A/B testing and multivariate testing are two methods used to optimize websites and features, each with distinct characteristics and applications. A/B testing, or split testing, involves comparing two versions of a webpage, feature, or user flow to determine which performs better based on metrics like conversion rates, and is typically quicker due to its simplicity. Multivariate testing, on the other hand, is more complex, involving multiple variables simultaneously to gain deeper insights into which combinations of elements improve a webpage's performance, making it suitable for high-traffic platforms. While A/B testing is ideal for lower-traffic sites due to its faster results with fewer variations, multivariate testing requires a substantial amount of traffic to achieve statistically significant results. Split, a feature management platform, facilitates these testing methods by allowing users to set up feature flags, control feature deployment, and conduct feature experiments seamlessly, enhancing the efficiency and reliability of software releases.