ecommerce-advisor

E-commerce Advisor

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.

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Keywords

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

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Clarify First

Before building the model, confirm these inputs. If any is unknown or vague, ASK — do not assume:

• [ ] Single channel or blended — model each channel (DTC, Amazon, wholesale) separately; a blended model hides an unprofitable channel and makes contribution margin meaningless
• [ ] AOV and COGS — average order value and landed cost of goods (drives gross margin, the top line of the model)
• [ ] Returns/refund rate — returns eat margin twice (the sale plus reverse logistics), so this swings contribution margin
• [ ] CAC basis — true paid/blended CAC and what ad spend is counted (drives CAC payback period and break-even repeat rate)

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.

Quick Start

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.

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Core Workflows

Workflow 1: Unit Economics Model

1. Build a JSON config: COGS, fulfillment cost, payment processing %, returns %, ad spend %, AOV
2. Run calculator: python scripts/ecom_unit_economics_calculator.py model.json
3. Identify the marginal cost line items eating most of the margin
4. Decide: cut costs, raise price, change channel mix, or kill the SKU

Time Estimate: 2-4 weeks for first robust model.

Workflow 2: Fulfillment Strategy

1. Read references/fulfillment_models.md
2. Score each model (DTC self-fulfilled, 3PL, Amazon FBA, dropship, retail) for your stage and SKU profile
3. Migrate fulfillment as you scale — most brands change models 2-3 times in their first 3 years

Time Estimate: 4-8 weeks per major fulfillment transition.

Workflow 3: Channel Strategy

1. Read references/channel_strategy.md
2. Decide channel mix: DTC site, Amazon, wholesale, retail, marketplace
3. Each channel has distinct unit economics — model them separately, never blend
4. Sequence: most brands start DTC, add Amazon, add wholesale / retail

Time Estimate: Continuous, with major decisions every 6-12 months.

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Tools

ecom_unit_economics_calculator.py

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:

• Gross margin (% and absolute)
• Contribution margin (after marginal CAC)
• CAC payback period (months)
• Break-even repeat rate

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Reference Guides

• references/fulfillment_models.md — DTC self, 3PL, FBA, dropship, retail — when each fits
• references/channel_strategy.md — DTC site, Amazon, wholesale, retail — economics per channel

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Templates

• assets/unit_economics_template.json — Input file for the calculator with example values

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Best Practices

• Model channels separately. A blended LTV across DTC and Amazon hides the fact that Amazon may be unprofitable.
• Returns and refunds compound. A 15% return rate eats into margin twice — once on the initial sale, once on the reverse logistics.
• Plan for inventory. Working capital tied up in inventory is the #1 cash-flow killer for product brands.
• Don't fall in love with revenue. $10M revenue at 5% contribution margin is worse than $3M revenue at 30% contribution margin.
• Be honest about CAC. Most DTC brands subsidize CAC and call it growth. CAC payback under 6 months is the bar.