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Daily, weekly and monthly stickiness

Report active-user counts over time to monitor engagement trends.

Authored by Intempt Technologies

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Agentic workflow

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1 step Blu runs end to end. It drafts a plan and nothing runs until you approve it.

  1. 1

    Track daily against monthly use

    Coming soon

    Blu builds a step

About this recipe

When to use it

MAU alone tells you reach, not habit. This tracks DAU, WAU, and MAU together with the stickiness ratios that actually measure whether people are coming back daily or just once a month.

What it delivers

Tracks daily, weekly, and monthly active users together with the standard stickiness ratios (DAU/WAU and DAU/MAU) used as the core PLG engagement benchmark.

How you prompt this

Describe the outcome in your own words and Blu Agent maps it to this recipe, or run it by name. It drafts a plan first and nothing runs until you approve it.

Tell Blu Agent what you want

“Report active-user counts over time to monitor engagement trends.”

recipe.md preview

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Inputs & outputs

What the recipe needs before it runs, and what it leaves in your workspace.

Inputs

  1. Nothing declared beyond an Intempt workspace. Blu asks for anything else it needs as it goes.

Outputs

    How the recipe runs

    Blu follows the steps in order and shows you each one before anything goes live.

    1. 01Track daily against monthly useCreate an Insights report called "DAU / WAU / MAU Stickiness". Series A: Event "Session start", aggregation: Count Unique Users, time granularity: Daily, label: "DAU" Series B: Event "Session start", aggregation: Count Unique Users, rolling 7-day window, label: "WAU" Series C: Event "Session start", aggregation: Count Unique Users, rolling 28-day window, label: "MAU" Series D: Computed: Series A / Series B × 100, unit: %, label: "DAU/WAU Stickiness" Series E: Computed: Series A / Series C × 100, unit: %, label: "DAU/MAU Stickiness" Time granularity: Daily (smooth Series D and E with 7-day rolling average to reduce noise) Time range: Last 90 days Breakdown: By Plan: resolved from the user's most-recent active subscription Compare: Year-over-year (same 90-day window prior year) Chart type: Dual-axis: left axis user counts (A/B/C as lines), right axis stickiness % (D and E as lines) Annotations: - Add benchmarks: DAU/MAU ≥ 20% is "good" for B2B SaaS; ≥ 50% is best-in-class. - Add benchmarks: DAU/WAU ≥ 50% indicates strong daily-habit usage. - Flag any plan where DAU/MAU stickiness dropped >3 percentage points vs. previous period (engagement erosion: leading indicator of churn). - Flag any plan where MAU is growing but DAU is flat (acquiring users who aren't engaging). Stickiness leads retention by 1-2 quarters; it's the canary in the coal mine. Taxonomy notes: - Session start is the canonical "user is active" event. Alternative: identify, but Session start is more frequent and reliable. - plan_tier as a User property does not exist; Plan comes from the user's Subscription started.

    Install Intempt and run it

    1. 1

      Sign up

      Create a free Intempt workspace.

    2. 2

      Connect your data

      Add the sources this recipe reads from.

    3. 3

      Ask Blu

      Type /stickiness-ratios-dau-wau-mau in Blu once this recipe is live there.

    4. 4

      Review and approve

      Blu builds each step and waits for your OK before anything goes live.

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