The 5-Step Test to Determine Optimal Email Frequency

You’re well aware that there is a thin line between infrequent email communications and inundating your email recipients with messages to the point of opting out. Perhaps you’re interested in increasing the frequency of your email marketing in 2021 but don’t want to see all your hard lead generation work go to waste by doing so. How do you determine the optimal email sending frequency for your subscriber list?

If you guessed “test,” you are correct! While we’ve conducted tests and published research on email sending frequency, each brand’s email marketing campaign objectives and subscriber list are unique, necessitating fine-tuned testing to determine the most effective sending frequency.

Therefore, how do you begin conducting an email send frequency test? Many people have been hesitant to conduct this test for fear of jeopardizing their lead generation efforts, but it is actually quite straightforward. Let’s walk through the steps required to conduct this test so you can begin determining how frequently you should communicate with your email subscribers.

1. Establish Your Hypotheses

Reconnect with your favorite lab partner from high school science class. It is critical to establish the specific results you anticipate from these tests in order to determine success.

For instance, you may hypothesize that increasing your email send frequency from once a week to three times a week will increase your click-through rate by 35% or that it will increase the number of “wheat bread” leads who progress to the prospecting stage by 15% as a result of your nurturing. Or perhaps you have an alarmingly high opt-out rate and believe that reducing your email send frequency from daily to every other day will result in a reduction in unsubscribe. You can (and should!) create multiple hypotheses to get the most out of these tests, and your hypothesis should be extremely specific in its terms.

2. Choose a List Segment

Consider this to be your sample size. Given that your email list is already segmented (correct? ), choose one segment to test and ensure it is sufficiently large to provide meaningful data. Ascertain that the list segment you choose also corresponds to the hypotheses you are testing. For instance, if you’re testing for an increased offer click-through rate targeted at prospects, it’s not a good idea to conduct the test on a segment of your customer list. Rather than that, you might choose a sample (not the entire list) of your blog subscribers who are not only large enough to provide meaningful data, but also accustomed to receiving emails from you with offers.

3. Establish Baseline Metrics

Once you’ve determined what you want to test and who you want to test it on, you can establish the sample’s current performance metrics. This step is critical, as you will need something to compare the results of your test to. Take note of the email marketing metrics you’ll need to determine your test’s success, such as your open rate, deliverability rate, unsubscribe rate, and click-through rate for that specific sample.

Additionally, do not be afraid to broaden your horizons beyond traditional email marketing metrics to include website performance metrics. For instance, if you were testing the hypothesis of increasing an offer’s click-through rate, you’d want to know how many email recipients not only clicked through the email offer, but also completed the form required to obtain their offer.

4. Create and Schedule Your Test Emails

Create a few test emails to distribute to the list sample, adhering to your standard email marketing best practices. Now is not the time to experiment with novel subject lines, new senders in the “from” field, or new email templates. These content changes have the potential to skew your results and should be reserved for a separate set of tests.

Once the emails are created, schedule them to be sent at the frequency specified in your hypothesis. For tests lasting longer than a week, ensure that the same days and times are used to avoid adding another variable to the equation, as time of day and weekday have been known to skew results. Again, this is a critical test to perform, but do so at a later time.

5. Measure and Analyze Results

Analyze your findings in relation to the hypotheses you established at the outset and the baseline data you collected. In addition, you should monitor results frequently throughout the experiment to allow for any dramatic swings caused by your change in emailing frequency.

Are the outcomes you’re observing favorable? Do they corroborate your hypotheses? Do they enable you to increase your email sends even more in order to see a positive impact on your bottom line without jeopardizing your list’s size or quality? Or is a reduction in sending what is required? Now that you’ve established a new benchmark for success, iterate on it by initiating a new email test, whether for frequency, template design, subject line, message copy, or offer content, or any other number of variables that can be tested to improve the effectiveness of your email marketing.