What Samsung learned bringing B2C experimentation rigor to B2B

Samsung Electronics America Lead Product Manager Anuradha Tempe discusses how experimentation differs between Samsung’s mature B2C storefront and its newer B2B platform, where lower traffic, highly variable bulk orders, longer approval processes, and cross-device buyer journeys require more careful interpretation of test results. Her team normalizes B2B order data to prevent large purchases from creating misleading outcomes and reserves full A/B tests for high-risk decisions, while using UAT feedback or pre/post analysis for simpler changes. An experiment that surfaced software and service add-ons alongside hardware purchases improved conversion and average order value, with add-on sales nearly doubling after the team recognized that business customers often research on mobile before completing approved purchases on desktop. Conversely, an early “Buy Now” option confused bulk buyers who wanted product details and configuration clarity before purchasing, reinforcing the principle that B2B customers prioritize confidence over premature speed. Tempe emphasizes setting a North Star metric before building, monitoring guardrails such as conversion or customer feedback, openly sharing unsuccessful results, and introducing experimentation practices collaboratively across teams and cultures. She is also developing an AI-assisted testing copilot to generate hypotheses and triage test needs, while maintaining human review to preserve judgment and prevent unreliable automated outputs.

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