Objective:
Identify frequent product combinations to optimize product placement in the store.
What I did:
- Collected and cleaned sales transaction data
- Applied FP-Growth algorithm to find frequent itemsets
- Generated association rules based on support and confidence
Result / Insight:
- Recommended product placements based on items frequently bought together
- Suggested potential product bundles for promotion
- Improved understanding of customer purchasing patterns