Guide to instantly improve your ads

Ad Testing 101: A Beginner’s Guide To Instantly Improve Your Ads

Ad Testing Strategies for Success

Welcome to the world of digital advertising, where creating and running ads is just half the battle. The other half is ensuring that your ads are performing as effectively as possible, and that’s where ad testing comes in.

If you’re new to ad testing, don’t worry – this beginner’s guide will provide all the information you need to get started. We’ll cover the basics of different types of ad tests, setting goals and metrics, designing effective ad tests, conducting tests, interpreting results, and using tools and resources for ad testing.

So, whether you’re a business owner, marketer, or advertiser, this guide is for you. Get ready to learn the ins and outs of ad testing and take your advertising campaigns to the next level.

Types Of Ad Tests

Ad testing is comparing different versions of an ad to see which one performs better. There are different types of ad tests, each with its benefits and drawbacks. Here are three common types of ad tests:

A/B Testing

A/B testing, also known as split testing, involves creating two versions of an ad that differ in only one variable, such as the headline or the image. The two versions are then shown to a random sample of your target audience, and the version that performs better is used for the rest of the campaign. A/B testing is a simple and effective way to test ad elements, but it doesn’t consider interactions between variables.

Multivariate Testing

Multivariate testing involves testing multiple variables in a single ad. For example, you might test different headlines, images, and calls-to-action combinations. Multivariate testing can provide more comprehensive insights than A/B testing, but it can be more complex to set up and analyse.

Split Testing

Split testing is similar to A/B testing but involves testing two different ads instead of just one variable. This type of test can help you determine which ad concepts work best for your audience, but it requires a larger sample size and may take longer to run.

Setting Goals & Metrics

Goals & Metrics, ad testing

Before conducting any ad tests, setting clear goals and metrics to measure success is important. This will help you determine whether your ad tests effectively achieve your advertising objectives. Here are some steps to follow when setting goals and metrics for ad testing:

Identify Your Advertising Objectives

First, determine the purpose of your advertising campaign. Are you trying to increase brand awareness, generate leads, or drive sales? Your advertising objectives will influence the type of ad tests you conduct and the metrics you use to measure success.

Choose Metrics To Measure Success

In addition to setting goals, choose metrics that will help you measure success. For example, if you’re testing different versions of a landing page, you might measure the conversion rate, bounce rate, and time on the page. Ensure your metrics are relevant to your advertising objective and aligned with your goals.

Set Realistic Expectations

When setting goals and metrics, it’s important to set realistic expectations. Don’t expect your ad tests to result in a 100% increase CTR overnight. Instead, set incremental goals that are achievable and align with industry benchmarks.

Monitor & Adjust

Finally, monitor your ad tests and adjust your goals and metrics. If a test isn’t performing as expected, don’t be afraid to adjust your goals or metrics to better align with your advertising objectives.

Designing Your Ad Tests

Ad Tests

Designing effective tests that can provide actionable insights is important to get the most out of your ad testing. Here are some steps to follow when designing your ad tests:

Define Your Test Variables

First, determine which variables you want to test. This could include ad elements such as headlines, images, calls to action, or even the overall ad concept. Be sure to choose variables that are relevant to your advertising objectives.

Create Your Test Variations

Once you’ve identified your test variables, create variations of your ad that differ in those variables. For example, if you’re testing different headlines, create two versions of your ad that differ only in the headline. Be sure to create enough variations to ensure statistical significance.

Determine Your Sample

You’ll need to determine your sample size to ensure your ad tests are statistically significant. This is the number of people who will see your ad variations during the test. The sample size should be large enough to ensure reliable results but not so large that it becomes prohibitively expensive.

Decide On A Testing Methodology

Next, decide on a testing methodology. As discussed earlier, A/B, multivariate, and split testing are viable options depending on your goals and resources. Choose the methodology that best aligns with your objectives.

Set Your Test Duration

Finally, set the duration of your test. The length of your test will depend on the size of your sample, the complexity of your test, and your advertising objectives. Generally, you’ll want to run your test long enough to ensure statistical significance but not so long that it becomes cost-prohibitive.

Conducting Ad Tests

Once you’ve designed your ad tests, it’s time to conduct them. Here are some steps to follow when conducting your ad tests:

Launch Your Ad Variations

First, launch your ad variations to your test audience. This could be a subset of your overall target audience or a particular test audience. Launch your ad variations simultaneously to ensure external factors don’t skew your results.

Monitor Your Metrics

Once your ad variations are live, monitor your metrics closely. Depending on your testing methodology, you may need to track different metrics to determine statistical significance. For example, if you’re conducting an A/B test, you’ll want to track each variation’s CTR, conversion rate, or other relevant metrics.

Interpreting Results & Taking Action

Interpreting the results of your ad tests can be challenging, but it’s crucial to make data-driven decisions based on the insights you gather. Here are some steps to follow when interpreting your ad test results and taking action:

Identify Key Insights

Next, identify key insights from your ad test results. This could include which specific ad elements or concepts performed better, which audience segments responded better to each variation, or which channels drove better performance.

Make Data-Driven

Use your insights to make data-driven decisions about your advertising campaigns. This could involve implementing the winning ad variation, further testing variations, or optimising your overall advertising strategy based on your insights.

Continue Testing

Ad testing is an ongoing process, and you may need to continue testing and optimising your campaigns over time. Regularly reviewing your results and making data-driven decisions can help you continuously improve your advertising performance.

Monitor Performance

Finally, monitor the performance of your campaigns to ensure that your changes are driving the desired results. This could involve regularly reviewing key metrics such as CTR, conversion rate, or ROI and adjusting as needed.


In conclusion, ad testing is crucial to any successful advertising campaign. By systematically testing different ad variations, you can gain valuable insights into what resonates with your audience and optimise your campaigns to drive the best results.

Throughout this beginner’s guide to ad testing, we’ve covered various topics, from setting goals and metrics to designing and conducting your tests, interpreting your results, and taking action based on your insights.

While ad testing can initially seem overwhelming, it’s important to remember that it’s ongoing. By continuously testing and optimising your campaigns, you can stay ahead of the curve and drive the best possible results for your business.

Whether you’re just getting started with ad testing or looking to take your campaigns to the next level, staying focused on your goals, gathering and analysing data effectively, and making data-driven decisions based on your insights.

By following these principles, you can drive more effective advertising campaigns, build stronger connections with your audience, and ultimately achieve greater success for your business.

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How long should I run my ad tests?

The time you should run your ad tests will depend on your testing methodology and goals. You should run your tests long enough to gather statistically significant results.

How often should I conduct ad tests?

Ad testing is an ongoing process, and you should conduct tests regularly to stay ahead of the curve and optimise your campaigns for better performance. The frequency of your tests will depend on your specific goals and resources.

Can ad testing help me save money on advertising?

Yes, ad testing can help you save money on advertising by helping you identify which ad variations are most effective and eliminating underperforming ads.