Telemetry
Product analytics SQL recipe

Measure Time to Activation

Calculate the distribution of elapsed time between signup and a user’s first meaningful product action.

Advancedproduct_eventsReviewed 2026-07-27

Question answered

How long does it take new users to reach the first meaningful action?

Conversion rate says whether activation happened. Time to activation reveals friction among the users who did activate and helps set an honest onboarding window.

Event contract

Fields the query expects

FieldTypeWhy it exists
timestamp_utcTimestampEvent time.
user_idUtf8Stable user identifier.
event_nameUtf8Signup or activation milestone.
DataFusion SQL

Copy the query

sql
WITH milestones AS (
  SELECT
    user_id,
    MIN(CASE
      WHEN event_name = 'signup_completed' THEN timestamp_utc
    END) AS signed_up_at,
    MIN(CASE
      WHEN event_name = 'first_meaningful_action_completed' THEN timestamp_utc
    END) AS activated_at
  FROM product_events
  WHERE timestamp_utc >= now() - INTERVAL '90 days'
  GROUP BY user_id
)
SELECT
  CASE
    WHEN activated_at - signed_up_at < INTERVAL '10 minutes' THEN 'under 10m'
    WHEN activated_at - signed_up_at < INTERVAL '1 hour' THEN '10m–1h'
    WHEN activated_at - signed_up_at < INTERVAL '1 day' THEN '1h–1d'
    WHEN activated_at - signed_up_at < INTERVAL '7 days' THEN '1d–7d'
    ELSE '7d+'
  END AS activation_window,
  COUNT(*) AS users
FROM milestones
WHERE signed_up_at IS NOT NULL
  AND activated_at >= signed_up_at
GROUP BY activation_window
ORDER BY users DESC;

This recipe is read-only and reviewed against Telemetry's DataFusion query patterns. Sample output is deterministic and synthetic; validate field types, thresholds, and business definitions against your own data.

Query result

Activated users by time-to-value window

Most activated users reach value within one day, but the distribution has a meaningful multi-day tail.

activation_windowusers
under 10m182
10m–1h264
1h–1d318
1d–7d146
7d+38

Synthetic example output. Run the query against your own event schema and thresholds before using it for operational decisions.

How the SQL works

  1. 1MIN over conditional CASE expressions finds each user’s first signup and activation timestamp.
  2. 2The CASE expression converts elapsed time into operationally readable buckets.
  3. 3Users who never activate are excluded from this distribution and belong in the funnel conversion view.

Edge cases to decide

  • Imported or invited users may have a different starting event.
  • Activation before signup usually indicates identity merging or historical backfill.
  • Choose buckets that reflect the product’s natural usage cycle.

Recommended dashboard

  • Distribution: users by activation window
  • Stat: median time to activation
  • Table: non-activated signups by age

Alert guidance

Use the distribution for product review; alert only when instrumentation stops or activation volume collapses.

Read alert setup

Put the recipe to work

Related instrumentation and guides

Continue the analysis

Run it on real events

Create a table, adapt the fields, and save the result

Start free, send structured events, and use the query result as a chart, shared dashboard widget, or alert input.

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