A/B Testing & Conversion Optimization

Hey Everyone, thank you for tuning into this week's blog post. This week is going to be a busy one! #WFH summer quarter is in full effect. For those of you who read my last blog, I am happy to announce that I have received my Google Analytics Certification.

Looking forward to the week, I will be uploading three blog posts for #WWUDIGIMARK. The first blog to start the week off with a bang is about A/B Testing & Conversion Rate Optimization, followed by Inbound and Content Marketing. The final blog to end and wrap-up the week will revolve around Organic Social Media.

A/B Testing

What is A/B Testing?

A Split test known better as an A/B test is the process of showing two variations of the same webpage or interface to different consumers at the same time. The purpose behind showing different copies is to compare both interfaces to identify which variant drives a higher conversion.

Think about an A/B test as a simple science experiment. If you recall back to your science class experiments should generally consist of three variables:

• The Controlled Variable
• The Manipulated Variable
• The Responding Variable

Concerning the A/B test, the controlled variable would be the current webpage or interface (A). The manipulated variable would be the variant modified from the website or interface (B). The responding variable is what happens as a result of the experiment. Did conversion increase? Decrease? Stay the same?

How Does It Work?

You may still be asking yourself how does A/B testing work. In general, you take an interface and manipulate it to create a second version of the same page. The changes made can range in difficulty. In some cases, the only modification made is that of a button or color. In other instances, the magnitude of the change can be as significant as redesigning the interface. Once the changes have been complete half of the traffic will view the original interface while the rest will view the modified version.

Support the change with Data

As mentioned in my previous blog, choices should be enforced by supporting data. No longer must you rely on that gut feeling to make an important decision. A/B testing tracks and analyzes the consumer experience on both the controlled and modified webpage to determine which had a positive outcome.

A/B test is used to optimize companies' interface to lead to higher conversion rates. The test can be used multiple times to advance a goal. It’s important to note that testing one change at a time helps identify which changes had effects on consumer’s behavior. Accumulating the positive changes and integrating them into the interface will lead to positive consumer interaction. 

The A/B Process

Before you jump straight into A/B testing companies and individuals must understand the framework behind the process. There are six crucial steps you can use to start running the test:

• Collecting Data: First off, you must collect data from your webpages to understand the potential. The insight will help you identify what needs improvement.
• Identify Goals: To identify goals you must use the appropriate key performance indicators (KPIs) and metrics for your industry. The purpose of a goal is to determine whether or not the variation is successful.
• Create a Hypothesis: A hypothesis consists of ideas for why you think particular changes will be better than the original version. Once you have generated a list of ideas, prioritize them in terms of expected impact and difficulty.
• Create Variations: Use software to make preferred changes to the interface. Now there are two copies of the same webpage that can be compared against each other. The differences are based on the research conducted previously.
• Run Experiment: You are finally ready to start the experiment! During this phase, you just wait for consumers to interact with your interface. Consumers will be randomly assigned to either the controlled or manipulated webpages.
• Analyze Results: Once the test reaches the end, we can compare both versions of the webpages. Using the goals previously laid out, you can identify whether or not the variation was a success.

Even though you have finished the A/B test, you can start to generate a new round. Using the test multiple times only helps to further optimize the webpage or interface.

Don’t Forget About CRO

A key metric to consider when conducting an A/B test is your conversion rate optimization (CRO) goals. CRO is used to create a pleasurable experience for consumers. In other words, CRO helps improve the functionality of a website. Creating a user-friendly website would help drive conversion.

In today’s age, consumers who find webpages hard to navigate will most likely leave and never come back. It is important to get consumers within the conversion funnel in the first interaction to get the desired action. CRO is a non-stagnant process which means that it’s an ongoing process of learning and improving.

Big Picture Idea

A/B testing and the CRO metric work hand in hand to create a pleasurable experience for consumers. Many companies have combined the two forces to fulfill their desired goal. For example, in 2008, the Barrack Obama Presidential campaign used the test to increase donations towards the campaign. The simple rewording of the “Sign Up” button to “Learn More” saw a 40% increase in sign-up rates. The increase conversion “resulted in an additional 2.8 million email addresses which ultimately led to $60 mission in donations.”

Knowing the proper frameworks to apply will lead to a much more successful marketing effort. Basing decisions solely on instincts may not always lead to the desired outcome, but when backing those instincts with data, the decision is easier to make. Conducting A/B testing and looking at the CRO metric goals will help you understand the target market’s needs and behavior to better optimize your webpages and marketing efforts.