URL testing is the same function as A/B testing to test multiple variants for hypothesis verification purposes.
You can check how each URL affects the indicator by using the page URLs (control group and experimental group)
First of all, the A/B test dynamically changes and experiments with different versions of content on the same screen. For example, when a user visits a page, the server or client side randomly shows either inside A or inside B.
Can be used to test changes in page components such as text, images, and buttons. Both web services or app services are available and are suitable for verifying the effectiveness of large structural changes, details.
- Example : when you change the button text of [Buy Now] button, you can experiment with which words induce more clicks.
The URL testing exposes pages of two different versions or more different URLs. It is mainly used for large structural changes, redesigns, and reconstructions on the page. Because in this case, it may be convenient to host the new page in a separate URL. Below is recommend situation.
- When web site change a lot : when you make significant changes to the overall design, layout, rather than making changes to some components, you can use URL testing to compare effects of between existing pages and new designed pages.
- Fast testing, Low codes needed : URL testing need low cost to ready and set testing compared to A/B Testing. you can quickly prepare and start experiment by just adding integration code to <head> of html on your page.
URL Testing has the advantage of being easy for anyone to prepare and start the experiment quickly. Because it doesn't need writing code in the development program. This allows you to optimize your web pages without any programming knowledge.
Let's assume there is an URL for Group A (Control version) and multiple URLs for Group B, C, D (experimental version).
Then all the traffic of Group A would split to the Group A, B, C, D randomly.
- Group A :[ www.example.com/product/10] - 25%
- Group B :[ www.example.com/product/11] - 25%
- Group C :[ www.example.com/product/12] - 25%
- Group D :[ www.example.com/product/13] - 25%
To use this method, you can see each URL's affect to users. Please see the How to start URL Testing docs to understand how to start now.
Updated 3 months ago