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A|B Testing 101: Split Testing in Google and Microsoft Ads

Have you ever wondered why your ads on Google or Microsoft aren’t getting the results you were hoping for? In today’s digital world, competition is higher than ever, making it increasingly difficult for businesses to stand out and make their voices (and USPs) heard. 

In order to stand out in an increasingly noisy digital landscape, we’ve all been tempted just to throw more money at the problem (we’re marketers, not magicians!), but there are smarter ways to boost your impact. Split testing is a fundamental method for optimising digital ad campaigns across Google Ads, Microsoft Ads, and more. Our Head of Paid Media, Jon Llewelyn, will break down how to utilise strategic A|B testing to build an effective ad strategy across your search ad platforms, as well as his top tips for best practices to ensure you’re getting the most out of your testing!

How to get started with A|B Testing Ads

To start testing effectively in both Google and Microsoft Ads, one of the most important aspects is to set clear and defined objectives that align with your overall strategy. When you know what your end goal is, such as improving your click-through rates (CTR), conversion rates, or return on ad spend (ROAS), it helps set the groundwork for a successful test. By defining your objectives early on, you not only allow yourself to set up and guide the approach to the test, but you also give yourself something to refer back to later as a benchmark, allowing you to determine the overall success of the test.

Creating Variations For Split Testing

The next step is creating your variations: create two or more versions of your ad and make sure to test only one element at a time. This could be anything from the headline, description, a visual element, or even the keywords — the choice is yours. By identifying and isolating individual variables, you can accurately determine which specific change impacts the ad’s performance and ultimately, identify what you want to keep.

Once the variations are ready, it’s time to start the test. Both Google and Microsoft Ads offer built-in tools to support users with testing, making it easier to control how different versions are displayed to audience segments. A quick tip is to ensure that each version reaches a similar audience size to maintain the test’s validity, as disproportionate tests may lead to skewed results.

Monitoring and Analysing A|B Test Results

Monitoring and analysing the results of your test is where the real insights emerge. It’s important to pay attention to KPIs you identified as key indications, such as CTR, CPC, etc…, to assess the performance of each ad version. Detailed analysis will help you understand user behaviour and preferences, which can then be used to refine your advertising strategies. For example, this means you can determine if Headline A helped increase CTRs compared to Headline B.

Implementing Findings to Optimise Your Campaigns

Finally, it’s time to implement the findings from your A|B tests to optimise your campaigns! The insights gained from these tests are invaluable in making data-driven decisions that enhance ad performance. Continuously applying these learnings will improve your advertising efficiency and effectiveness over time and the best part: it’s a never-ending process! There’s always something to trial and test in the ever-changing world of digital marketing. What works well during one month or season may change in the next – but that’s what keeps things interesting, right?

Benefits of Testing in Google Ads and Microsoft Ads

Running A|B tests within Google and Microsoft Ads offers a number of different benefits. Most importantly, it allows you to optimise ad performance by identifying the most effective ad elements that resonate with your target audience, which is applicable across every industry. This leads to improved conversion rates as you gain a deeper understanding of what drives user behaviour.

Additionally, testing helps improve cost efficiency. By focusing on high-performing ad variations, you can allocate your budget more effectively, reducing wasted spend (a universal goal for us marketers!). On top of this, it enhances user experience by allowing you to test different creatives and landing pages, creating a more personalised and engaging interaction for users and increasing user satisfaction.

Lastly, testing supports data-driven decisions, providing concrete data to inform your marketing strategies, and ultimately reducing reliance on guesswork.

Leveraging A|B Testing for Maximum Benefit

To maximise the benefits of A|B testing in both Google Ads and Microsoft Ads, consider the following the below best practices:

  • Test One Element at a Time: Changing only one variable at a time ensures that you can accurately identify what influences performance.
  • Use Meaningful Metrics: Focus on KPIs that align with your overall business or campaign goals, such as conversion rates, CTR, and ROI.
  • Run Tests for Sufficient Duration: Allow your tests to run long enough to gather a significant amount of data. This helps in making more accurate and reliable conclusions. Anything longer than 2 weeks is ideal — any less than this and the ads will likely still be in the learning phase.
  • Analyse and Learn: Thoroughly analyse the test results to understand user behaviour and preferences. You can then use these insights to influence your approach to any future activity.
  • Continuous Testing:  A|B testing should be an ongoing and continuous process. Regularly test your ads to keep improving performance over time to ensure you’re being as proactive as possible.

Why should I implement A|B testing?

A|B testing can be a really powerful tool for optimising your digital advertising campaigns on platforms like Google and Microsoft Ads. By systematically testing different ad elements and analysing your results, you can make more data-informed and driven decisions that improve ad performance, increase conversion rates, and maximise your ROI. Incorporating A|B testing into your advertising strategy ensures that you are continuously learning and adapting, leading to sustained success in your digital marketing efforts. By following best practices and leveraging advanced techniques such as audience segmentation, machine learning, multivariate testing, and cross-channel testing, you can further refine your strategy and achieve even greater results.

Jon Llewelyn, Head of Paid Media at Arke.

Jon leads our Paid Media team and is responsible for managing, developing, and implementing paid media strategies for our clients. With a strong understanding of in-house processes, operations, and data utilisation, he is well-equipped to personalise and customise his approach to meet each client’s unique needs.

Our Head of Paid Media at Arke, Jon Llewelyn, has written his top tips and insights into implementing A|B testing in your paid media strategy.

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