Suppose you have two different ideas for how a website element should look or perform, but no clear way to determine which one works best with real users. Making decisions based only on assumptions or internal preferences can lead to missed opportunities and ineffective optimizations.
A/B testing provides a structured approach to experimentation. By presenting different versions of an experience to different groups of users, teams can compare their interactions and identify which variation performs better.
However, an effective A/B test requires more than simply creating two versions of a page. Traffic needs to be distributed correctly, the audience needs to be defined, and the variations should isolate a specific element so that the results can be interpreted clearly.
Within Kleecks, the AB Test Standard workflow allows users to create controlled experiments directly through the customer journey editor. Teams can define the number of variants, distribute traffic between profiles, set access rules, and modify specific page elements while keeping the rest of the experience consistent. The result is a structured experimentation process designed to generate insights from real user interactions.
Starting from the Customer Journey Editor
The process begins by opening the source editor and creating a new customer journey. During the initial setup, users select AB test as the type of experience. This defines the journey as an experimentation workflow and allows the different versions of the experience to be configured.
The next step is to determine how many variants should be included in the test. Kleecks allows users to create either two or three profiles, depending on the experiment they want to run.
Defining the Test Profiles
Once the number of variants has been selected, users can configure the individual profiles within the dedicated profiles section.
Traffic can be divided between the profiles according to the desired testing strategy. Each profile represents a different version of the experience that will be presented to users participating in the test. Profiles can also be renamed, making it easier to identify their purpose. For example, they can be labeled according to the variation they contain or the specific hypothesis being tested.
Clear naming helps teams manage multiple experiments and understand the structure of each test more easily.
Controlling Who Enters the Test
Not every user necessarily needs to be included in an A/B test. Kleecks allows users to define additional journey rules that determine which visitors are eligible to enter the experiment.
These conditions can be based on characteristics such as device type, browser, or other available targeting criteria. This makes it possible to limit the experiment to a specific audience when required. For example, a test could be configured for users accessing the website through a particular type of device.
By defining the audience before the experiment begins, teams can make sure that the test is conducted within the intended context.
Creating the First Test Variation
Once the journey configuration has been completed, the profiles can be edited individually.
The editing process begins by selecting the option to work on a specific profile, such as profile A. The page then refreshes and provides the environment in which the variation can be created. A simple example of an A/B test is changing the background color of the footer, an element that appears consistently across pages.
The key principle is to modify the element being tested while keeping the rest of the experience unchanged. This makes it easier to isolate the variable and understand whether the variation has an impact on user behavior.
Creating the Second Variation
The same process is then repeated for the second profile. Profile B receives a different version of the element being tested, while the rest of the page remains consistent with profile A. For example, if profile A uses the existing footer background color, profile B can use an alternative color. Everything else remains unchanged.
This controlled approach creates a clear comparison between the two experiences and helps ensure that the experiment focuses on a specific variable.
Isolating the Variable
One of the most important principles of effective A/B testing is controlling the variables.
Changing multiple elements at the same time can make it difficult to determine what caused a difference in user behavior. By modifying only the element under investigation, teams can create a cleaner experiment and draw more meaningful conclusions from the results. The Kleecks workflow supports this approach by allowing each profile to be edited independently while maintaining the rest of the experience.
Whether the test involves a color, layout element, content component, or another page feature, the objective remains the same: create clearly differentiated variations while keeping the experiment controlled.
Testing with Real User Interactions
Once the profiles have been configured, the A/B test is ready to run.
Different users are exposed to the defined variations according to the traffic distribution established during setup. Their interactions with each version provide the data needed to compare the experiences.
This shifts optimization from assumptions to experimentation. Instead of deciding which version should be implemented based solely on opinion, teams can use real user behavior to evaluate the alternatives. The resulting insights can then support future decisions about which experience should be retained, refined, or tested further.
Building a Structured Experimentation Process
A/B testing becomes more effective when it is treated as an ongoing optimization process rather than a one-time activity.
The Kleecks workflow provides the building blocks needed to structure these experiments: defining the audience, creating profiles, distributing traffic, isolating variables, and editing each variation. This approach makes it possible to test specific hypotheses in a controlled environment while keeping the setup manageable for teams working across different pages and experiences.
Over time, individual experiments can contribute to a broader understanding of what works best for a particular website and its users.
Scaling Personalized Experiences
Personalization can become increasingly complex as websites grow and audience segments multiply. Managing different experiences manually can require significant time and coordination. A structured customer journey workflow makes it easier to create and manage multiple personalized experiences based on reusable targeting logic. This is particularly valuable for websites serving different markets, product categories, locations, or user profiles. Teams can define specific journeys for different audiences while keeping the experiences integrated into the same website.
Instead of creating separate pages for every audience, personalization allows the website experience itself to adapt dynamically.
From Experimentation to Optimization
The value of an A/B test goes beyond identifying a winning variation. Each experiment can provide insights into user preferences and interactions that inform future optimization strategies. A change that performs better can become the basis for a new experience, while an unsuccessful variation can reveal what should be avoided or investigated further. By connecting experimentation with real user behavior, teams can create a continuous cycle of testing, learning, and optimization.
Conclusion
Effective website optimization requires the ability to test ideas and understand how users respond to different experiences. A/B testing provides a structured way to make these comparisons while reducing reliance on assumptions.
Kleecks AB Test Standard allows teams to create controlled experiments directly through the customer journey editor. Users can define two or three profiles, distribute traffic, establish audience rules, and create targeted variations while keeping the rest of the experience consistent. By isolating individual variables and testing them with real users, teams can generate actionable insights and use those findings to guide future optimization.
In modern digital experiences, optimization is not simply about making changes. It is about understanding which changes create a meaningful difference. With Kleecks AB Test Standard, experimentation becomes a practical part of the process, turning user interactions into insights that can support better decisions.
Check out our video to understand better how Kleecks platform works: https://youtu.be/ym7YaPjxLqQ?si=tzAsPvgRiGX5Zc5U