A/B testing can be a great way of improving your digital marketing efforts. It can help you improve website copy, sales emails, and other marketing strategies, and it’s also a great way to test your PPC advertising to improve click-through rates.

What is A/B Testing?

The premise of A/B testing for PPC advertising is simple: you create two iterations of the same ad, identical in all respects except for one—the one difference being the thing you want to test. You can test virtually any element of a web page or ad—such as headlines, text, images, and layout—using various different metrics to analyse your results.

For example, if you’re testing product page variants in an online store, you’ll look at which variant gives the highest purchase completion rate. For non-product pages, it’s helpful to look at how long people spend on each page, and whether they move from that page to another page on the site, or whether they leave the site altogether.

Note that while it’s possible to create tests that examine multiple variants at once, it’s much simpler to test a single change at once, to produce results that are easy to interpret. So, for example, if you’re looking at page layouts, it’s more helpful to test each individual element individually rather than making sweeping changes to the layout all at once.

Applying A/B Testing to PPC

A/B tests can be applied to PPC advertising fairly simply, because PPC account interfaces already provide you with the means of creating and running multiple ads at the same time. So it’s simply a matter of choosing what elements to test, and then scheduling each variant to run at the same times. Some possible testing examples include:

·       Look at how headlines affect click-through rates; for example, the difference between using a statement headline and one that asks a question.

·       Test an ad that talks prices versus one that doesn’t.

·       Negative versus positive wording, for example, yes versus no, or don’t versus should.

Don’t Expect Instant Results

The key to getting usable information from A/B testing is to test one change at a time, and to give your tests some time. This can be difficult with PPC advertising, especially if you have budgetary constraints that limit your daily spend. Plan to devote at least a few days for testing each change, depending on the popularity of your key words. With keywords that garner high click-through rates you may see testing results more quickly, whereas lower rates might extend the time required for testing.