When it comes to determining the overall efficiency and productiveness of a website in terms of traffic generation and conversion, there are several parameters to look for. And, that makes the entire process of filtering the Goods of the website from the Bads a very complicated task.
In comes the method of A/B testing.
A/B testing is a highly helpful way to find out what works and what doesn’t for a website in terms of its UI/UX design.
Ask any seasoned marketing professional and they’ll tell you just how important A/B testing is to improve a business.
However, as helpful as it may be, conducting the A/B test for your website design takes a lot of precision and analysis.
In today’s discussion, we are going to make your life simple by sharing simple steps to perform effective and on-point A/B testing for your business website.
Before you even begin to plan your A/B test method, you need to first identify the element that you want to analyze in your overall website design.
It could be a complicated and huge element such as a form page, or a simple and small element such as a CTA button on the homepage.
In order to get a near-precise analysis of what actually worked for your business website, it is important to isolate one independent variable and measure its performance.
Now, in order to identify that element, you need to establish a strong hypothesis* that you want to test.
*Note: It is important to understand that A/B testing is a method to test your hypothesis. As a website owner, you may have several different hypotheses about various different elements of your website design. And, it is the A/B testing that helps you establish the credibility of those hypotheses.
You can build your hypothesis on the basis of the already existing data you can avail from analytics. For example, web analytics show that users rarely click on the “Download Guidebook” button. Maybe it’s because the button is not visible enough or, because its placement is not in the right place.
So, to execute effective A/B testing for your business website, begin with picking the right element to test.
Now, once you have identified the element by creating a hypothesis, it’s time to define your end objective.
What is it that you are looking to improve from this activity?
·Is it the increasing bounce rate on your page?
·Is it the average time spent by a user on your website?
·Is it the overall website traffic?
·Is it the number of pages visited by a single user on a single visit to your website?
Define your end goal so that you can create an appropriate testing process and note down analytical changes accordingly.
The next step includes defining the appropriate sample size for your analysis.
Once you have defined your end objective and set a hypothesis to test, it is easier to measure what size of user sample you want to test.
So, let’s say you want to test the conversion ratio of visitors downloading your e-book by sending emails to them. In this case, you'll probably want to send an A/B test to a smaller portion of your list to get statistically significant results. Eventually, you'll pick a winner and send the winning variation on to the rest of the list.
However, let’s say you want to test the conversion ratio of direct visitors downloading your e-book then that would depend on the duration of your test; which brings us to our next step.
When your goal is to analyze and improve an entire website design, it requires a substantial time interval in order to obtain a substantial number of views; otherwise, it'll be hard to tell whether there was a statistically significant difference between the two variations.
With respect to theperformance of a website’s UX/UI, it may take a while for you to get enough data because of the variation in user behavior over the period of days. Users behave differently on different days of the week.
So, let’s say you want to measure the purchase result on your website. Now, it is a known fact that users do not usually make a purchase on the very first visit; irrespective of how good the website design is.
You need to give your target consumers space and time to make a rational decision so that they don’t just become one-time buyers but, long-life loyal customers.
The average recommended testing time is 10–14 days.
And, finally, it’s time to run the tests!
Once you have everything in place with regards to the A/B testing process such as the element, the objective, the time duration, etc. it’s time to put things into motion.
It is, however, important to pick the right testing tool to measure the results.
There are several effective options available for you to conduct your testing process; such as,
Go through these, and more, A/B testing tools and pick the one that fits your bill.
A/B testing helps to understand what changes on the site can bring you profit. So, make sure you are executing the process with utmost precision and a professional approach.
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