Luxxify: Ulta Makeup Reviews

Hey everyone,

I recently released an open source dataset containing Ulta makeup products and its corresponding reviews!

Custom Created Kaggle Dataset via Webscraping: Luxxify: Ulta Makeup Reviews

Feel free to use the dataset I created for your own projects!

Webscraping Process

Web Scraping: Product and review data are scraped from Ulta, which is a popular e-commerce site for cosmetics. This raw data serves as the foundation for a robust recommendation engine, with a custom scraper built using requests, Selenium, and BeautifulSoup4. Selenium was used to perform button click and scroll interactions on the Ulta site to dynamically load data. I then used requests to access specific URLs from XHR GET requests. Finally, I used BeautifulSoup4 for scraping static text data. Leveraging PostgreSQL UDFs For Feature Extraction: For data management, I chose PostgreSQL so that I could clean the scraped data from Ulta. This data was originally stored in a complex JSON which needed to be unrolled in Postgres.

As an example, I made a recommender model using this dataset which benefited greatly from its richness and diversity.

To use the Luxxify Makeup Recommender click on this link: https://luxxify.streamlit.app/

I’d greatly appreciate any suggestions and feedback 🙂

Link to GitHub Repo