Flagship course

Retention Windows Atelier

Twelve evenings in Bangkok. You bring a live export. You leave with a window policy your product room can rerun without you in the chair.

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Analytics interface used as a reference image for the atelier

What the weeks are for

The atelier is not a survey of every retention metric ever named. It is a working method for App Retention Cohort Analytics: clock-start, house windows (7 / 14 / 28), survival versus return, paywall interaction, and Thailand seasonality. Lectures stay short. Critique takes the hours.

You must bring a real product table by week four. Hypothetical apps are refused. If your company will not let data leave the building, we work from an anonymised extract you prepare in advance — still real, still messy.

Informational fee

48,500 THB

  • Twelve evening sessions, Tuesday and Thursday
  • Intake size capped so critique still works
  • English instruction only
  • No payment is taken on this website

Compare Clinic and Residency

Modules

  1. 01

    Window grammar

    What a cohort is, what it is not, and why “users who came back” is not yet a definition.

  2. 02

    Acquisition stamps

    First-open, first authenticated session, first order. Choosing one stamp and writing it down.

  3. 03

    Clock-start disputes

    The arguments that actually happen in Bangkok product rooms, and how to close them.

  4. 04

    Building Day-7, Day-14, Day-28

    House windows constructed from a messy export, with denominators visible.

  5. 05

    Survival versus return

    Still present, versus a named event happening again. Two tables, two sentences.

  6. 06

    Paywall and trial clocks

    How trial start contaminates a naive return curve, and how to split the windows.

  7. 07

    Thailand seasonality overlays

    Songkran, year-end commerce, late-night usage. Annotate, do not silently delete.

  8. 08

    Presenting to non-analysts

    A readout that can be spoken aloud. Colour is optional. The policy paragraph is not.

Evenings nine to twelve are critique only: your live table, alumni guests, and a final written window policy.

Learning outcomes

  • Write a clock-start that another analyst can reproduce from the same export.
  • Produce house-window tables for Day-7, Day-14, and Day-28 without mixing survival and return.
  • Annotate a Thailand holiday effect instead of calling it a product regression.
  • Deliver a ten-minute readout that does not depend on a vendor screenshot.
  • Know the edge of the craft: this atelier does not produce LTV forecasts.
Portrait of Arunwadee Srisuk, atelier instructor

Instructor

Arunwadee “Ann” Srisuk

Ann spent eleven years inside Bangkok super-app analytics rooms before opening Proxy Cloudhub. She still prefers a printed table to a live demo. Guest alumni join the last two critique nights.

FAQ

Do I need to be a data scientist?

No. You need spreadsheet fluency and a product you actually ship. We will not reteach pivot tables from zero. If that sentence worries you, start with Window Clinic or wait a quarter.

Is there a real limitation I should know before enrolling?

Yes. We do not teach predictive LTV, media-mix modelling, or SQL engineering. The atelier stays with descriptive cohort tables and window design. Materials are English only; Thai-language workbooks are not provided. If your company forbids any extract from leaving the office, you must prepare an anonymised file before week four or you cannot complete critique.

Where is it taught?

Street: 16 Soi 123 Ladprao Klong Chan Bang Kapi; City: Bangkok; State/province/area: Bangkok; Zip code: 10240; Country: Thailand. Telephone (02)7333910.

Can my whole team join?

Group bookings are possible only when each person brings a distinct table. One shared spreadsheet is not a group. See pricing.

Notes from people who sat it

The Day-28 reconstruction week was slower than I wanted. Ann would not skip timestamp cleanup. I still use that table.

Krittin M. · Growth lead, Bangkok

★★★★☆

I expected more dashboard polish. The studio is stubborn about spreadsheets first. That annoyed me in week two.

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