Show Notes
Every forecast is wrong. The question is whether yours is useful. Luke Austin, walks through the CTC Methodology series opener: a complete operating model for making profit predictable across ecommerce brands. This is not a spreadsheet. It is a four-step system built on 12 years of experience and $4 billion in GMV, combining proprietary data science with daily operational discipline to hit 3% forecast accuracy at scale. Topics covered in this episode: Why all models are wrong and what makes the best ones useful
The "tigers not mice" framework for prioritizing what actually matters
Qualitative planning: how a 12-month marketing calendar becomes a mathematical input
The Spending Power (AMER) model and three optimization modes for new customer spend
Cohort LTV modeling: why active vs. lapsed customer distinction changes everything
The Event Effect model: how marketing moments get quantified, not just scheduled
Building a full P&L forecast from customer cohorts up, not channel metrics down
Why contribution margin is the north star metric, not ROAS
Plot, Pivot, Profit: the daily cadence that makes forecasts self-correcting
The "What / So What / Now What" daily operating format used by CTC profit engineers
Results: 3% forecast accuracy across $4B GMV, 32% avg revenue growth, 41% avg CM growth
This is Episode 1 of the CTC Canon Series. The Canon represents CTC's cumulative operating principles across 12-plus years and hundreds of brands, covering forecasting, media buying, creative strategy, email, and media measurement. Show Notes: Go to https://bit.ly/4aiEz79 to start your free migration with Omnisend today
Explore the Prophit Engine: https://commonthreadco.com/pages/prophit-engine
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