Forecast Trail Intensive
Build a defendable LTV model for a live or sandbox app: cohort design, survival curves, payback math, and a critique-ready memo for stakeholders.
Modules
Event honesty
Audit naming, duplicates, and silent drop-offs before any curve is trusted.
Cohort windows
Choose windows that match billing cycles instead of vanity seven-day cutoffs.
Retention shapes
Read elbows, plateaus, and seasonality bumps without forcing a single formula.
Revenue bridges
Connect ARPU, refunds, and store fees into a payback story finance will accept.
Forecast critique
Present, defend, and revise under peer and instructor pressure.
Learning outcomes
- Produce a documented LTV range with explicit assumptions and falsifiers.
- Separate platform, channel, and country effects in Southeast Asia samples.
- Write a one-page memo that product, UA, and finance can argue from together.
Instructor
Arisa Wongsawat
Former growth analytics lead for consumer apps across Thailand and Vietnam. Arisa runs critique circles and insists every forecast states what would prove it wrong.
Informational pricing
No checkout on this site. Figures below help planning conversations; final invoices are arranged after a fit call.
THB 28,500
Per seat · eight weeks · includes labs, critique circles, and template pack. Team desks priced separately on Pricing.
FAQ
Do I need SQL fluency?
Comfortable querying helps. We provide spreadsheet-first paths, but messy joins still slow you down — that is a real limitation if your warehouse access is blocked.
Is this only for subscription apps?
No. Hybrid and ad-supported models are covered, with different payback framing.
What is not included?
We do not implement production pipelines or guarantee investor outcomes. The course builds judgment, not a black-box score.
Learner notes
Module three’s retention shapes lab finally explained why our holiday spike ruined a linear extrapolation we had been showing weekly.
Clear on critique day with Arisa. I wanted more mobile-game examples; the pack leans consumer utility and fintech.