Choosing the appropriate traffic type, either user-level or tenant-level, is crucial for optimizing sample size and experimental accuracy in B2B experiments conducted with Split. User-level traffic types generally offer larger sample sizes, facilitating more reliable insights unless a consistent experience across an account is necessary. Split allows for traffic types to be selected on a case-by-case basis, considering factors like feature changes and success metrics. For tenant-level traffic types, challenges such as unequal user distribution can be addressed using normalized metrics like "percent of" or "ratio of two events" to ensure balanced data. Split's platform provides tools to manage features, run A/B tests, and deploy safely without disrupting production, supported by resources like Split Arcade for learning and certification. Additionally, Harness offers AI-driven automation to enhance code shipping processes, ensuring they are faster, safer, and smarter.