A/B Testing

by hammad.usmaniJune 13, 2016

A/B testing is also called the A/B split testing, a method that provides you the comparison of two versions e.g. (A or B) to determine which one is better and engage more and more users. A/B testing is a fantastic method that allows you to track which of your design is more effective to better your conversion rate. It allows you to design the best strategies for your business and it provides marketing plans for your business.

A/B testing methods can be used to track everything on your site whatever is going on, you may track the interest of the user, the movement on your site, the attractive objects on your page, and how users are interacting with your site and what is the best that attracts your user.

So you may easily compare your design to make a better result and your conversion rates.

In A/B testing you have two options, either A or B.

It compares two designs and provides you the results that which one is better than the order, what are the results of the variations and which one you should apply to your application.

How it works:

For A/B testing you choose one of the web pages and re-design it that's different from the first one, this change could be a large difference or a very minor change like the text changes, button position changes, color combination differences, and so on.

The A/B testing provide you the result as a Control and the Variation, in this scenario half of your traffic on that page will be redirected to the Design A and half will be to Design B.

So after the implementation of your variations you can easily judge what is going on, and how the users are engaging with your web page. You can analyze the data using any analytical dashboard and the data (control & variations) could be analyzed like this:

IMAGE: Optimizely.com

General best practices for A/B testing:


For every test whatever you are going to do is based on some Hypothesis. The hypothesis defines what you are going to do, and what you want to prove so the hypothesis should include the testing variable and the success metric that determines the winner.

For example your hypothesis is “A quote on the landing page will increase conversion rate, so it defines the parameters of your test, focuses on your test variable, and finally the results/output. Create a document and write it down as a title for your document.

Testing Variable:

You should be clear about that what you are going to test, it should be clearly defined in your hypothesis. A/B testing is the comparison between the two so the testing variable should be only one and all the other assets should remain constant, if you are testing two variables/variations at the same time so you can not conclude a perfect conclusion on the data because as you will not aware that which effects better. So the best practice is to test a single variable at a time and conclude that either it works or not.

Goals & Success metric should be clear:

You must be clear about the goals whatever you are going to and want to achieve, it should be clear and predefined how you are going to conclude the result, what are the rules and parameters so on that basis you will conclude the result.

If you are following the best practices and testing a single variable so it should be clear what you want to achieve by using that variation and stick to that until you get your final result.

Sample Data and Statistical Significance:

For a perfect output and proper results your data should be significant enough so on that basis you may conclude a better result. If the data is too small then you can not conclude a better result. Your data should be enough and properly targeted according to your target market.

Test Data by Grouping and Splitting:

Once you have collected enough data so now you can do the grouping of your data like you can split your data into different proportions and can achieve a better result.

Focusing user experience:

You must have to focus on the user experience on your site, you have to think and track how the user feels on your site and why he/she should remain on your site, do signups, subscriptions, and other activities whatever your site is providing.

As Neil Patel states:

"Any emotion can drive conversions. A user might convert because they are happy, sad, jealous, or downright furious. But the really important thing is why they are feeling that way."

Manage tracking pixels properly:

Check and make sure that you are tracking properly what people are exactly doing on your site, what are the most interesting things for them and which is enhancing your conversion rates, and so on.

Do Testing & common sense

A lot of things are predefined and should not be tested, you can not even test each and everything on your site. So for all such things you may use common sense, what will be the effect and how should I implement all other objects? And the things in which you are confused about perfect results so you may do the A/B testing using every single variable at a time.


This is the step where we lack and neglect it but it has a lot of importance in any process, if you are documenting properly so you must be following the rules that what are your success metrics, what the hypothesis is basically, and what is going to be your testing variable. You will be clear about your target markets and the goal you have to achieve so this is very important to do so to stick to your goals.

Online Available Testing tools:

You may analyze all your results and can make a decision very precisely and easily by using any of the following online tools.


So the A/B testing provides the chance to compare and choose the best on the basis of collected data and analysis. By proper implementation of the A/B testing by following the best practices you can make your site better, can improve the weak areas where users do not stay anymore, can make it more attractive, and attain the user's attention. This all will increase your site traffic and conversion rates. You may apply the A/B test on any confusing part in which you are confused that either I choose A or B, it gives you the chance of proper implementation of what is best for you.


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