How to use email open rates
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Previous: What do email open rates mean?
Now if you persevered this far without giving up on email open rates all together, here's the good news...they do have their uses.
The key is not to look at them as actual absolute numbers. Knowing an open rate is 35% isn't terribly useful. It's clear from the previous section they don't really tell you exactly how many people "read" your email.
But they are useful as indicators: how open rates change tells you a great deal indeed. In other words, they're a super measure for making comparisons between the different emails you send out.
As long as you always measure and calculate the open rate in the same way, then the chances are that changes in the open rate reflect real changes in something you're doing with your email marketing.
If you change your email service and open rates rise, it was a good idea. If they fall, it was a bad idea (assuming everything else remained unchanged). This kind of thing is great intelligence.
Here are some examples:
Open rate extremes
While open rates are inaccurate, you can still learn something from extremes.
Say you have your own email list where people signed up explicitly for your emails. If you send reasonably relevant mails out every 1 to 4 weeks, then single figure email open rates indicate a clear problem.
Unless there's an obvious explanation (like people all get text-only messages), then a very low open rate is a timely warning that you need to find out what's going wrong and do something about it.
Open rates can fall to zero if there's a technical fault in the email delivery service. It's worth checking the open rates of different parts of your list, too, rather than just looking at the overall number. This is especially valuable when it comes to spotting delivery problems.
Consider looking at open rates for all the recipients at a particular domain.
If the total recorded open rate for your mailing was 30%, but the open rate for recipients with a yahoo.com address was a big fat 0%, then you have a problem: clearly your email is not getting through to Yahoo email accounts.
Look at your email address list, pick out the common domains and keep an eye on the open rates for each one. Look for anomalies and find out why they deviate significantly from the norm.
Comparing subject lines and other elements of your email
Say you split your list into two halves and send one half Email A and one half Email B. The two emails are identical but for their subject lines. You want to see which subject line pulls better results.
One way to compare those subject lines is to compare the open rates for the two halves. Since the only difference between the groups (assuming you're doing things with due statistical diligence) is the subject line, any changes to open rates are caused by that subject line.
So if Email A gets an open rate of 50% and Email B one of 20%, you can be pretty sure that the subject line used in Email A is better at getting the attention of recipients.
The same A/B test principle can be applied to other elements of your email that might affect open rate, like the "from" line.
Of course it goes without saying that email open rates should not be the only measure you use to compare the test results (see what I said earlier about relevance).
Following trends over time
Assuming you measure and calculate the open rate consistently, then changes in that number over time can tell you things about your list and your emails.
If the open rate declines steadily you may have a problem with reader fatigue: time to mix things up a bit. If you see changes in your open rate then try and isolate the cause and learn lessons to apply in the future.
Perhaps certain types of offers in your subject lines always see a jump in open rate? That's insight you can use for the future.
Again, it's worth looking at different parts of your list.
Perhaps subscribers from particular sign-up source have a lower open rate than the rest of your list? Why?
Maybe there's a decline in open rates for people who've been on your list for more than six months. A decline that's masked in the overall recorded open rate by higher open rates from those who recently signed-up.
Look at the two groups separately and consider how you might re-engage those older email addresses.
Base figures for other metrics
When you look at the other numbers in your reports, like how many people clicked on a link, then how you interpret those numbers is also influenced by the open rate.
Consider this scenario...
You send out identical emails to two groups of people. The only difference is a headline in the body of the email: you want to see which of two different headlines generates the most clicks.
These are the results:
| Group A Headline 1 |
Group B Headline 2 |
|
| Emails delivered | 50,000 | 50,000 |
| Clicks generated | 12,000 | 11,000 |
At first glance, you might conclude that Headline 1 was the best, since it generated more clicks from the same number of emails. Now throw in the open rate results, too...
| Group A Headline 1 |
Group B Headline 2 |
|
| Emails delivered | 50,000 | 50,000 |
| Clicks generated | 12,000 | 11,000 |
| Open rate | 45% | 40% |
Now we have a different story. In Group A, 22,500 people "opened" the email and produced 12,000 clicks. That's a clickthrough rate of 53%. In Group B, 20,000 people "opened" the email and produced 11,000 clicks. That's a clickthrough rate of 55%.
Now we see that Headline 2 was actually better at generating clicks. You need to know the open rates so you can see if the differences in results were really due to the pulling power of the headlines and not just to the fact that fewer people saw one of them.
(It's more complicated than that, of course, since differences between the two groups themselves might explain the difference - but you get my point.)
Next: Average email open rates - useful?
1. Email open rates guide
2.
What do email open rates mean?
3.
How to use email open rates
4.
Average email open rates
(why yours are different)
5.
How to improve email open rates