Email marketing is a tried and tested method of reaching out to new and existing clients. From SMBs to Fortune 500 companies, everyone’s practically reliant on email marketing.

However, many email marketers fail to conduct A/B/n testing to measure whether a brand’s email strategies and tactics are working or not. Teams also often struggle to set up tests correctly and measure their results accurately, leading to ineffective email experiments, and well, wasted time.

If your testing is unreliable, you don’t know if your strategies work or not. Here are 5 common testing problems.

Testing without a hypothesis

Many email marketers pick up the rudiments of testing by using the tools their ESPs give them, mainly for setting up basic A/B split tests on simple features such as subject lines. However, this ad hoc, one-off approach is like learning to drive a car without knowing how to read a map. You can turn the car on just fine. But you need map skills to plan out a journey that will get you where you want to go with the fewest traffic jams and detours.

Using the wrong conversion calculator

This relates to the customer‘s journey and the test’s objective. When you do a standard A/B split test on a website landing page, you often use “transactions/web sessions” as your conversion calculation to see how well the page is converting. This makes sense because you don’t know the path your customers took to get there on the site, so you focus on this particular part of the journey, as it ignores everything that happens before it.

Measuring success with the wrong metrics

A workable testing plan needs relevant metrics to measure success accurately. The wrong metrics can inflate or deflate your results. This, in turn, can mislead you into optimizing for the losing variant instead of the winner.

Testing without statistical significance

If your testing results are statistically significant, it means that the differences between testing groups (the control group, which was unchanged, and the group that received a variable, such as a different call to action or subject line) didn’t happen because of chance, error or uncounted events.

Testing only one element in a campaign

Subject-line testing is ubiquitous, mainly because many email platforms build A/B subject line split testing into their platforms. That’s a great start, but it gives you only part of a picture and is often misleading. A winning subject line that’s measured on the open rate doesn’t always predict a goal-achieving campaign.