Same Test, Different Name? Clearing Up the Confusion Between A/B and Split Testing

If you’ve ever used “A/B testing” and “split testing” interchangeably, you’re not alone. Plenty of teams do — and in many cases, they mean the same thing. But depending on your tech stack, your testing goals, or your traffic routing setup, the difference between the two can start to matter more than you think.

Here’s the short version:
A/B testing typically refers to comparing variations on the same page or experience.
Split testing often means routing users to entirely different pages or environments.

But it’s not just about the label. It’s about running the kind of test that gets you to the clearest, fastest, most trustworthy answer.

When They’re the Same—and When They’re Not

Most of the time, A/B testing and split testing are used to describe the same general concept, showing different experiences to different users and measuring which one performs better. But technically, there’s a subtle, and often significant, difference in how they’re implemented.

Here’s the easiest way to think about it:

Let’s say your product team wants to test a new onboarding flow.

A/B Test Approach: You keep users on the same URL and use front-end logic to show two variations of the signup form — one short, one long. This works well if you just want to measure drop-off or completion rates based on form fields.

Split Test Approach: You route users to two entirely different onboarding experiences hosted on separate URLs — one has a multi-step flow, the other a single-page form with integrated tooltips. You’re not just testing form length, you’re testing philosophically different onboarding strategies. Both are valid. But they answer different questions and have different technical considerations. 

A/B Testing: Same URL, Different Experience

In an A/B test, all users land on the same URL, and your platform dynamically renders different content for each group. Users are randomly assigned to Variation A or B, but the page detects the assignment and shows the relevant version, meaning that essentially everything happens in the same environment. This is great for small-to-medium UI changes, copy tests, layout tweaks, CTAs, pricing tables, basically anything that doesn’t require massive structural or backend changes.

Split Testing: Different URLs, Different Worlds

In a split test, users are sent to totally different URLs. Version A might be from example.com/signup, and version B from example.com/new-signup. Each version could have unique codebases or flows because you’re essentially comparing two different experiences from end to end. This approach is better for testing full redesigns, alternative user journeys, backend or infrastructure changes (e.g., different checkout flows or new recommendation algorithms).

When the Distinction Matters—and How to Choose the Right Test

For many teams, using “A/B test” and “split test” interchangeably causes no issues—until it does. That’s because the difference isn’t just about terminology. It’s about how you design, implement, and interpret your experiments. Choosing the wrong method can lead to inaccurate data, delayed deployment, or a test that simply doesn’t work as intended.

A/B testing is ideal when you want to make smaller, surface-level changes, such as updating a headline or trying out a new layout. These tests typically run on the same page and URL, which makes them faster to implement and easier to manage. It’s a lightweight, reliable way to learn fast and make data-backed decisions without major engineering overhead. You’re testing within an existing experience, so you can move quickly without disrupting other systems or workflows.

Split testing is a better fit when you’re making broader, structural changes, like testing two entirely different versions of a page or comparing two user journeys. Because they send users to completely separate URLs or environments, they work well for when you’re evaluating full redesigns or new backend logic Of course, split testing needs more planning and coordination, but they do give you the freedom to test strategic changes that go beyond visual tweaks.

There’s also a practical trade-off between speed and scope. A/B tests are generally quicker to set up and deploy, which makes them ideal for high-velocity testing and rapid iteration. Split tests take more time and engineering effort, but they allow you to evaluate end-to-end experiences, infrastructure updates, or substantial product shifts with accuracy.

At ABsmartly, we help teams make those choices with confidence. Whether you’re testing subtle UI changes or rolling out a major infrastructure shift, our platform supports both A/B and split testing — with tools designed to handle the complexity so your team can focus on learning, improving, and shipping smarter.

So What Should You Call It? (And What Should You Use?)

Different companies, teams, and tools use the terms differently. Some treat them as synonyms. Others make a hard distinction based on implementation. In either case, confusion often creeps in when teams assume they’re aligned but are actually thinking about very different test setups. Our advice is not to worry too much about the label. Focus instead on what you’re testing, how your tool handles it, and what you’re trying to learn. If you’re running a variation on the same page, that’s commonly called an A/B test. If you’re routing users to different environments or URLs, you’re probably running what many would define as a split test.

The key is to make sure your team are clear on shared definitions and are documenting how your organization refers to different types of tests, especially when experiment design, implementation, and analytics cross multiple teams. Clear communication avoids costly missteps, like trying to run a backend infrastructure test as if it were a simple front-end A/B experiment. At ABsmartly, we designed our platform to support both A/B and split testing workflows seamlessly, and we help teams navigate the trade-offs so you’re not left guessing which setup to use. Whether you’re testing a line of copy or an entire user journey, we give you the flexibility to choose the right approach.

Clarity in Testing Starts with Intentional Design

At the end of the day, the difference between A/B testing and split testing isn’t just about terminology, it’s about making intentional choices in how you design, run, and learn from experiments.

When you understand the mechanics behind each approach, you’re better equipped to match the right method to the problem you’re solving. That means fewer surprises, faster learning, and results your team can trust.

Whether you’re optimizing a headline or testing a brand-new user flow, the most important thing is clarity in your goals, in your setup, and in the insights you gather. The label matters less than the confidence you have in your results and the ability to act on them.

At ABsmartly, we help product, engineering, and data teams run experiments that are not only statistically sound but strategically valuable. From simple UI tests to complex infrastructure experiments, our platform and team are here to help you move fast, test smarter, and build a culture of learning that scales.

Ready to run tests you can trust — without second-guessing your setup?

Book a demo and let’s walk through how ABsmartly supports both A/B and split testing with the tools, guidance, and flexibility your team needs to experiment with confidence