The 'Diagnose with Data, Treat with Design' Framework

“数据诊断，设计处方”框架

概述 / Overview

数据应用于建立业务的“可观测性”，即理解客观现状（诊断）。然而，数据不能直接给出解决方案，这需要创造性的同理心和设计思维（处方/治疗）。

来源 / Source

• •嘉宾: Julie Zhuo
• •职位: Co-founder at Sundial
• •公司: Sundial

核心原则 / Core Principles

• •Data reflects reality: Use metrics to understand user behavior and spot anomalies, not to predict the future with certainty.
• •Diagnosis vs. Treatment: Use quantitative analysis to identify where the problem is, but use qualitative design/intuition to solve how to fix it.
• •Avoid False Precision: Acknowledging that metrics (like A/B tests) have limitations and cannot replace long-term product vision.
• •New Context, New Metrics: As technology shifts (e.g., to LLMs), traditional metrics (clicks) must evolve to new forms (conversation quality).

适用场景 / When to Use

当产品团队陷入“分析瘫痪”，或设计师因感到创造力受限而抵触数据时。

常见错误 / Common Mistakes

期望数据直接告诉你下一个功能该做什么，或者当数据与你对产品成功的“叙事”相悖时选择忽视数据。

实战案例 / Real-World Example

Julie 提到快速增长的公司通常靠“感觉（Vibes）”运行，直到增长放缓。此时，他们必须实施数据埋点来诊断根本原因（Why），但重新点燃增长的解决方案需要设计干预。

金句 / Quote

"You want to diagnose with data and treat with design. Data is not a tool that's going to tell you what you should build."