Designing a digital product brings about various uncertainties: Which font reads best? What CTA converts more? The vast selection of possibilities to choose from can give brands a headache. It is true that following best practices and intuitions is a good place to start but it won’t take you far in a brand setting and a bad design choice can negatively impact your revenue. So what should you do and where do you get them from? Use A/B testing. Continue reading to learn about it.
What is A/B Testing?
A/B testing also known as split testing or bucket testing compares two versions of a product, web page and app against each other to find which performs better it’s a quantitative way of finding the optimal version of your work. In other words, A/B testing is an experiment where two options are shown to users at random and after that marketers and designers use statistical analysis to find which variation works better for their outcome goals.
Why is A/B Testing Important in UX UI Optimization?
As stated A/B testing plays a crucial role in understanding user behaviour and meeting the needs of the target audience. Here are some reasons why A/B testing is important in UX UI optimization.
Evaluating and Analyzing Needs
A/B testing helps brands and designers to understand the needs of the audience. By dividing users into two groups and letting them interact with different designs, researchers and designers gain a deeper understanding of their behavioural patterns.
Empowering the Design Process
A/B testing in UI UX empowers the design process by allowing users to express their design decisions. When users interact with different versions and give feedback their opinions influence the design choices. This ensures that the target audience’s needs are considered which results in more user-centric designs.
Choosing the Best Features
Comparing the two versions of the designs through A/B testing in UI UX helps identify the pros and cons of each version. This helps brands and designers select the best features from each version, creating a final design that meets the majority of user needs.
A/B testing removes the assumptions from UI UX designs and directly measures the impact of any changes you make so that you can ensure you are creating an optimal result. In the long run, A/B testing saves companies money especially if they conduct it in the design phase. Testing often intercepts mistakes or unsatisfactory designs before they have invested in development.
Even after a product has been launched you can still conduct A/B testing. It helps brands and designers find out what users want, optimise and iterate.
You might want to conduct A/B testing for these reasons:
- To resolve design team conflict
- Get quantitative data about your designs
- Make user-focused decisions
- Find which UI elements work best
- Iteration
- Find out how a small change affects user behaviour
- Improve user experience
- Optimise conversion rates
What Elements Can You A/B Test?
Your website’s conversion funnel determines the outcome of your business. Therefore every piece of content that reaches your target audience through your website must be optimized to its maximum potential. This works especially for elements that have the potential to influence the behaviour of website visitors and business conversion rates.
For example, you might change the size and colour of one button, the location of one submission box, the CTA copy on one button…You got the idea to test only one variable.
You may want to consider testing things that will have a big impact on user experience or you don’t have enough data to understand. Some of the elements you might want to test.
Headlines
A headline is practically the first thing that a visitor sees on a webpage. When it comes to testing consider playing around with the emotional feel of the wording. You might try a headline that calls up urgency or one that encourages curiosity. Similarly experimenting with the length of headlines can improve performance, shorter headlines are generally strong and a longer headline can convey more information and potentially draw the reader’s attention.
You can try other approaches when testing your headline:
- Try a longer vs shorter headline
- Convery negative and positive emotions
- Ask a question in your headline
- Make a testimonial part
- Try different value propositions
Call To Action (CTA)
The CTA is where all the real actions take place. On a webpage, your call to action is a button that shows your page’s conversion goals. You can the CTA copy, the design of the button and its colour and so on to see what works best. Such experimentation helps understand which variation has the potential to get the most conversions.
Hero Sections
A hero section is the main image that appears on the folding on the webpage. It shows your product and your service being used in the real-life context but how do you know what hero section will convert for which landing page?
Test and find out different imagery styles such as photography and illustrations to understand which one resonates with your audience. Similarly experimenting with the size and orientation of the image as well as playing around with the colour schemes can induce different emotions and set a specific tone.
Insider Tip: Just like your headline and supporting copy the hero section is subject to message match. If your ad shows mattresses, but your landing page’s hero section shows a rocking chair, then you have likely got a mismatch.
Lead Forms
Forms are mediums through which prospective customers get in touch with you. Depending on your business you more than just a name and an email, but the number of fields can be a crucial factor in user engagement. You might test a form with only essential fields in case of one with additional, optional fields to evaluate your visitor’s willingness to provide more information.
Copy
For the copy of your campaign, you might consider testing different writing styles. For example, a conversational tone might resonate with your audience than a formal tone. Experiment with the inclusion of bullet points or numbered lists to enhance readability and engagement. A shorter copy is usually better but for a certain product and markets, a detailed copy is important in the decision-making process.
Layout
Because everything seems so essential, brands sometimes struggle with only the most essential elements to keep on their website. With A/B testing this problem can be resolved permanently. You might try a that emphasizes visual elements over text or vice versa to see which is more effective.
Insider Tip: if you want to try with layout, move one thing at a time and keep all the elements on the page as it is. Otherwise, it will be difficult to separate the changes that work.
How To Conduct A/B Testing Appropriately?
A/B testing offers a very systematic way of finding out what works and what doesn’t in any given marketing campaign. A structured A/B testing program can make marketing efforts more profitable by identifying the most crucial problem areas that require optimization. Learn how to conduct A/B resetting step by step:
Step1: Set a Goal
Before conducting your test you need to know why you are running the test. Set a goal that you want to achieve. That way you understand which version to continue testing. Make sure you gather any data before you test so that you can measurably see changes.
Examples:
- Improve conversion rates with newsletter letter sign-ups
- Get more responses
- More shares
Step 2: Determine What to Test
Think about the goal you want to achieve. Consider what single feature of your design you could change to get closer to that goal. For a list of ideas scroll back up to “What to A/B test”.
Examples:
- Shift the newsletter box to the middle of the blog posts
- Reduce the number of questions in the form
- Increase the size of the social media share button
Step 3: Develop Your Hypothesis
Based on the data you know your team will have available. You will now want to identify the opportunities for your experiment and map out a theory about how the user will react to a specific element of your product.
Example: You might assume that the user will want the steps required to complete a task using your new feature to be ordered in a particular sequence. That’s your hypothesis.
Step 4: Run Your Test
Now it is time to send the different versions of your new features to various segments and wait to see how the group responds to each version. Your team will need to determine how long to run your A/B test how much data to collect etc. because this will vary for each company.
The duration of your test can depend on things like your type of business, the size of your audience and the specific element being tested. Make sure to calculate your A/B test size and duration to ensure your findings are accurate.
Step 5: Analyse Your Results and Deploy Changes
Even though this is the last step in finding your campaign winner, analysis of the result is extremely important. Because A/B testing calls for continuous gathering and analysis, it is at this step that your entire journey resolves. Once your test is completed analyse the results by considering standards like percentage increases, confidence level, direct and indirect impact on other metrics. After you have considered these numbers if the test is fine, deploy the winning variations. If the test remains unresolved, draw insights from it and implement these in your upcoming tests.
Types of A/B Testing You Can Perform
There are 3 subtypes of A/B testing you should know about:
1. Split Testing
In split testing, you test a completely new version of an existing webpage to analyze which one performs better. You should use split testing when you want to test the entire design of the existing landing page without disturbing the existing page.
2. Multivariate Testing
Multivariate testing is a form of testing where variations of multiple page variables are simultaneously tested to analyse which combination performs the best of all possible combinations. As it involves creating many variant pages this method is more complex and is best suited for advanced marketing products.
3. Multipage Testing
In this type of testing, you test changes to particular elements like the CTA buttons and the cross multiple pages. Multipage testing is also appropriate in situations where you would simply like to add or remove one element from every page flow or funnel and test the effects.
When To Use A/B Testing
A/B testing provides the most benefits when it operates continuously. A regular flow of tests can deliver a spill of reconnections on how to upgrade performance. Continued testing is possible because the available options are nearly unlimited.
A/B testing can be used to evaluate just about any digital asset including website pages, components on web pages, emails, newsletters, advertisements and mobile apps. A/B testing plays an important role in campaign management it helps to determine what works and what doesn’t it also helps you to see which element of your marketing has the biggest impact. Now you understand why you should A/B test, let’s consider when to use A/B testing:
- Campaigns that are not performing well and are not meeting expectations. A/B testing can be used to separate the performance problem and drive performance higher.
- You are about to launch something new (web page, email campaign) and you are not sure which approach will perform best. Dynamic use of A/B testing will allow you to compare the performance of two different approaches to identify the good one.
A/B Testing Tools to Use For UX UI Optimization
Several A/B testing tools are available, but here are some popular ones:
- Google Optimize: It is an excellent tool for running A/B tests on a website. It allows designers to split their websites into two versions and gather data separately. Integrating Google Optimize tools like Google Analytics and Ads enhances the analytics.
- Optimizely: Optimizely offers a range of features A/b testing in UX UI providing access to valuable data and test results. With Optimizely brands can set up A/B tests at different customer touchpoints for a comprehensive understanding of the overall user experience.
- AB Tasty: AB Tasty is a tool dedicated to split testing and helps designers conduct A/B testing without coding experience.
A/B Testing Mistakes to Avoid
Some of the most common mistakes you should avoid are:
Missing Defined Goals: You must have defined goals for the expectation for the result of an A/B test. These goals will allow your team to understand why the test is conducted and guide you in creating design variations.
Pausing The Test Too Early: An A/B test that lacks sufficient data points will return unreliable results. To get statistically reliable results, you must wait until the appropriate sample size of a test is reached. Only then you should conclude and end your A/B test.
Testing Without Strong Hypothesis: Only one in every seven A/B tests is a winning test. This rate is likely to be even lower if you are testing design elements without having a strong data-based hypothesis.
Focusing On Single Metric: The goal of an A/B test is often to increase or decrease a certain metric. However, if you measure only one metric to find whether your test is successful, you might disregard important information that can tell you if a design change is truly beneficial for your brand.
Ignoring Qualitative Research and Business Context: Just because A/B delivers a statistically significant result doesn’t mean you should follow blindly. After all, the A/B test might return a false positive or false negative that might introduce a measurement error, or your result might be statistically significant but not practically significant.
Yellow Slice A/B Testing Approach (Case Study)
About Revamp It
Revamp It is a fashion-tech startup and India’s first sustainable fashion makeover platform. Sustainable, creative, and accessible are the basic principles of RevampIt.
Revamp It aims to change the way fashion is purchased from online and offline platforms. They do so by slowing down the cycle of fast fashion with the concept of revamping your old clothes to brand new with exclusive designs in an effortless journey.
Problem Statement
They wanted to bring their offline line shop online and hence wanted us to create a website that enhanced their user buying experience and visuals to suit their target audience.
Checkout their full case study here
Final Words,
After reading the above guide in A/B testing you should now be fully prepared to plan your optimization roadmap. Follow each step actively and be attentive to all major and minor mistakes you commit if you do not give data the importance it deserves. If done with complete dedication A/B testing can reduce a lot of risks involved when undertaking an optimization program.
Remember testing is an incredibly valuable opportunity to learn how customers interact with your website. Start now with Yellow Slice.
FAQs About A/B Testing For UX UI Optimization
1. What is the goal of optimal UX?
The goal of optimal UX is to enhance usability, increase user satisfaction, drive conversions and build brand loyalty.
2. What is the purpose of user testing in UI UX design?
User testing in UI UX aims to gather feedback directly from users, enhancing the design process by uncovering insights and reffing the interface based on real user experience.
3. Can I test multiple things at a time?
Yes, you can but be careful about the potential drawbacks.
4. How long does A/B testing take?
A/B tests should be run until enough data is collected for any conclusions to be considered reliable. Let a test run for a minimum of 2 weeks.
