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What is your DAU/MAU ratio — and is it improving?

DAU/MAU is the standard measure of product stickiness. This query calculates it from your Snowflake event data month by month, so you can track engagement trends over time.

📊 Snowflake👥 Product and growth teams🔤 Plain-English → SQL
Show me daily active users and monthly active users ratio for each month in the last 6 months
Snowflake DAU/MAU Ratio Query — generated by Taptic Data AI
WITH daily_active AS (
  SELECT
    DATE_TRUNC('month', event_date)::date  AS month,
    event_date::date                       AS day,
    COUNT(DISTINCT user_id)                AS dau
  FROM user_events
  WHERE event_date >= DATEADD('month', -6, CURRENT_DATE)
  GROUP BY 1, 2
),
monthly_active AS (
  SELECT
    DATE_TRUNC('month', event_date)::date  AS month,
    COUNT(DISTINCT user_id)                AS mau
  FROM user_events
  WHERE event_date >= DATEADD('month', -6, CURRENT_DATE)
  GROUP BY 1
),
avg_dau AS (
  SELECT month, ROUND(AVG(dau), 0) AS avg_dau
  FROM daily_active
  GROUP BY month
)
SELECT
  TO_CHAR(m.month, 'YYYY-MM')                           AS month,
  a.avg_dau,
  m.mau,
  ROUND(a.avg_dau * 100.0 / NULLIF(m.mau, 0), 1)      AS dau_mau_ratio_pct
FROM monthly_active m
JOIN avg_dau a ON a.month = m.month
ORDER BY month ASC
Schema-aware SQL generated from plain English30 lines

This query was generated by Taptic Data from plain English against a real Snowflake schema. In Taptic, you type the question — the AI writes the SQL, runs it, and returns the result. You can edit the SQL, ask for explanations, and save it as a refreshable report. This type of analysis is commonly used in ai business analytics and text to sql tool.

Breaking it down line by line

  1. First CTE computes DAU per day per month from your event table
  2. Second CTE computes MAU (unique users per calendar month)
  3. Third CTE averages DAU across all days in the month to get a stable avg_dau figure
  4. Final SELECT joins both to compute DAU/MAU ratio as a percentage
  5. NULLIF prevents division by zero for months with no MAU data

Result description

Monthly table with average DAU, MAU, and DAU/MAU ratio as a percentage for the last 6 months — ready to trend as a line chart.

The business impact

A DAU/MAU ratio above 20% is considered good for most SaaS products; above 50% is exceptional. Tracking it monthly shows whether product changes are improving engagement or whether your active user base is drifting toward dormancy.

All queries and use cases on this page relate to analyzing your Snowflake data in Taptic. To see the full analytics workflow, explore ai business analytics, text to sql tool.

Common questions

How do I generate a "Snowflake DAU/MAU Ratio Query" query automatically?
In Taptic Data, type "Show me daily active users and monthly active users ratio for each month in the last 6 months" and the AI generates schema-aware SQL against your real Snowflake data — no manual writing required.
What database does this query work with?
This query is designed for Snowflake. Taptic reads your live schema so the generated SQL always matches your actual table and column names.
Can I edit the generated SQL?
Yes. Taptic shows you the exact SQL it generated. You can edit it directly, ask the AI to explain any line, or request a revision in plain English.
Can I save this as a scheduled report?
Yes. Once you run this query in Taptic, you can save it as a report, add charts and KPIs, and schedule it to email your team on any cadence — daily, weekly, or monthly.

Skip the SQL. Ask the question.

In Taptic Data, you type "Show me daily active users and monthly active users ratio fo..." and this SQL runs automatically against your real Snowflake data.

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