A/B Testing: Definition and Functions for Website

For a marketer, they need to know that after creating a website, they still have to make sure all the elements work together without problems to provide the most optimal user experience. A/B testing is one way to find out.

Implementing A/B testing will help businesses find the best online promotion and marketing strategy. When testing is done, you can find out which parts to eliminate and which parts to optimize. Therefore, this method is very useful for increasing the conversion rate, a crucial metric for assessing business growth.

see Hadehana's explanation of the definitions, functions, and elements in the following A/B testing!

What is A/B Testing?

A/B testing, or often also called split testing, is the process of comparing two versions of a website page, email, ad, or other digital asset to determine which one is more successful.

Generally, the best results in the AB test are associated with increasing the conversion rate. So, which page converts higher.

There are several elements you can test with A/B tests such as:

• Logo
• Banners
• Ad placement
• Button
• Content
• footers
• Page layouts
• Widgets
• Call-to-Action

Both the mobile and web versions of these elements will be treated the same so you don't have to worry about the results being different or being influenced by certain factors.

ab testing example

To make it easier to understand, here is an ab testing example conducted by Hubspot. Here Hubspot tests the Search Bar elements from a visual and functional standpoint to optimize their website.

For variant A, Hubspot upped the visual and changed the placeholder text to "search by topic".

As for the B variant, Hubspot upped the visual and changed the placeholder text to "search the blog".

After testing, the result is that all variations increase the conversion rate. However, variant B saw a 3.4% increase in conversion rate and a 6.46% increase in users engaging in the Search Bar.

The data obtained after testing can help marketers choose which version of the content gives the most results. 

When marketers have the best version of content in their hands, a lot can be achieved. One of them is cost efficiency in paid marketing campaigns, such as advertising on Google Ads, Facebook Ads, etc

A/B testing function

With A/B testing, businesses can find out what works and what doesn't because it is accompanied by supporting data. From here, it is easier for companies to make decisions and develop digital marketing strategies that are more effective in the long run.

1. Increase Website Traffic

Testing multiple formats of split testing a website's pages can show which one attracts more clicks. Thus, you can follow the format in the tested format to increase traffic consistently.

2. Increase the Conversion Rate

A/B testing can encourage website visitors to follow the call-to-action (CTA) that you have made. You can find out what kind of CTA suits them.

Then, you can get more subscribers, purchases, customer data, and whatever else you include in your CTA.

3. Lowering the bounce rate

By doing A/B testing, you can find out the copywriting, anchor text, to the design according to what the customer wants. Thus, they will stay longer on your site.

4. Follow the trend

consumer behavior is always changing, A/B testing which is carried out regularly can provide the business with the latest data.

A/B Testing Tools

There are many tools that can be used for A/B testing. Here are some examples:

Hubspot's A/B Testing Kit

Hubspot's A/B testing kit has easy-to-use spreadsheet templates and guides. In addition, there is also a built-in calculator to calculate the success of the experiments that have been carried out.

Optimizely

Optimizely has the main advantage, users can carry out many experiments simultaneously without limit. Therefore, Optimizely is often used not only by the marketing team, but also by the product team and engineers.  

Oracle Maximiser

Oracle Maxymiser helps businesses perform advanced website testing. With this tool, businesses can create the most effective websites and mobile apps for generating conversions. Apart from that, Oracle Maxymiser can also be used to run multivariate testing. An explanation of the difference from A/B testing can be read in the FAQ section of this article. 

VWO

VWO can also be used for A/B testing and multivariate testing. VWO has strong integrations that allow users to enter data into external tools to connect different platforms. With this integration feature, users can simplify the testing process because the data is centralized in the VWO. 

The steps to start A/B Testing are:

Here are some steps for you to run A/B Testing:

• Collect as much data as possible. Then analyze the data that has been collected to find out which parts can be optimized. Pay attention to data when traffic is high or low. With that, low conversion rates can be increased.
• Next identify the goals in running A/B Testing. Goals can be the number of clicks, the number of sign-ups, product purchases, and others.
• Choose a metric to determine whether the variation you tried succeeded in increasing the conversion rate or not.
• After having clear goals, make ideas and also hypotheses from A/B Testing to find out why the latest variation will be better than the original or previous version. Once you have a list of ideas, prioritize them based on the expected impact and difficulty in implementing them.
• Now it's time to make changes in the A/B Testing tool. There are 3 common tools used in A/B Testing: Optimizely, VWO, and Google Optimize. Google Optimize is free. It is fully featured and integrated with Google Analytics.

Make desired changes to the site such as changing the color of the buttons, changing the layout, navigation, etc. Many of the leading A/B testing tools have visual editors that make changing these elements easy. An example is Optimizely.

• Then use these design variations within a certain timeframe, in order to get the number of visitor numbers as a sample. The A/B Testing Tool will display several variations of the modified web page. Visitors who log in at the same time will be presented with a different web page.
• When enough data has been collected, the A/B Testing tool will report changes in the conversion rate on each different page. If there are significant positive changes, now is the time to decide whether to apply the results of A/B Testing or not. But if the opposite happens, don't worry, use A/B Testing as a learning experience and generate new hypotheses that can be tested later.
• When you find a variation that shows a positive trend, try to identify why that variation is working. The only positive results obtained are the benefits of A/B Testing. Another benefit is increasing work efficiency in the future with better tests.

Conclusion

A/B testing compares the performance of two versions of elements (such as headlines, images, and designs) to see which appeals more to audiences. This strategy tests version A against version B to gauge which works best against key business metrics.

By using testing and collecting empirical data, businesses can know exactly which marketing strategies work best for the company.