Multivariate testing, also known as A/B testing or split testing, is a method of lead generation where multiple variables are tested simultaneously to determine which combination drives the most conversions. This approach allows for more efficient optimization of a website or marketing campaign compared to traditional A/B testing. By experimenting with various elements such as headlines, images, and call-to-action buttons, marketers can gather valuable data on what resonates best with their target audience.

Multivariate testing can be extremely beneficial for marketing campaigns. It allows businesses to test multiple variables at once, which can lead to a more successful campaign overall. Additionally, it can help businesses save time and money by reducing the need for extensive market research. Multivariate testing can also improve customer satisfaction by ensuring that marketing campaigns are tailored to meet their needs and preferences. Ultimately, businesses that use multivariate testing can achieve a higher ROI for their marketing efforts.

There are a few different types of multivariate testing, each with their own benefits and drawbacks. The most common types are A/B testing, split testing, and MVWO testing.

A/B testing is the most basic form of multivariate testing. In this type of test, two versions of a web page (or email, or ad, etc.) are shown to users at random. The goal is to see which version performs better in terms of conversion rate or other desired metric.

Split testing is similar to A/B testing, but instead of showing two versions of a page at random, all visitors see one version or the other. This can be used to test major changes that can't be easily undone, such as a redesign.

MVWO testing, or multivariate without replacement testing, is a more advanced form of split testing. In this type of test, each visitor sees all versions of the page, but in a different order. This allows for more accurate data, but can be harder to set up and may take longer to get results.