Preference test and A/B testing are two common methodologies for testing your digital products. A lot of people use the two terms interchangeably when they mean one or the other, which is wrong as they are two different methods.
This article discusses what each of these testing methods is, when to use them, and how they differ from one another. And in case you don’t feel like reading, check out this short video where Charli compares the methods!
A test in which participants are given two options and asked to select between them. This is a helpful UX testing method since participants go beyond merely selecting a choice by being asked why they chose that particular option.
It’s commonly used to look for additional qualitative information in preference assessments that goes beyond what the users want. This information aids in the formation of a broader and more comprehensive picture, resulting in a better understanding of the best design for customers.
You can show customers two different navigation layouts in a web design, for example. User feedback will tell you which layouts people like and why they chose them. This feedback will provide you with crucial information about your design, allowing you to tweak it until it’s perfect.
When to Conduct a Preference Test?
Preference testing is used to determine what consumers prefer and for what reason. This user test is done earlier on in the design process. It aids in obtaining proof of concept prior to investing time, attention, and money to the final product’s development. If you run such a test early on, you’ll have a better understanding of what your customers want and why they want it.
How to Conduct a Preference Test?
Check out this easy step-by-step guide on when and how to conduct the most effective preference testing creating.
Begin by determining your goals and gathering research materials.
Whether you’re conducting qualitative or quantitative preference test, decide how you’d like test participants to communicate their subjective preferences.
According to the user testing general rule, you should select test participants that reflect your target consumers as closely as feasible, as well as the state of mind or context required to comprehend the design.
Once you have your test participants, design variations, research objectives and questions, feel free to explain the procedure to them before you begin the test.
In terms of quantitative information, examine the questionnaire replies to determine which option is the most popular. Learn how to analyze the results of a Preference Test.
What Tools to Use for Preference Test?
In order to get the best results from preference testing, you’ll need the right tools. Check out our list of the best 5 Preference Testing Tools.
What is A/B Testing?
A/B testing isa method for comparing two objects and determining, in a nutshell, which one is preferred by website visitors or programs.The desired change in behavior can be traced to metrics such as conversion, registration, engagement etc.
In A/B testing success is judged by the numbers.
A/B testing involves testing of two versions;
- The Control – This is the version of your website that is now active, often known as in operation, open, or live.
- The Experiment – This is the new version consisting of a different layout, content, or image that you’d like to test to see if it performs better than what you presently have on your website.
You could question, for example, if a larger “download now” button on your website will encourage more people to download your ebook. This A/B test will use the existing “download now” buttons on your ecommerce sites as the control, with a larger “download Now” option on select product pages as the experiment.
How to Conduct A/B Testing?
Your analytics will frequently reveal areas where you may start optimizing. To acquire data faster, it’s best to start with high-traffic regions of your site or app. Look for pages with high drop-off rates or low conversion rates that can be improved.
Determine conversion objectives
Your conversion goals are the measurements you’ll use to see if the variation is more effective than the original. Goals can range from clicking a button or link to making a purchase or signing up for an email list.
Before conducting A/B testing, it’s a good idea to state your null and alternative hypotheses: the null hypothesis states that there is no difference between the variant and control groups. According to the alternate hypothesis, there is one.
After you’ve chosen your null and alternative hypotheses, the next step is to create your control and test (variant) groups.
Run the experiment
Visitors to your website or app will be randomly assigned to the control or variation of your experience at this point. To determine how each experience succeeds, their interaction with it is measured, counted, and compared.
Determine the differences
Once you’ve finished your investigation and obtained your data, you’ll need to determine whether the difference between the control and variation groups is statistically significant. Finally, develop conclusions based on the experimental findings.
When to Conduct A/B Testing?
When you are rebuilding your web, changing a service, plugin, or a certain feature on your website, it’s a great time for an A/B test.
What Tools to Use in A/B Testing?
A monitoring template for A/B testing, a how-to guide for education and motivation, and a statistical significance converter to determine if your experiments were successful, unsuccessful, or inconclusive.
This is a tool that allows you to learn about user behavior and how users engage with your website. Their A/B Test interface makes it super simple to pick a goal, map a desired website action to that goal and watch the results come rolling in. As soon as the tool detects a winning variant, it sends more traffic to that winner automatically.
The A/B testing tool in Google Optimize, especially, provides much more than conventional A/B testing. Users can test several variants as well as run:
- Multivariate analysis
- Testing with different URLs
- Experimentation on the server
Preference Test Vs. A/B Testing: What’s the Difference?
Preference test seems to be more about learning what layouts the user likes and why people choose them before the product is finished,
Example: For a particular model, you possess three potential website layout drawings available. Rather than forming conclusions, do preference testing to find out which design prospective customers favour.
On the other side, A/B Testing is focused on KPIs. It is all about determining when various variations impact behavior and how people utilize a service to attain a purpose.
Example: Let’s assume your eStore’s email signups have lately decreased. To promote additional signups, you have several choices, including varied CTA box colours in each layout version. Give users several options to test their activity and see which CTA colour generates the most signups.
So, which testing method should you use?
UX designers don’t have to make assumptions about how their products work anymore or rely on what users say. And this is precisely why user testing was created in the first place. Instead of asking individuals which design they prefer, we now invite them to try out a prototype and identify the usability concerns that need to be addressed.
When evaluating the usability of our goods, we can combine a preference test and A/B testing. Start with some techniques you want for the A/B test and conduct some preference testing ahead of time to determine which are the clear winners that we want to include in that A/B test so that we have a better feel of what will not fail when launched.
For more tips on conducting usability testing we’ve put together an article on How to Run Usability Tests to ensure you get the best results. Create your UXtweak account and run your first Preference Test today! Stop guessing the behavior of your customers. Ask them why they do what they do.