How often do you run A/B tests in your e-mail marketing campaigns? If you are currently racking your brain trying to think of the last time – if ever- you ran an A/B test, then it is time to revamp your strategy!
“But, I follow all of the e-mail marketing best practices,” you try in rebuttal. That’s great! Best practices are best practices for a reason.
However, just as every person differs, every brand’s audience does too. So, you still need to test, test, and test some more, no matter how extensively you have researched, “what works best?”
To get you started, here are five easy e-mail marketing tests to try, any one of which you can implement in your next campaign.
Test #1: Date & Time
One of my most successful e-mails was sent at 7:00pm on a Sunday evening! True story. That’s crazy to some of you who know that most marketers lean toward Tuesday sends. And, most of the time, Tuesday is a great option. But, as my Sunday evening e-mail success proves, there are always exceptions.
Are you sending an e-commerce e-mail notifying your audience about a sale? What is the best time to catch your customers in shopping mode? Implement an A/B test to see how your open and click rates differ on Tuesday at 11:00am vs. Tuesday at 8:00pm. Or try Tuesday at 11am vs. Saturday at 11am.
If you have never tested it, how do you know the perfect time for your audience to target certain messages? Don’t stick to the status quo. Test similar campaigns on an entire range of dates and times, and you will start to gather data to see when your sale e-mails get the best engagement, when your editorial e-mails get the best engagement, and when your B2B e-mails get the best engagement.
Test #2: Subject Lines
What type of language does your audience respond to? Sure, you’ve read about all of the buzzwords that make for good e-mail marketing subject lines. Sure, your audience likely responds to these words. But, can you do better?
Does your audience of thrill-seeking outdoor enthusiasts seem to like adrenaline-arousing language better?
Does, “Save 10% Storewide,” or, “All Items on Sale,” work better for your sales?
If you’re talking to a group of dog moms, do they resonate more with a pawesome pun?
There is only one way to find out.
Test #3: Imagery
The imagery you use in your e-mails will indeed make a difference in how your audience responds. This is a must-use test for any great e-mail marketing strategy.
If you are in the business of selling products, try testing whether images of your products or more aspirational imagery of people using your products resonates better.
The results may surprise you!
Test #4: Content
There are so many content elements you can test in your e-mail marketing campaigns. Do your emails convert better when you include more information, or when you tease a short bit of information? You can switch up the wording used in your call to action. You can even see if putting a more editorial spin on a topic vs. sending just the facts will work better. The list goes on…
Start small, and try testing whether or not adding product testimonials to your e-mail makes a difference in your click through rates.
Test #5: Design
Similar to your content tests, the design of your e-mail is a great test to conduct. One easy and fun test that you can conduct is varying your e-mail layout; no graphic designers needed for this one!
Try a two-column layout vs. a one-column design. See if your imagery works better when it is aligned next to your text or is used as a header on top of your text.
Continue to play around with all types of layouts, and you will be able to start to see if there are any ways to fine tune your e-mail’s design going forward based on your audience’s response.
As you go through your testing strategy, be sure to analyze the results often, and continue to optimize your e-mails based on your findings. A lot of marketers struggle with this step. A/B testing is not a run it and leave it process. As much as you test you must analyze, and, of course, optimize based on results.
And always remember the golden rule of controlled testing: only edit one variable at a time.