BlackPrint Technologies · Aug 2026
Motorcycle Retail Area Study
Corridor Attractiveness & Bottom-Up Sales Projection
Overview
Delivered a bilingual area study for a motorcycle brand's new point of sale in a large State of Mexico municipality, ranking four commercial corridors with a seven-factor attractiveness index and projecting monthly unit sales bottom-up from official registration and census data.
Highlights
- 01
Built a 30-script Python pipeline feeding a static MapLibre + ECharts report that reads every figure from JSON at runtime, with no hand-typed numbers.
- 02
Designed a seven-factor corridor index and stress-tested it by moving each weight ±50%; the top corridor stayed the same in every case.
- 03
Projected demand as a band by triangulating INEGI's definitive vehicle-registration series (+212,481 motorcycles in the State of Mexico in 2024) with census motorcycle ownership, and shipped Spanish and English editions on one data contract.
Stack
- Python
- PostgreSQL
- INEGI Census 2020
- INEGI VMRC Registrations
- ENIGH 2024
- DENUE
- H3
- Origin–Destination Mobility
- MapLibre GL
- ECharts
- Vercel
Working on something similar?
Tell me about the problem and the data behind it. I reply within 24–48 hours.
Discuss a project