Multivariate testing is a type of experimentation method where multiple variables are simultaneously tested to understand how they interact and influence the key metrics of interest. This method is often used in A/B/n testing scenarios where more than two groups are being compared.

In a multivariate test, a single control variable can be assigned multiple values, such as A, B, C, or D. This allows experimenters to evaluate the impact of different variations of a feature or product experience on the key metrics.

For example, in a website design experiment, a multivariate test could involve changing the color, text, and placement of a call-to-action button to see which combination leads to the highest click-through rate.

Here's a breakdown of the process:

1. Identify Variables: Decide on the different elements that you want to test. These could be anything from button colors, text, images, layouts, etc.

2. Create Variations: Develop different versions of the element by combining the variables in different ways. For instance, if you're testing button color and text, you might create variations like a red button with text A, a red button with text B, a blue button with text A, and a blue button with text B.

3. Run the Experiment: Use a tool like Statsig to randomly assign each user to a variant and collect data on their interactions.

4. Analyze the Results: Determine which variant led to the best outcome. This could be measured in terms of click-through rates, conversion rates, time spent on a page, or any other metric of interest.

By using multivariate testing, you can discover a global optimum when multiple variables interact, leading to more effective and data-driven decision-making.