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<\/div>\nThis form of testing and analysis allows you to scale the potential outcome of newly implemented strategies. It can also be used to highlight the best performing ads within your campaign.<\/p>\n
In this article, we delve deep into A\/B testing to see how you can use it in your next ad campaign to improve your results.<\/p>\n
What is A\/B testing?<\/h2>\n
A\/B testing is split-testing between two different variants – labeled A and B. This technique allows the advertiser to determine the underperforming and outperforming factors of your two separate ads.<\/p>\n
By taking conversion rates and other metrics into consideration, this testing allows you to figure out which ad, or element, is the most effective in driving your goals.<\/p>\n
How to Set-Up A\/B testing<\/h2>\n
To run an A\/B test, you need to:<\/p>\n
- \n
- Create two separate variants of the ad you\u2019re looking to test.<\/li>\n
- Set and identify changes in the variables you wish to analyze.<\/li>\n
- Set the period for testing.<\/li>\n
- Display these separate versions to two similar types of audiences.<\/li>\n
- Record the results over a set amount of time.<\/li>\n<\/ul>\n
Then, depending on the performing metrics and engagements, you\u2019ll be able to determine which ad performed better over a set period.<\/p>\n
2 Strategies of A\/B testing<\/h2>\n
There are two main strategies of A\/B testing, which differ depending on the availability of the variants:<\/p>\n
1. Testing Two Variants<\/h3>\n
This is the standard A\/B testing strategy. Through this, advertisers split-test two separate options during the testing process. This strategy involves some pros and cons, which we will outline later in this article.<\/p>\n
2. Testing Multiple Variants<\/h3>\n
This type of A\/B testing uses the same underlying mechanisms of the two variants method. However, this strategy allows you to compare more variables to gain more information on how they interact together.<\/p>\n
The purpose of this multiple variant test is to measure and record the effectiveness each combination has on the primary goal.<\/p>\n
A couple of problems may arise with this strategy:<\/p>\n
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- There is too much data to be analyzed.<\/li>\n
- There is an internal conflict between the ad copy variants.<\/li>\n<\/ul>\n
To overcome these issues, you should keep a close eye on your data to improve measurements, and also set up a campaign experiment.<\/p>\n
5 Benefits of Using A\/B Testing<\/h2>\n
There are many benefits to using this type of testing, such as:<\/p>\n
- \n
- More detailed understanding of user behavior.<\/li>\n
- Reduced bounce rates as your ads have increased relevance.<\/li>\n
- Better audience targeting.<\/li>\n
- Successful strategy development.<\/li>\n
- Plenty of data to process the development of optimization strategies.<\/li>\n<\/ul>\n
<\/p>\n
6 Common Problems with A\/B Testing<\/h2>\n
While this form of testing comes with many benefits for your ad campaign, it also has its fair share of issues as well.<\/p>\n
Here\u2019s a list of six common problems you may encounter, and some advice on how to navigate these pitfalls.<\/p>\n
1. Inducing an Invalid Hypothesis<\/h3>\n
A crucial A\/B testing mistake is including an invalid hypothesis on why you\u2019re receiving specific results on your ad copy or web page. Often, this theory rests on incorrect performance parameters. This typically happens if you don\u2019t measure the proper metrics for the right performance scales or goals.<\/p>\n
For instance, let\u2019s say that your ad copy isn\u2019t receiving enough clicks based on its impressions. This is more likely an issue dealing with the relevancy factor between your target audience and bidding keywords. Advertisers may get this mixed up with the bidding prices and choose to increase their bids instead, resulting in wasted spend.<\/p>\n
2. Changing the Settings During a Testing Period<\/h3>\n
Editing or changing your test variation settings when the test is running is a wrong move, as it undermines the credibility of your test. It requires consistent data, so you shouldn\u2019t skew the results with any changes during testing.<\/p>\n
Be patient, and remember that you will only be able to get a clear overview of campaign performance after an extended period \u2014 not just one day.<\/p>\n
3. Split-Testing Multiple Variations<\/h3>\n
This is one of the most unusual testing mistakes – and it also happens to be one of the most common.<\/p>\n
When advertisers try to split-test too many items within a single test, thinking it may be a time-saver, they end up running into problems, ultimately misunderstanding which change is responsible for the results.<\/p>\n
This complicates the process and makes it difficult to pinpoint the flaws or identify the outperforming copy.<\/p>\n
4. Not Running the Test for Long Enough<\/h3>\n
It\u2019s vital you run your A\/B test for a certain about of time to achieve mature and concrete data. This time allows your ad copy to develop accurate results.<\/p>\n
Depending on your results, you\u2019ll be free to make any new marketing decisions for improved advertisement optimization.<\/p>\n
5. Learn from Previous Case Studies<\/h3>\n
While gaining inspiration from case studies is an excellent idea, you should be aware that what worked for another advertiser may not work for you.<\/p>\n
That being said, it\u2019s better to use case studies as a starting point for creating your testing strategy for your unique ad campaign. This will help you determine what works best for your<\/strong> specific customers, not someone else\u2019s.<\/p>\n
6. Scale the Proper Performance Measures<\/h3>\n
While this form of testing is a great strategy, many advertisers still don\u2019t have a proper grasp of what they should measure while testing. You should develop clarity on this before split-testing.<\/p>\n
Identify the key performance indicators before starting your process, and read up on Essential CRO Knowledge<\/a> to develop a better understanding of the parameters you should measure for various areas of your campaign.<\/p>\n
Your A\/B Testing Takeaway<\/h2>\n
A\/B testing can help you create a more accurate and successful ad campaign, as long as you understand what to look for and how to implement these strategies.<\/p>\n
By keeping your eye out for common issues and knowing which metrics you should be measuring, you\u2019ll have a solid foundation from which to kickstart your campaign.<\/p>\n","protected":false},"excerpt":{"rendered":"