Your Guide to A/B Testing for PPC

Posted on March 8, 2022 • Written by Andrew Krom
Guide to AB testing for PPC

As with all marketing channels, your brand’s paid search, or PPC, can be optimized to drive conversions, increase traffic, or help you reach your other goals. At Fruition, we know that one of the best tools in your paid media arsenal is A/B testing—so long as you follow the key tenets of the practice. 

Related: Paid Vs. Organic Search: What You Need to Know

Here are some A/B testing basics to keep in mind when you’re working on refining your paid campaigns.

Why A/B Testing for Paid Search Is Important

Before we get into best practices for A/B testing on PPC, it’s a good idea to have a basic understanding of why it’s beneficial to A/B test in the first place. Here’s a quick rundown of why you should probably be A/B testing for your paid campaigns. 

Essential Practices When A/B Testing for Paid Media

Keep Your Changes Simple, and Your Mind Open

It might be tempting to try to change up several factors from your A test to your B test—especially if you’re interested in testing multiple different versions of your paid media placements—but just like we all learned in elementary school with the scientific method, A/B testing does the best when only one aspect of your campaign is changed between the two versions of the paid media you plan to run. 

For instance, if you want to test whether one CTA or another CTA is more effective and engaging to your brand’s audience, you should keep the rest of the elements of the campaign (e.g. the audience you’re targeting, the channel you’re running the campaign on, the general design or look of the ad, etc.) the same. In this way, your data from the test will be able to provide you with a clear picture of which CTA is performing better. If you’d like to test multiple aspects of the same campaign, consider running multiple A/B tests over a longer period of time. Too many changes all at once will muddy your data, leaving you with test results that you won’t find much use in. 

Duration Matters

Probably the most often overlooked part of A/B testing, especially for paid, is duration. Many companies are quick to pull an A/B test early, either because they’re eager to see which option is performing better, or because they just don’t understand how long it takes for data to accumulate. Because an A/B test for paid requires enough traffic to populate results that present a coherent picture of what your audience prefers, it is very important to run your A/B test for 2-3 weeks. Across the industry, this is acknowledged as the optimal time frame for A/B testing.

Stay Focused on Your Data

Once those 2-3 weeks have passed, and you’ve gotten results from your A/B test, the best way to use that data is to let it guide your next moves, whether you plan to run a follow-up A/B test, or whether you plan to build a single campaign based on that information. Sometimes the data that comes from your A/B test might surprise you, but it’s always best to listen to what the data is telling you about your audience and make informed decisions based on that data. If you need help parsing data that might be confusing, it’s often a good idea to consult paid media pros, like our team here at Fruition, who can help you better understand what choices to make and which actions to take in your next paid campaign. 

How System Updates and Privacy Changes Affect Data

It is also important to keep in mind that A/B testing (and paid media, for that matter) does not exist in a vacuum. There are sometimes larger, widespread changes in the world of the internet that might affect your data. For example, changes in Google algorithms or in Apple iOS operating systems often affect how data presents itself in analytics software or applications. It’s a good idea to keep on top of these changes so that you and your team can anticipate them. 

Another important thing to keep an eye on is privacy. Last year, for instance, the changes to cookies pushed by iOS and Google platforms had a radical effect on how data is collected, analyzed, and reported online. Understanding and staying informed about these kinds of larger, tectonic changes to the way the internet works will give your team an edge when A/B testing.

Read more: iOS14 & iOS15 Update: What You Need to Know

When A/B Testing for Paid Search Might Not Be Beneficial

As with all things, there are some instances when A/B testing for paid search might not serve much of a purpose for your brand. Simply put, your brand’s data is only useful if you have enough traffic to measure. Here’s a little more on that:

This guide should prepare you for at least your first few A/B tests on paid media campaigns, but if you decide you need a little more assistance, reach out to our team at Fruition. We’re always happy to help build your brand based on data-driven insights. 

Get in Touch With the Experts!

Andrew Krom

Written by Andrew Krom

As Fruition’s Paid Media Specialist, Andrew Krom provides ongoing and actionable insights into his clients’ paid search campaigns overall performance, with impeccable attention to detail when it comes to competitor research, website research, audience targeting, new technologies, and policies. Having worked with several full-service marketing agencies before coming to Fruition, Andrew has a deep background in paid, as well as a BA in Marketing and Graphic Design from Carthage College, and certifications in Google software and HubSpot Inbound Marketing.

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