What the numbers are
Most email tools report a few standard figures after each send.
Open rate is the share of delivered messages recorded as opened. Click rate is the share of delivered messages in which at least one link was clicked. Some tools also report click-to-open rate, which divides clicks by opens, along with the unsubscribe rate and the bounce rate, which counts messages that could not be delivered.
The exact definitions can vary between tools. Some count unique recipients, some count total events, and some base the percentages on messages sent rather than delivered. Check how your own tool defines each figure before comparing it with anything.
A worked example
Imagine a hypothetical send of 1,000 messages. Of these, 20 bounced, so 980 were delivered. The tool records 343 opens and 49 clicks.
- Open rate: 343 divided by 980 is about 0.35, or 35 percent.
- Click rate: 49 divided by 980 is 0.05, or 5 percent.
- Click-to-open rate: 49 divided by 343 is about 0.143, or roughly 14 percent.
These figures are invented to show the arithmetic, not to suggest what is normal. Notice that the denominators differ, which is why click rate and click-to-open rate look so different even though they describe the same clicks.
How an open is recorded
Most tools detect opens by loading a tiny hidden image when the message is displayed. That method has weaknesses.
- Some mail apps and privacy features load images automatically, even if the person never reads the email, which can inflate open counts.
- Some readers block images, so a genuine read goes unrecorded.
- Some people read a message in a preview pane or on a device that behaves differently.
Because of this, open rates are best treated as a rough indicator rather than an exact count of readers. Changes in mail apps over the years have made the figure less reliable in many cases. If your open rates look unusually high and clicks do not follow, this is a common reason.
Clicks are somewhat more reliable, but still limited
A click is a deliberate action, so it usually shows interest more clearly than an open. But it has limits too. Some security software follows links automatically to check for threats, which can register as clicks. A person who reads and finds what they needed in the message itself may not click at all. And a click shows interest in a link, not necessarily satisfaction with what was on the other side. To learn what happens afterward, look at your website analytics for the destination page.
What the metrics can tell you
Used carefully, the numbers can help you notice patterns.
- A sudden fall in opens may point to a delivery problem, a change in subject lines or a change in timing. See email deliverability for more on why mail may not arrive.
- Clicks on certain links over others show which topics appeal to your readers.
- A rising unsubscribe rate after a particular message may signal a mismatch with expectations.
- A high bounce rate suggests a list needing cleaning.
None of these proves a cause. They are prompts to look more closely.
Compare with your own history first
Published averages are tempting, but they vary by industry, audience, list quality and how each tool measures. They are not reliable benchmarks for your situation. A more useful comparison is your own past results from the same type of message. Track a handful of recent sends and see what range is typical for you. Then a result well outside that range is worth investigating.
Compare like with like. A welcome message and a monthly newsletter will naturally behave differently, as will a message sent to a small, engaged segment and one sent to the whole list.
Beware of small numbers
With a small list, a handful of readers can swing percentages sharply. If you send to 50 people, one extra click changes the click rate by 2 percentage points (1 divided by 50 is 0.02). Looking at several sends together gives a steadier picture than reading meaning into one.
This also affects testing. If you try two subject lines on a small list, the difference you see may be down to chance. The ideas in split testing apply, and the main lesson is to be modest about conclusions.
Metrics beyond opens and clicks
Consider what you actually care about. Possible goals include:
- readers replying with questions or comments
- readers visiting a particular page
- readers signing up for an event or resource
- readers staying subscribed over time
Pick a few measures connected to your purpose and ignore the rest. A newsletter that receives thoughtful replies from a few dozen readers may be succeeding even if its percentages look ordinary. Qualitative signals, such as feedback from readers, are worth collecting alongside the numbers, much as customer feedback tools gather views that statistics cannot.
A sensible routine
After each send, glance at the basics. Once a month, look at trends across several sends. When something shifts, check the simple explanations first: timing, subject line, list changes, and technical setup. Use what you learn to refine the next message, such as writing clearer subject lines, rather than chasing a particular percentage. Measurement is most helpful when it supports better decisions, not when it becomes the goal.