A/B testing is split-testing between two different variants – labeled A and B. This technique allows the advertiser to determine the under performing and outperforming factors of your two separate ads.

1. What is A/B
Testing?
It’s a known fact in the advertising world
that consistently successful advertising
campaigns require innovative strategies.
It’s the only way to outrank your competitors.
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A/B Testing: The Beginner’s Guide
It’s a known fact in the advertising world that consistently successful advertising campaigns require
innovative strategies. It’s the only way to outrank your competitors. However, a solid strategy won’t
guarantee better campaign results every time. This is where A/B testing comes in.
This 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.
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.

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What is A/B testing?
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.
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.

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How to Set-Up A/B testing
To run an A/B test, you need to:
• Create two separate variants of the ad you’re looking to test.
• Set and identify changes in the variables you wish to analyze.
• Set the period for testing.
• Display these separate versions to two similar types of audiences.
• Record the results over a set amount of time.
Then, depending on the performing metrics and engagements, you’ll be able to determine which ad
performed better over a set period.

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2 Strategies of A/B testing
There are two main strategies of A/B testing, which differ depending on the availability of the variants:
1. Testing Two Variants
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.

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2 Strategies of A/B testing
2. Testing Multiple Variants
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.
The purpose of this multiple variant test is to measure and record the effectiveness each combination
has on the primary goal.
A couple of problems may arise with this strategy:
• There is too much data to be analyzed.
• There is an internal conflict between the ad copy variants.
To overcome these issues, you should keep a close eye on your data to improve measurements, and also
set up a campaign experiment.

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5 Benefits of Using A/B Testing
There are many benefits to using this type of testing, such as:
• More detailed understanding of user behavior.
• Reduced bounce rates as your ads have increased relevance.
• Better audience targeting.
• Successful strategy development.
• Plenty of data to process the development of optimization strategies.

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6 Common Problems with A/B Testing
While this form of testing comes with many benefits for your ad campaign, it also has its fair share of
issues as well.
Here’s a list of six common problems you may encounter, and some advice on how to navigate these
pitfalls.
1. Inducing an Invalid Hypothesis
2. Changing the Settings During a Testing Period
3. Split-Testing Multiple Variations
4. Not Running the Test for Long Enough
5. Learn from Previous Case Studies
6. Scale the Proper Performance Measures

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6 Common Problems with A/B Testing
1. Inducing an Invalid Hypothesis
A crucial A/B testing mistake is including an invalid hypothesis on why you’re receiving specific results on
your ad copy or web page. Often, this theory rests on incorrect performance parameters. This typically
happens if you don’t measure the proper metrics for the right performance scales or goals.
For instance, let’s say that your ad copy isn’t 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.

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6 Common Problems with A/B Testing
2. Changing the Settings During a Testing Period
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’t skew the results with
any changes during testing.
Be patient, and remember that you will only be able to get a clear overview of campaign performance
after an extended period – not just one day.

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6 Common Problems with A/B Testing
3. Split-Testing Multiple Variations
This is one of the most unusual testing mistakes – and it also happens to be one of the most common.
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.
This complicates the process and makes it difficult to pinpoint the flaws or identify the outperforming
copy.

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6 Common Problems with A/B Testing
4. Not Running the Test for Long Enough
It’s 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.
Depending on your results, you’ll be free to make any new marketing decisions for improved
advertisement optimization.

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6 Common Problems with A/B Testing
5. Learn from Previous Case Studies
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.
That being said, it’s 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 specific customers, not
someone else’s.

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6 Common Problems with A/B Testing
6. Scale the Proper Performance Measures
While this form of testing is a great strategy, many advertisers still don’t have a proper grasp of what they
should measure while testing. You should develop clarity on this before split-testing.
Identify the key performance indicators before starting your process, and read up on Essential CRO
Knowledge to develop a better understanding of the parameters you should measure for various areas of
your campaign.

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Your A/B Testing Takeaway
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.
By keeping your eye out for common issues and knowing which metrics you should be measuring, you’ll
have a solid foundation from which to kickstart your campaign.

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