Forecasts with teeth
You leave with a model you can defend: assumptions listed, confidence bands drawn, and a written “what would falsify this” note for stakeholders.
Servertrailcore
LTV Forecasting for Apps · Bangkok studio
We train product and growth teams to read retention noise, build honest payback windows, and ship forecasts that survive a real release cycle.
Cohort-first practice
2,183
learners across SEA cohorts
63%
reported tighter payback estimates
41
live forecast critique sessions
Flagship on the trail
One intensive path. Modules move from raw event logs to board-ready LTV narratives without pretending uncertainty disappears.
Flagship
Forecast Trail Intensive
Eight weeks of cohort windows, survival curves, and critique circles built for consumer and fintech apps.
Why teams stay
Thailand market texture
Examples pull from SEA payment rails, festival seasonality, and dual-store pricing quirks — not generic Silicon Valley case packs.
Critique over cheerleading
Weekly review circles poke holes in optimistic curves before they reach a roadmap deck.
Voices from the trail
The payback module forced our UA lead to stop averaging iOS and Android into one fantasy curve. We still argue about month-four decay, but at least the argument has numbers.
Useful, though the spreadsheet templates assume cleaner event naming than our legacy build had. Once we cleaned that, Forecast Trail Intensive clicked.
Bring your messy event log
We will help you turn it into a forecast trail your team can actually walk.