Projects
Amazon Running Shoes Case Study
The Running Shoes (and Trail Running Shoes) dataset serve as a toolkit for buyers or sellers seeking knowledge of running shoe brands and their products on the Amazon platform. This dataset, curated from Amazon product postings, provides a comprehensive view of the running shoes and trail running shoes market for both men, women, and unisex shoes. Scraped data using Python, imported into an excel csv file, then imported to a MySQL database for cleaning and wrangling data using PopSQL as a text editor. The results were visualized through PowerBi.
RFM Analysis: Online Retail Customers
The RFM (Recency, Frequency, Monetary Value) Analysis on online retail customers serves the purpose to enhance customer segmentation and help drive targeted marketing strategies. Utilizing a dataset from Kaggle on online retail customers, it encompasses transactional records that include Invoice Number, Stock Code, Description, Quantity, Invoice Date and Time, Unit Price, Customer ID, and Country. This analysis provides insights into customer behavior, and sales effectiveness, by categorizing customers based on their transaction through recency, frequency, and monetary value.
Portland Airbnb Listings
Airbnb listings data dashboard that can provide valuable insights to a buyer who is interested in purchasing a property to list on Airbnb in the Portland area. This type of dashboard displays information on the performance of Airbnb listings by region and neighborhood, including data on number of listings by region, average listing rates, and listing type (condo, apartment, etc) and more.
