name: feature_adoption
display_name: Feature Adoption Rate
category: product_usage
type: ratio
unit: percentage
grain: monthly
table: user_events
expression: "COUNT(DISTINCT feature_users) / COUNT(DISTINCT total_users) * 100"
time_column: event_date
description: "Feature Adoption Rate — the percentage of active users who used a specific feature in a given month."
dimensions:
  - feature
  - plan_type
synonyms:
  - feature_usage_rate
  - adoption_rate
notes:
  - "Denominator is all MAU for the period, numerator is MAU who triggered the feature event"
  - "Track each feature separately by filtering on feature_name or event_type"
  - "Adoption >20% within 90 days of launch is a common success threshold"
sql: |
  WITH monthly_active AS (
      SELECT
          DATE_TRUNC('month', event_date) AS month,
          COUNT(DISTINCT user_id) AS total_users
      FROM user_events
      WHERE event_type != 'internal'
      GROUP BY 1
  ),
  feature_users AS (
      SELECT
          DATE_TRUNC('month', event_date) AS month,
          feature_name,
          COUNT(DISTINCT user_id) AS users_adopted
      FROM user_events
      WHERE event_type = 'feature_used'
        AND event_type != 'internal'
      GROUP BY 1, 2
  )
  SELECT
      f.month,
      f.feature_name,
      f.users_adopted,
      m.total_users,
      ROUND(f.users_adopted * 100.0 / NULLIF(m.total_users, 0), 2) AS adoption_rate_pct
  FROM feature_users f
  JOIN monthly_active m ON f.month = m.month
  ORDER BY f.month, adoption_rate_pct DESC