A/B Testing- Meaning and Its Role in Digital Marketing

What is A/B Testing?

• A/B testing (also known as split testing) is the practice of showing two variants of the same web page to different segments of visitors at the same time and comparing which variant drives more conversions because different audiences behave differently.
• So this does not mean that something that works for one company may work for another also.
• A/B Testing allow you to compare 2 versions of something so that you in future you will able to know which is more effective.
• A/B tests can also be complex in way that you are not perform this testing carefully or you make incorrect assumptions about what people like and what makes them click this can degrade your other strategies performances so while performing A/B testing you must be careful about its various aspects.
• A/B Testing is famous for creating PPC models.

Where does A/B Testing works?

When it comes to customer-facing content A/B Testing can be done on-

• Individual emails
• Multimedia marketing strategies
• PPC
• Newsletters
• Website design
• Email campaigns

If you are testing website design then A/B Testing may help you in-

• Color scheme
• Layout
• Number and type of images
• Headings and subheadings
• Product pricing
• Special offers
• Call-to-action button design

How to perform A/B Testing?

1. Research-

• Build an A/B testing plan, one needs to conduct thorough research on how the website is currently performing.
• You have to follow some metrics which may includes questions like "How many user are visiting on site", "Which pages drive most traffic", "What are the conversion goals of different pages" and many more like these.
• Online tools such as Google Analytics will help you to figure out the answer of these questions.

2. Identify Goals-

• When metrics has been collected then identify the goal.
• For example- Your goal is to achieve target of 1 lakhs download in  days.
• These types of goals are made in this section.

3. Generate Hypothesis-

• This means you have create hypothesis that the goal you set is achievable or not .

4. Create Variations-

• The next step in your testing program should be to create a variation based on your hypothesis.
• A variation is change in the current version that you want to test. 

5. Run the experiment-

• After creation of the variation run the experiment. 
• You should not conclude the results in 2 or 3 days wait for atleast 15 to 20 days to get proper results.

6. Analyze the results-

• After 15 to 20 days of experiment you will be able to know the variation was beneficial for the current version or not.
• You have to compare the data of the current version and the data of the variation then you must conclude the results.
• You can analyze the results by using Google analytics tool.