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ecommerce-advisor【效率与协作】Strategic advisory for e-commerce founders on unit economics, fulfillment models, payments, and channel strategy. Use when evaluating an ecommerce idea or modeling unit economics, or mentioning DTC, Shopify, Amazon, 3PL, or CAC.
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Strategic frameworks for e-commerce founders, operators, and brand builders. Most ecommerce decisions are unit-economics decisions — knowing the math is the difference between a brand that compounds and one that subsidizes itself out of existence.
ecommerce, e-commerce, DTC, direct-to-consumer, Shopify, Amazon, retail, wholesale, 3PL, fulfillment, dropship, unit economics, contribution margin, CAC, AOV, LTV, returns, refunds, payment processing, interchange
Before building the model, confirm these inputs. If any is unknown or vague, ASK — do not assume:
Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the model.
python scripts/ecom_unit_economics_calculator.py model.json
Calculates gross margin, contribution margin, CAC payback, and per-order profit from a structured input file.
python scripts/ecom_unit_economics_calculator.py model.jsonTime Estimate: 2-4 weeks for first robust model.
references/fulfillment_models.mdTime Estimate: 4-8 weeks per major fulfillment transition.
references/channel_strategy.mdTime Estimate: Continuous, with major decisions every 6-12 months.
Models per-order, per-month, and CAC-payback economics from a structured input.
python scripts/ecom_unit_economics_calculator.py model.json
python scripts/ecom_unit_economics_calculator.py model.json --json
Input model schema in the script's docstring; example in assets/unit_economics_template.json.
Outputs:
references/fulfillment_models.md — DTC self, 3PL, FBA, dropship, retail — when each fitsreferences/channel_strategy.md — DTC site, Amazon, wholesale, retail — economics per channelassets/unit_economics_template.json — Input file for the calculator with example values