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The ABC’s of A/B Testing Your Mailings

The ABC’s of A/B Testing Your Mailings

Wednesday, September 13, 2017 by Redi-Mail

As the saying goes, “If you’re not testing, you’re guessing.” But, did you know that failing to test your mailings can be just as bad—if not worse—than guessing alone? When it comes to direct mail, marketers cannot afford to guess. We’ve got everything you need to know about testing your next mailing.

What is A/B Testing?


A/B (or split) testing allows marketers to compare two different versions of a direct mail piece—a control (the original) and the variation—to determine which performs best. These tests are used to experiment with various design options including the position of text and images, background colors, number of images and different headlines.

Why use A/B Testing?

A/B testing unveils concrete evidence of what works within your marketing. By continuously testing your hypotheses and expectations, you will not only yield actionable results, but will also better understand your customers. Having a clear idea of what your customers actually like and respond to can help improve your branding and marketing across all channels.

How to A/B Test

A.      Identify Your Goals

What do you want to achieve? B2B companies may be more focused on generating more leads for their sales staff, while B2C companies may have a greater emphasis on increasing sales.

B.      Decide What to Test

What are you going to change? Modify variables such as call-to-action placement, wording, or size, image placement and content, and the layout of the message.

C.      Define Hypothesis

A/B testing must start form a clearly defined hypothesis. A good hypothesis is easy to test, aims to solve a problem, and gains market insights.

D.      Create a Variation

Modify the variable in the second version—as the number of variables in a test increases, the potential choices grow exponentially.

E.       Test hypothesis

Implement the modified version to be compared with the control.

F.       Calculate Your Results

Before concluding your test, you’ll need to reach statistical significance of 95% or better to be sure your results are valid, rather than based on chance.

G.     Analyze Test Data

Compare A/B test results to determine which variation delivered the best performance. If there is a clear winner among them, go ahead with the implementation.

H.     Learn from Results and Repeat

No matter how well your direct mail pieces may be performing, there is always room for improvement. Test other variables for even better results.

Those who know are those who test! With over 20 years’ experience and in-house capabilities, trust Redi-Mail for personalized direct mail and specialty packages. From your basic mailer to a multi-channel approach, Redi-Mail will manage your program from start to finish with the latest in equipment and technology.

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