Ramp plan
A merchant onboarding model that balances budget, headcount and shipping costs, with what-if scenarios and goal-seek.
Recreated on dummy data. Every name, figure and date in the recreation is invented.
Problem: Onboarding merchants had to fit a budget, a small team’s bandwidth and freight economics at once. Too much cheap inventory makes shipping uneconomical, while the program aimed to cover as much of the marketplace as it could.
What I built:
- Sliders and inputs for risk levels and strategy goals.
- What-if and goal-seek scenarios that update as soon as an input changes.
- Recommended baseline scenarios for quick reference.
- An automatic priority list where operators mark merchants onboarded, rejected or pending, and the plan updates around them.
How I worked with AI: I recreated it here with Claude Code in VS Code, from my own description, on dummy data.
Decisions and trade-offs:
- I treated the inputs as one system, because changing one can break another. The cost is that no input can be tuned on its own.
- I kept a qualification gate on cheap catalogs. The cost is slower coverage of the marketplace.
What changed: The program grew merchants nearly 14x and monthly orders 5x within four months of the pilot, reaching about 20% of weekly marketplace gross merchandise value.
Links: The recreation is below. Dummy data generator ยท Dummy data