# URL Test ### What is a URL Test? A URL Test is a feature for testing multiple variations with the purpose of hypothesis validation, just like an A/B Test.\ You can input URLs corresponding to the control group and treatment groups to see how each variation affects your metrics. ![](/files/l3a2vV0f5QhKbW1L8fai) ### How is a URL Test different from an A/B Test? First, A/B Tests and URL Tests are essentially the same concept. **A/B Test** refers to running experiments by dynamically modifying content through code on the original page to show different versions. It can be used for both web services and app services, and is suitable for validating the effects of large structural changes or granular elements (text, images, buttons, and other page components). **URL Test** is a method that randomly serves different pre-built URLs instead of making dynamic changes, and tests their effectiveness. (Also called a redirect experiment or split experiment.) Since users are randomly exposed to two or more different URLs, it can also be used for large-scale changes to an entire page (redesigning the design concept, reorganizing component lists, etc.). Because each new page is hosted separately, there is no need to implement code directly in each component, which makes it possible to prepare experiments faster without development knowledge. URL Tests are also easy to use when a website is built with a web builder, and offer the following advantages: * **Minimize development resources for experiments**: Since complex code implementation is not required, even without development knowledge, you can quickly prepare and run experiments by simply inserting the integration code within the `` tag of the prepared URL's HTML. * **Full page redesign**: When you have made significant changes to the overall design and layout rather than minor element changes (text, color, font), you can use this to compare the page with the new design against the existing page. In summary, since both are the same concept, it is recommended to choose the appropriate method based on your experiment goal (hypothesis) or the environment in which the experiment will be conducted. ### Who should use this? * Those who frequently change landing page structure and content and want to optimize quickly * Those who find it difficult to run A/B Tests as often as desired due to limited development support * Those who were looking for an A/B Test solution to replace Google Optimize after its discontinuation 👉 [View URL Test success stories](https://blog.hackle.io/post/url-test-success-case1?utm_source=guide) ### How does a URL Test work? Suppose there is an original version (Group A) and modified versions (Group B, C, D...) to be tested. When users enter Group A, they are randomly redirected to Group A, B, C, D... and each URL is exposed with a 1/N probability. * Group A: \[ [www.example.com/product/10](http://www.example.com/product/10)] - 25% distribution * Group B: \[ [www.example.com/product/11](http://www.example.com/product/11)] - 25% distribution * Group C: \[ [www.example.com/product/12](http://www.example.com/product/12)] - 25% distribution * Group D: \[ [www.example.com/product/13](http://www.example.com/product/13)] - 25% distribution --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.hackle.io/en/ab-test/url-test.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.