What problem does it solve? Ecommerce teams often cannot tell whether their customer acquisition spending is actually profitable because CAC, LTV, and payback period are scattered across ad platforms, analytics apps, and spreadsheets. This Skill provides a structured methodology for computing unit economics correctly — using contribution margin instead of revenue, segmenting by channel and cohort, and setting budget guardrails. ## Core Features & Use Cases - CAC Calculation: Compute blended, paid, and fully-loaded CAC by channel using tools like Lifetimely, Triple Whale, Metorik, or manual exports, with channel-level benchmarks. - LTV and Payback Modeling: Build observed cohort LTV curves and predicted LTV formulas, then derive LTV:CAC ratios and payback periods with health thresholds (2:1 minimum, 3:1 healthy, 5:1 excellent). - Guardrails and Trend Monitoring: Set maximum allowable CAC per channel (LTV / target ratio) and monitor weekly CAC trends to catch channel saturation early. - Use Case: When preparing investor materials, use this Skill to present defensible unit economics — fully-loaded CAC by channel, cohort LTV curves, and payback periods — that survive due diligence scrutiny. ## Quick Start Ask the AI to calculate fully-loaded CAC and 12-month LTV by acquisition channel for your Shopify store and assess each channel against the 3:1 LTV:CAC benchmark.
