The subtle differences between A/B testing and split testing

Fri Feb 02 2024

Unravel the differences between A/B testing and split testing and how these methodologies refine user experiences and boost conversion rates.

Understanding the nuances between A/B testing and split testing is essential for optimization, especially in the realm of web page and marketing campaign improvement. A/B testing is a popular technique used to compare two versions of a single variable, typically by showing version "A" to one subset of users and version "B" to another. As a result, data is gathered to determine which version enhances performance, whether it be for user engagement, conversion rates, or other business metrics.

While both A/B testing and split testing aim to improve decision-making based on empirical data, split testing often implies dividing traffic between two entirely different versions of a website. Although the terminologies are sometimes used interchangeably, they have distinctive applications that affect the outcome and effectiveness of the tests. A nuanced understanding enables marketers to apply the correct methodology in pursuit of optimizing their digital assets.

To navigate these techniques effectively, one must consider the statistical and methodological principles underpinning each form of testing. Adopting a more accurate and strategic approach to testing can lead to more reliable and actionable insights, driving improved outcomes for web pages and marketing campaigns. Familiarity with foundational concepts can be enriched by examining materials that explicate A/B Testing fundamentals, ensuring a solid groundwork for effective testing implementation.

Understanding the terms

Before delving into the nuances, it's essential to clarify that A/B testing involves comparing two versions of a single variable to assess which one performs better, while Split Testing often means the same but can sometimes refer to testing on completely separate URLs. Multivariate Testing, on the other hand, examines the performance impact of varying multiple elements simultaneously.

What is A/B testing?

A/B Testing, or split testing, is a method where two versions of a webpage or landing page—labeled as "A" and "B"—are compared against each other to determine which one yields a higher conversion rate. In this type of test, user behavior is observed to see which version drives more conversions. For example:

  • Version A: Original landing page that serves as a baseline.

  • Version B: Different variation of the landing page with a different call-to-action

Test results are obtained by exposing a similar audience to each version and statistically analyzing which variant outperforms the other. A/B testing tools will help you determine if there is a statistical significance between the two versions of the page.

What is split testing?

Split testing, although sometimes synonymously used with A/B testing, specifically refers to a test where two or more completely different versions of a web page or website are hosted on separate URLs. This distinction is crucial when changes are so significant that they may represent two different approaches to the web page design or user experience.

For instance:

  • URL A: Original website with original design and content

  • URL B: New version of the website layout with altered navigational structure

In split testing, the performance of each website version is meticulously tracked to see which one achieves a better conversion rate optimization.

What is multivariate testing?

Multivariate testing extends beyond A/B and split testing by testing multiple variants of several elements simultaneously to observe the effect on user behavior and conversions. Here, combinations of different elements are changed to determine which combination produces the best outcome in a test run. Examples include:

  • Different headlines on the homepage

  • Swapping out images

  • Changing the call-to-action button

In multivariate testing, you can track how each combination affects the conversion rate, and through systematic testing, you can determine which design elements resonate most with users and redesign based on the results.

Key differences between the tests

When evaluating A/B and split testing, understanding their key differences helps in deciding which method to use for website optimization.

Scope of change

A/B testing typically involves making small changes such as tweaking a headline, changing button colors, or altering font sizes. The focus is on granular modifications to refine a page. On the other hand, split testing, also known as split URL testing, is often used for large changes that may include separate page builds. This can encompass redesigning an entire page or significant shifts in layout or content.


Implementing A/B testing generally involves the use of Javascript overlays on the existing page. This allows for dynamic adjustments without the need for multiple page versions. Split testing, in contrast, requires separate versions of a page to be created and hosted on different URLs. It's a more complex approach that can involve more resources but is suitable for broad modifications.


In the analysis of test results, both approaches examine user behavior to determine which variation performs better. However, the reliability of these results can be influenced by Type 1 errors. Minimizing such errors is essential to ensure the accuracy of the tests. To understand more about reducing these errors, consider the nuances discussed on how to reduce Type 1 errors in split testing. A/B testing results often hinge on subtle differences, whereas split testing aims to draw conclusive results from more prominent changes.

Choosing the right approach

Determining which testing process to employ—A/B testing or split testing—involves understanding their applications in optimization of user experience and conversion rates. The decision hinges on specific marketing strategy goals and the particular elements under review, such as headlines, CTAs, button color, or page design.

When to use A/B testing

A/B testing is ideal when the objective is to optimize existing page elements by making minor, incremental changes. For example, when tweaking headlines or call-to-action (CTA) buttons, this method allows for a controlled comparison between the original version (A) and a single changed version (B). Businesses aiming to refine their user experience (UX) and conversion rate optimization (CRO) benefit from A/B testing because it provides clear insights into the impact of specific variables.

  • Headlines: Testing different wording can unveil which captures more attention.

  • CTA Buttons: Changes to verbiage or button color can impact click-through rates.

This method is also powerful for product development, which can be understood through insights on how A/B testing paves the way for scientific and measurable causality.

When to use split testing

Conversely, split testing is the approach of choice when entirely new layouts or significant overhauls are being considered. It is fitting for evaluating revamped page design scenarios or novel marketing campaigns where two wholly different versions are put to the test. It suits scenarios like:

  • New layouts: Testing an alternative layout against the current design.

  • Marketing campaigns: Evaluating distinct campaigns to see which performs better.

Companies undergoing a rebrand or launching a new product line frequently employ split testing to compare different user experience strategies or marketing messages on a larger scale.

Use of both methods

In some circumstances, marketers may opt to employ both A/B and split testing in their testing process and optimization endeavors. A robust marketing strategy employs A/B testing for fine-tuning elements like CTA placement or text, while split testing is used for assessing the performance of new concepts against the status quo. For instance, an e-commerce business might run A/B tests to determine the best button color to draw attention, and split tests to compare different checkout process designs.

  • E-commerce: Leveraging A/B testing for optimizing checkout buttons, and split testing for new checkout flows.

  • UX and CRO: Utilizing both methods can comprehensively enhance shopping experiences and conversion rates.

Maximize your optimization with Statsig

Unlock the full potential of A/B and split testing with Statsig. Distinguish between minor tweaks and major overhauls to enhance user engagement and conversion rates with precision. Statsig's platform offers the tools and insights needed for effective decision-making, ensuring your digital assets achieve their maximum impact. Dive into a world of data-driven optimization and elevate your web pages and marketing campaigns to new heights.

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