metrics are misleading?
Three show up constantly in reports and lead to the wrong priorities:
- Total number of subscribers, without the share of active ones. A large, inactive list costs money and hurts deliverability.
- Total channel revenue, without accounting for segment size and without margin.
- Open rate used as a goal, even though it is influenced by mechanisms outside your control.
On top of these come comparisons with market benchmarks. Differences between categories, business models, and collection practices make these comparisons almost useless; the right reference point is your own history.
What does a useful monthly report look like?
A report that can be read in a few minutes and used to make decisions has four sections: