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Managing a digital marketing campaign involves making many optimization decisions to maintain or improve performance as competition (and click costs) grow over time. It’s not uncommon for account managers to make those decisions based on their experience (their “gut feel”) rather than relying on statistically relevant data.
Is it worth the effort of implementing A/B testing? In our experience, absolutely – introducing a robust yet efficient A/B ad testing framework will significantly improve the effectiveness of your data-driven strategies in digital marketing, but how to do that in a way that doesn’t consume all your time?
Luckily, there is a way to run ad testing in an efficient manner, allowing you to rely on data (rather than ad-hoc or gut feel testing) so your performance can methodically migrate towards better results.
Google Ads Ad Variations is a tool within Experiments that allows marketers to approach ad optimization scientifically. By choosing elements to test, methodically tweaking them, and comparing their performance, businesses can uncover what resonates best with their target audience. This not only improves click-through rates and conversions but also enhances the overall user experience by presenting ads that truly engage.
With Ad Variations, you can test a variety of elements. These include:
Not only can you test different variations of the above, but you can also swap their positions to test the effect it has.
The path to A/B testing success begins with clarity. Defining what you want to achieve helps in creating a focused and effective testing strategy. Whether it’s reducing cost per acquisition (CPA), enhancing ad engagement, or boosting landing page visits, each objective needs a tailored approach in both creatives and measurement.
When selecting elements to test, consider starting with those that have the highest visibility and potential impact – we suggest starting out with Headline testing. A compelling headline can grab attention, while a persuasive call to action (CTA) can increase click-through rates. Testing different CTAs or value propositions can provide valuable insights into what drives your audience to act and improve your conversion rates.
Whatever you do, make sure you test one element at a time so you have an accurate test – here are some suggestions to get you started:
Ad Structure
Once you have your building blocks ready, it’s time to think about ad structure. Here is a framework that generally works well:
👉 Pro Tip: Pinning is important. Google wants you to run your ads with no pinning, but it’s been well documented that whilst this results in generally better CTRs, if you want higher conversion rates then pinning (at least your headlines) is the way to go.
There are two steps to using audiences when testing your RSAs:
Level 1: Testing audience performance against your ads.
We recommend you start by adding all available/appropriate audiences to your Ad Group as “observation” targeting. This will reveal the performance of your ad across multiple audiences’, but at an individual audience level you still can’t see which text combinations performed poorly or well. To do that, you need to level up!
Level 2: For your higher traffic audiences, you can duplicate the Ad Group and specifically target an individual audience within the Ad Group. This allows you to tailor your ads so they speak directly to that individual audience. The effort required to go this deep means it’s only time effective to do for your largest audiences, but it can really help your ads to stand out if done well.
👉 Pro Tip: Create a campaign experiment if you want to split test audiences without having duplication and overlap. You’ll have to pause the current ads in your experimental campaign and create ones you’d like to test, but it’s an effective way to test this.
When you start testing, it’s important to decide if you want an equal traffic split or if you’d just like to test a small part of your traffic. If your existing ads are performing well, we suggest testing your new ads on a smaller percentage of traffic to avoid the negative impact of introducing worse performers. Conversely, if your current ads performance smells like an old pair of gym socks, you may want to test a larger percentage of your traffic to see if you can improve performance quickly.
👉 Pro Tip: If you only want to allocate a portion of spend to the test, you’ll need to create a campaign-level experiment instead.
Sign in to Google and navigate to Experiments, then click “Ad variations”.
If you’ve created other variations, you’ll see those here. Next, click on the blue plus sign. Either choose all campaigns or select a specific campaign. Now, filter by the ad element you’d like to test. Click continue.
Use the find and replace, update URLs, or update text to make changes in the ad elements you’d like to test. Type in the element you’d like to replace in the find text box and the new text in the Replace with box.
Once this has been completed, you’ll set up the test details. First, name your ad variation and choose the start date. Add an end date or duration. Last, choose Experiment Split and tap Create Variation.
Proper conversion tracking setup is critical, but so is understanding its nuances. For instance, tracking micro-conversions, such as newsletter signups or page engagement, can offer early indicators of variation performance before final conversion data becomes available.
Creating a few micro-conversions that show someone’s journey could be helpful. For ecommerce accounts, this might be an add-to-cart or expanding product details. In lead gen accounts, it could be PDF downloads or viewing a pricing page.
👉 Pro tip: Set those micro-conversion steps to your ultimate goal (like a purchase) as secondary conversions so your conversion data remains clean and your campaigns bid strategy will optimize for the correct goals. Using micro-conversions to feed the bid algorithm is a whole other topic for another day!
Diving deep into the analytics, it’s essential to look beyond surface-level metrics. Analyze user behavior changes, engagement patterns, and even ad fatigue. Utilizing tools like Google Analytics in conjunction with Google Ads can paint a more comprehensive picture of how each variation influences user behavior across the funnel.
Look at time on site, the number of pages viewed, and other indicators of audience change. Who is visiting your site and what they’re doing is as important as getting conversions because, just like life, it’s about the journey and not the ending.
The real magic happens when insights from A/B testing inform your broader marketing strategy. It’s not just about tweaking ad copy or imagery; it’s about understanding the underlying preferences and behaviors of your audience. These insights can guide content strategy, landing page design, and even product development.
What can you learn? Here are just a few things:
A/B ad testing is the data-driven way to optimize your ads. Beyond testing too many variables or making premature adjustments, another common pitfall is neglecting the impact of external factors. Seasonal trends, competitor actions, or market shifts can all influence A/B testing results. Controlling these or at least acknowledging their influence is crucial for accurate analysis.
Watch out for these potential mistakes:
A/B testing, especially with Google Ads’ ad variations, is not a one-off task but a continuous cycle of learning and optimization. The insights gained from each test should fuel the next, creating a culture of constant improvement and adaptation.
A/B ad testing shouldn’t just be limited to your ads but all parts of your campaigns and accounts. The more testing you do, the more successful you’ll be. Some other areas to test are campaign type, demographics, budgets, and device-related strategies.
To truly master A/B ad testing with ad variations, consider diving into advanced resources, such as:
A/B ad testing with Google Ads’ ad variations is a journey of exploration, learning, and refinement. By embracing this iterative process, small marketing agencies and beginners alike can unlock the full potential of their digital advertising efforts, turning insights into action and browsers into buyers.
Using Google Ads’ Ad Variations is a great way to perform A/B ad testing in an efficient way. Google provides the tools to do various types of A/B testing right within the platform. Taking advantage of these will help you to be more successful within the platform and provide you with insights that will help you across all of your digital marketing.
We love talking PPC and spend most of our time chatting with agencies, so if you have a question please do drop us a line!
Also, Adpulse comes with a 14-day free trial, and right now the first month is only $19.99/mth, so it’s a low-risk way to try it for yourself. Sign up now!
