Split testing, also known as A/B testing, is a method of comparing two versions of a webpage or other user experience to determine which one performs better. It is a way to test changes to your webpage against the current design and determine which one produces better results.

In a split test, you take a webpage or user experience and modify it to create a second version of the same page. This change can be as simple as a single headline or button, or be a complete redesign of the page. Then, half of your traffic is shown the original version of the page (known as the control) and half are shown the modified version of the page (the variant).

An example of a split test might be an e-commerce site testing two different types of product images to see which leads to more purchases. The site would show half of its visitors the current product image (the control) and the other half would see the new product image (the variant). The site could then compare the results to see which image led to more purchases.

Split testing is a powerful tool for making data-driven decisions that can help improve a product or a business. It allows teams to eliminate guesswork and make changes that have been proven to drive better results.

Here's a typical process of a split test:

1. A user need is surfaced or hypothesized

2. A solution is proposed

3. An MVP of the solution is designed

4. The target population is split randomly for a test, where some get the solution (Test) and some don’t (Control)

5. Comparing outcomes between the users with the Test and Control experiences gives the team information on if the solution worked. Based on the results, they might ship the full solution, iterate on it, or scrap the idea and try something new.

Split testing is not just for binary ship/no-ship decisions on product changes. It can also function as a powerful tool for analysis and understanding, and can be useful for much more than launch decisions.