Amazon Product Funnel & Performance

Amazon Product Funnel & Performance Analysis (Python + SQL + Looker Studio) Analyzed an Amazon product dataset to understand pricing behavior, product performance, and engagement-driven funnel patterns.

The project focused on identifying how products perform from listing characteristics through to engagement signals such as reviews and category-level competition.

Key work included:

Cleaned and structured a dataset of 224 Amazon product listings using Python (Pandas)

Standardized pricing and categorical fields for analysis readiness

Built SQL queries in BigQuery to extract performance insights across products and categories

Performed funnel-style analysis from product listing attributes → engagement metrics → review patterns

Identified concentration effects in product performance (Pareto distribution across categories)

Built a Looker Studio dashboard to visualize key metrics and category-level comparisons

Final output: an interactive analytics view of Amazon product performance and behavioral patterns.

This project demonstrates applied product analytics and funnel thinking in an e-commerce marketplace context.