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A/B Testing: The Testing Family Tree And How It Works

Published on 05 May 2022 in

What if, instead of trying to guess your customers’ online preferences and behaviors, you could base your product design choices on real-world, real-time data? With today’s A/B testing methods, that power is in your hands. The ability to compare different versions of an app or other digital product or platform — even an individual part — provides vast opportunities for companies seeking a scientific approach to solving human problems.

Wireframing is the most popular method for visualizing the layout of individual site pages. As with other early-stage UX artifacts such as journey maps and site maps, wireframes enable companies to crystallize project requirements and goals before diving into execution. Providing a pared-down visualization of each page and the content within it, wireframing plays a unique and extremely high-ROI role in the web design process.

A/B testing allows you to make continuous, data-driven improvements to the customer experience by replacing bias and “best guesses” with quantifiable evidence. Almost any part of your online products can be validated through this practice, from entire apps to minute design changes. All it takes is a control, a variable and a conversion goal to start gathering metrics that will drive your digital business forward.

How A/B testing works

Put simply, A/B testing is an experiment in which two variants of the same digital element compete for the win. Providing the data necessary for making low-risk, high-impact adjustments, this methodology continues to stand out as one of the most reliable, versatile, and value-creating tools for increasing online conversions and engagement.

A/B testing begins with choosing a control sample of a digital element to use as a baseline; this could be an app screen, landing page, contact form, or virtually any other piece of your product or platform. Next, the team creates a modified version of the same element featuring one change in style, content, timing, or other variable expected to have an impact on customer behavior.

The two options are tested against each other among the same audience, ideally the company’s most desirable users, to generate statistically significant performance data. Metrics compared using A/B testing may include click-through rates, time spent on the page, completed purchases, or the number of demo requests. Visitor behavior analysis tools such as heat mapping and Google Analytics, or even user surveys and interviews, provide findings that design teams can act on quickly and cost-effectively.

The sample that emerges from the test with the highest conversions and other predetermined KPIs is selected as the winner, either maintaining its position as the baseline or becoming the new one. From there, the cycle begins again; as we’ll discuss more in this post, in addition to answering the immediate question, a strong A/B testing strategy provides a consistent, sustainable framework for future iteration.

The testing family tree: A/B, split and multivariate tests

To best leverage A/B testing, it is helpful to understand two somewhat lesser-known but closely related methodologies: split testing and multivariate testing. These approaches share many of the same goals as A/B testing and are often used in combination with it. However, it is important to keep in mind that each testing method serves a different purpose in the validation process.

1. Split testing

A split test is used to determine the higher performance of the two design directions. In this form of testing, half your audience is shown an original version, and half is shown one with multiple altered elements. The winner of a split test can then form the basis for A/B testing, multivariate testing, prototyping, and other refinement methods.

Unlike A/B testing, which examines an isolated variable within an otherwise similar page, split testing presents two separate design concepts—and potentially very different user experiences. Anything from page layout to text, color palette, images, and interactions can vary between the two sites, allowing teams to try out multiple ideas at once. Ultimately, the only qualities the samples need to share are the same user base and conversion goals.

For these reasons, split tests provide limited information as to which variables are driving the observed changes and why. This methodology is quite effective, however, in informing bigger-picture decisions about UX, UI, and overall look and feel.

2. Multivariate testing

Multivariate testing magnifies the capabilities of A/B testing, providing a high level of insight into how specific combinations of variables are performing across one or more pages. Essentially, multivariate testing enables you to run several A/B tests simultaneously. Generating data on multiple variations of multiple variables, it helps clarify the exact tweaks needed to optimize your conversion rate.

As is the case with A/B testing and split testing, customer patterns become clear through objective measurements. Gaining statistically significant data from multivariate testing requires a larger volume of traffic, which can it more of a challenge than other methods. A multivariate test can be as simple or complex as you like, however; just keep in mind the more hypotheses you test at the same time, the more user visits and interactions you’ll need to validate them.

What digital innovators accomplish with A/B testing

1. Low-risk, high-return modifications

A/B testing allows companies to make incremental, relatively inexpensive changes to their digital platforms without jeopardizing their existing traffic, conversion rates or brand image. Analyzing potential adjustments one by one, or in small batches, helps teams avoid investing time and resources in unnecessarily large-scale redesigns.

Designed to achieve maximum impact with minimal effort, well-executed A/B testing drives exponential ROI as the product continues to evolve. As a result, companies can make the most informed and strategic choices possible when it comes to their product improvement initiatives.

2. Frictionless pathways to conversions

Users come to your online business to solve a specific problem, and any obstacles they encounter in doing so are likely to send them to a competing product. A/B testing is invaluable when it comes to identifying and changing elements that appear to be causing confusion, inconvenience, or frustration among your users.

By addressing pain points in your product’s design and functionality, A/B testing streamlines the sales funnel, removes friction, and ensures that your customers’ expectations are fully met. This helps companies achieve lower bounce rates, reduced cart abandonment, higher sales volume, and other successful conversion metrics.

3. Deeper user insights

A/B testing can be used to gain a more holistic understanding of who your users are, how they think, and what factors are most central in their decision-making. A well-designed A/B test allows teams to discover new information about their ideal customers—not only which version of a digital element they prefer but why, when, and how they choose to engage with it.

For example, A/B testing may reveal that your audience is more likely to respond to a call to action at a specific time of day, when they want to learn more about a certain topic or how much information they need in order to feel confident about a purchase. Complemented by the use of web personas and other tools, this information provides many ways for companies to better engage their users.

4. Continued improvement

A/B testing is a go-to solution for resolving short-term disagreements and making quick adjustments. When leveraged effectively, however, it also creates long-term value for your overall product and business. It is designed to be a repeatable, ongoing process through which you can keep your online presence moving ever forward.

Improving the user experience does not end when the current A/B test does. Rather, the findings lay the foundation for continuous iteration—a critical element of success in today’s fast-moving digital marketplace. Used consistently over time, A/B testing ensures a digital platform, app or product has what it takes to stay ahead of the competition in innovation, customer reviews, sales, brand loyalty, and more.

Summary

If your company is seeking a more data-driven way to keep enhancing your online customer experience, you can’t afford to ignore A/B testing. The ability to track real user behaviors without a heavy investment of time and expense—and without the risk of making unvalidated changes to your existing digital presence—allows your design team to make measurable and meaningful improvements, and faster than ever before.

Implementing A/B testing, with or without the addition of split testing and/or multivariate testing, can result in a nearly immediate boost in your KPIs while setting you up for a successful long-term trajectory. The more A/B testing you perform, and the more focused your strategy becomes, the more confidence you’ll have in your digital product’s design, quality, and future success in the marketplace.

At Morphosis, we’re passionate about helping businesses achieve their digital testing and product improvement goals.