Wish.com Product Listing Analysis

This project analyzes key factors influencing product sales on Wish.com, focusing on listings that appeared under the search term "summer" in July 2020. Using a dataset of 1,329 cleaned product listings, the analysis explores the impact of price, retail price, units sold, ratings, and other product metrics on sales performance.

Identifies which factors (e.g., price, ratings, discounts) most significantly affect units sold.

Helps merchants optimize product listings to increase sales and avoid unnecessary trial and error.

Provides actionable insights that could benefit Wish.com corporate for resource guides, blog content, and marketing strategies.

This project delivers data-driven recommendations to improve seller success on Wish.com, making it a valuable resource for both merchants and platform stakeholders.

https://colab.research.google.com/drive/175pf2iL9QlR0-dcbNjagu9I0rOONLFgg?authuser=1