product-conjoint-analysis
Product Conjoint Analysis
A reusable end-to-end workflow for conjoint analysis, distilled from a working case study (safety glasses on Amazon, N=160). It covers data acquisition, attribute engineering, experimental design, logistic regression estimation, and the four canonical insight transforms (importance, WTP, choice probability, cost-benefit ROI).
The skill is opinionated about decisions that beginners commonly get wrong — choice of reference levels, when to split models for collinearity, why price needs special handling for importance, when WTP is meaningful, etc. Read this file fully on first use, then consult the references/ folder when you hit a specific decision point.
When to use this skill
Trigger on any of these intents:
- "I want to know which product attributes matter most to customers"
- "How much would customers pay for [feature X]?"
- "Help me design a conjoint study / choice experiment"
- "Analyze this product/review data to figure out optimal configuration"
- "I have purchase records — can you reverse-engineer preferences?"
- Any mention of: conjoint, part-worth utility, trade-off analysis, discrete choice, attribute importance, willingness-to-pay (WTP), 聯合分析, 屬性重要性, 願付價格
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