metrics-framework

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Define metrics that drive decisions, not dashboards that collect dust. Every metric must answer: "If this number changes, what will we do differently?" If nothing changes, it's a vanity metric.

定义能驱动决策的指标，而非无人问津的仪表盘数据。每个指标都必须能回答：“如果这个数值发生变化，我们会采取什么不同的行动？”如果没有任何行动变化，那它就是虚荣指标。

North Star Metric

One metric that captures the core value your product delivers to customers. Not revenue (that's an output). Not signups (that's vanity). The North Star reflects the moment customers get value.

Examples:

Slack: Messages sent in channels with 3+ members
Spotify: Time spent listening
Airbnb: Nights booked

Test: If this metric goes up, does the company sustainably grow? If yes, it's your North Star.

这是一个能体现产品为客户提供核心价值的指标（即北极星指标）。它不是收入（收入是一种产出），也不是注册量（这属于虚荣指标）。North Star Metric反映的是客户获得价值的瞬间。

示例：

Slack：3人及以上成员的频道中发送的消息数
Spotify：收听时长
Airbnb：预订晚数

测试标准： 如果该指标上升，公司是否能实现可持续增长？若是，它就是你的North Star Metric。

Input/Output Tree

输入/输出树

Build a tree connecting your North Star to actionable inputs:

North Star: Weekly active teams with 3+ collaborators
  |
  +-- Acquisition: New signups/week
  |     +-- Website visitors
  |     +-- Signup conversion rate
  |
  +-- Activation: % who invite a teammate in 7 days
  |     +-- Onboarding completion rate
  |     +-- Time to first shared project
  |
  +-- Engagement: Documents edited per active team/week
  |     +-- Feature adoption (comments, mentions, sharing)
  |     +-- Return frequency
  |
  +-- Retention: % active at day 30
        +-- Weekly return rate
        +-- Feature breadth used

Each leaf is a metric a team can directly influence. The tree shows HOW inputs drive the North Star.

构建一棵将North Star Metric与可执行输入关联起来的树状结构：

North Star: Weekly active teams with 3+ collaborators
  |
  +-- Acquisition: New signups/week
  |     +-- Website visitors
  |     +-- Signup conversion rate
  |
  +-- Activation: % who invite a teammate in 7 days
  |     +-- Onboarding completion rate
  |     +-- Time to first shared project
  |
  +-- Engagement: Documents edited per active team/week
  |     +-- Feature adoption (comments, mentions, sharing)
  |     +-- Return frequency
  |
  +-- Retention: % active at day 30
        +-- Weekly return rate
        +-- Feature breadth used

每个叶子节点都是团队可以直接影响的指标。这棵树展示了输入指标如何驱动North Star Metric。

Counter-Metrics

EVERY metric gets a counter-metric. This prevents gaming and ensures you're not optimizing one thing at the expense of another.

Metric	Counter-Metric
Signup conversion rate	Activation rate (don't lower the bar to get signups)
Time to first value	30-day retention (don't rush users past learning)
Feature adoption	Task completion rate (don't push features that confuse)
Revenue per user	Churn rate (don't squeeze users into leaving)

If the metric improves but the counter-metric degrades, you've optimized the wrong thing.

每个指标都必须配备一个Counter-Metrics（反向指标）。这可以防止指标操纵，并确保你不会为了优化某一个指标而牺牲其他方面。

指标	反向指标
注册转化率	激活率（不要为了提升注册量而降低门槛）
首次获得价值时长	30天留存率（不要催促用户跳过学习环节）
功能使用率	任务完成率（不要推送会造成用户困惑的功能）
每用户收入	流失率（不要过度压榨用户导致其流失）

如果指标有所改善但反向指标出现下滑，说明你优化了错误的方向。

Guidelines

指导原则

CRITICAL: ALWAYS pair every metric with a counter-metric. No exceptions.
NEVER use vanity metrics: total signups, page views, total users, app downloads. These only go up and tell you nothing.
NEVER track more than 5-7 metrics actively. If your dashboard has 20 charts, nobody looks at any of them.
ALWAYS define metrics with exact formulas. "Activation rate" means nothing. "Percentage of new signups who invite at least one teammate within 7 days of account creation" is a metric.
ALWAYS set a baseline before setting a target. You can't improve what you haven't measured.
NEVER set targets without understanding the current number and why it's where it is.
ALWAYS measure outcomes (user behavior) over outputs (features shipped).

Built on Amplitude's North Star framework and the Linear Method. Skills from productskills.

关键原则：务必为每个指标搭配对应的Counter-Metrics，无一例外。
切勿使用虚荣指标：总注册量、页面浏览量、总用户数、应用下载量。这些指标只会持续增长，却无法提供任何有效信息。
切勿同时主动追踪超过5-7个指标。如果你的仪表盘有20个图表，没人会去看其中任何一个。
务必为指标定义精确的计算公式。“激活率”毫无意义，“注册后7天内邀请至少一名队友的新用户占比”才是一个明确的指标。
设定目标前务必先确定基准值。你无法改善未被测量的事物。
在不了解当前数值及其背后原因的情况下，切勿设定目标。
务必优先衡量结果（用户行为）而非产出（已上线功能）。

基于Amplitude的North Star框架和Linear方法构建。技能源自productskills。