How Zalando connects every experiment to its North Star

Mi Tian, Head of Applied Science at Zalando, describes how the e-commerce company manages more than 1,000 annual experiments by linking product decisions to a company-wide North Star goal through a KPI tree that connects high-level objectives, measurable proxy metrics, and controllable product inputs. Zalando’s centralized economics and experimentation organization, which reports under the chief economist and CFO, combines experimentation, causal inference, and economic analysis to select appropriate measurement methods and reinforce executive support for evidence-based decisions. Its self-service platform enables teams to launch and analyze tests, while risk tiering balances rapid, lower-risk experimentation with more rigorous evaluation of potentially disruptive initiatives. This approach supported the launch of Zalando’s personalized discovery feeds, where short-term A/B tests and long-term holdouts measured engagement, transaction effects, and gross merchandise value, ultimately indicating positive results. Looking ahead, the company is exploring LLM-based customer-behavior simulations to screen hypotheses and inform prioritization, while emphasizing that such tools are not replacements for live experiments.

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