An exploratory data analysis project on 1,465 Amazon product listings across 9 categories. The dataset includes real pricing, discount, rating, and review data — making it ideal for understanding Amazon's pricing strategy, discount patterns, and customer behavior. Unlike previous EDA projects, this one focuses on business insights rather than scientific or behavioral patterns.
Analyze pricing and discount patterns across Amazon product categories
Identify which categories are most discounted, most expensive, and best rated
Understand the relationship between price, discount, and customer ratings
Find the top performing products by reviews and ratings
Process
Cleaned price columns by removing ₹ and comma symbols and converting to float
Extracted main category from nested category strings using string splitting
Added two engineered features — savings (actual minus discounted price) and discount tier (binned into 5 ranges)
Built 19 visualizations across 5 sections — category, price, rating, discount, and product analysis
Insights
Electronics is the core revenue driver — highest product count (526) and highest average price (₹10,127)
Office Products has the highest average rating (4.31) with nearly zero discounting — suggesting loyal professional buyers who don't need price incentives
Discount percentage has near-zero correlation with rating (-0.16) — sellers cannot buy better ratings through higher discounts
AmazonBasics dominates the most reviewed products with 426,973 reviews — the in-house brand has captured massive customer trust for basic accessories
The 41–60% discount tier is the sweet spot — 508 products fall here, suggesting Amazon and sellers have converged on this as the optimal pricing strategy
Cables and accessories are discounted up to 94% — likely used as loss leaders to drive traffic to product pages
This case study documents a portfolio analysis. Findings describe this dataset and should be interpreted within its limitations. Dataset source ↗