You know there's a delicate balance between infrequent email communications and bombarding your email recipients with messages to the point that they opt out. Maybe you're interested in ramping up your email marketing in 2012 but don't want to see all your hard lead generation work go to waste by increasing your sending frequency. How do you know what email sending frequency is the right frequency for your subscriber list?
If you guessed "test," you're right on the money! While we've performed tests and released research on email sending frequency, every brand's email marketing campaign objectives and subscriber lists are unique and thus require fine-tuned testing to determine appropriate sending frequency.
So how do you get started with an email send frequency test? Many people have been nervous about performing this test for fear of ruining their lead generation efforts, but it really is quite simple. Let's break down the steps you can take to perform this test so you can start understanding how often you should communicate with your email subscribers.
Take yourself back to high school science class, and channel your favorite lab partner. It's important to determine what specific results you expect to see from these tests so you can identify success.
For example, you might 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 perhaps it will increase the number of "wheat bread" leads that move to the prospecting stage as a result of your nurturing by 15%. Or perhaps you have an unnervingly high opt-out rate, and you think decreasing your email send rate from daily to every other day will also decrease your number of unsubscribes. You can (and should!) create more than one hypothesis to make the most out of these tests, and be extremely specific with the terms of your hypothesis.
Think of this as your sample size. Since your email list is already segmented (right?), select one segment that you will test, and ensure it is sizable enough to provide meaningful data. Make sure the list segment you select also aligns with the hypotheses you are testing. For example, if you are testing for an increased offer click-through rate targeted toward prospects, it isn't wise to test on a customer list segment. Instead, you might decide to choose a sample (a sample, not the entire list) from your blog subscriber list that is not only sizable enough to provide meaningful data, but is also used to receiving emails with offers from you.
Now that you know what you want to test and on whom, you can establish your current performance metrics for that sample. This step is crucial, because you need something against which to measure the results of your test. Note the email marketing metrics you'll need in order to determine success in your test such as your open rate, deliverability rate, unsubscribe rate, and click-through rate for that particular sample.
And don't be afraid to expand your scope beyond traditional email marketing metrics to website performance metrics. For example, if you were to use the hypothesis of increasing an offer's click-through rate, you would also be interested to know how many of the email recipients not only clicked through the email offer, but also completed the form required to obtain their offer.
Create a handful of test emails to rotate through the list sample, following your regular email marketing best practices. Now is not the time to experiment with creative new subject lines, test a new sender in the "from" field, or create a new email template. These types of content changes can skew your results, and should be reserved for a separate set of tests.
Once you've created the emails, schedule them for the sending frequency you outlined in your hypothesis. For tests that exceed a week in duration, be sure to select the same days and times so as not to add another variable to the equation, as time of day and day of week has been known to skew results. Again, this is an important test to perform, but reserve it for another time.
Measure your results against the hypotheses you established in the beginning and the baseline results you recorded. You should monitor results frequently throughout the experiment, too, so you can respond to any dramatic swings that may crop up because of your change in emailing frequency.
Are the results you're seeing positive? Do they confirm the hypotheses you've outlined? Do they allow you to increase your email send even more to see positive gains to your bottom line without sacrificing things like the size or quality of your list? Or is a decrease in sending what's in order? Now that you have a new baseline for success, iterate off of it by beginning a new email test, whether for frequency, template design, subject line, message copy, offer content, or any other host of items you can test to make your email marketing more effective.
Have you tested how frequently you should send emails to your subscriber base? What results did you find, and were any surprising departures from what you expected?
Image credit: alexander_witt
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