Research
Conjoint Analysis for Sustainable Fashion Brand
Overview
What this challenge is about.
You will design a choice-based conjoint (CBC) survey with 4 attributes (price, material, color options, warranty) each with 3-4 levels. You must collect responses from at least 100 participants (simulated data provided if needed), analyze the data using multinomial logit (MNL) or hierarchical Bayes, and compute part-worth utilities and attribute importance. Deliver a recommendation for the optimal product profile and a pricing strategy. Success is a clear, data-driven recommendation with sensitivity analysis.
The Brief
What you'll do, and what you'll demonstrate.
What is the optimal combination of price, material, color options, and warranty for EcoWear's new jacket line to maximize customer preference?
Earning criteria — what you'll demonstrate
- Design a choice-based conjoint experiment with appropriate attributes and levels
- Analyze conjoint data using multinomial logit or hierarchical Bayes models
- Compute part-worth utilities and attribute importance to inform product design
- Simulate market shares for different product configurations
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
Careers
Roles this prepares you for.
Real titles. Real skill bridges. Pick the one closest to your trajectory.
Career mappings coming soon.