Amazon E-Commerce Sales Strategy
Analyzed product portfolio optimization by applying K-Means clustering to 42,000+ Amazon products, identifying high-value Cash Cows and surfacing $241.7M in revenue recovery opportunities. Quantified revenue leakage exposure by detecting inventory gaps across 522 high-velocity SKUs using sales and stock gap analysis, justifying immediate automated restocking deployment. Evaluated pricing strategy effectiveness by measuring price–sales correlation analysis (r = -0.28), confirming significant price elasticity signals to support pricing adjustments. Assessed SKU performance risk by conducting product rating analysis to identify 72 Toxic SKUs (≤ 0.14 rating threshold), enabling immediate discontinuation of inefficient advertising spend.
View ProjectAmazon faced visibility gaps across 42,000+ product listings, causing lost GMV and revenue leakage from stockouts and suboptimal inventory/pricing.
Recover lost GMV and optimize inventory and pricing through data-driven segmentation and targeted interventions.
Deployed K-Means clustering (6 segments) and correlation analysis on 42k+ SKUs to measure how price and ratings drive sales velocity; automated restock cycles and SEO optimization for high-potential products.
Identified $241.7M in trapped capital (Ghost Inventory) and $113M in leaked revenue from stockouts. Automated restocks for 522 high-velocity items; optimized SEO for 2,030 high-potential products. Projected 20% annual revenue uplift ($130.1M).