Customer Segmentation using RFM Analysis, categorizing customers based on recency, frequency, and monetary values, and devised tailored marketing strategies. SQL for data processing and Power BI for visualization, enhancing customer targeting and engagement.
This project aims to perform Cohort Analysis to analyze the retention rate of customers using SQL and Tableau. The dataset used in this project is sourced from the Online Retail dataset.
In this project, we will conduct a thorough analysis of the AB-test results to determine the effect of moving the first gate from level 30 to level 40 on player retention. By examining the player retention rates between the two groups, we aim to draw valuable insights to help optimize the game's design and enhance the overall user experience.
The project's goal is to extract relevant information about properties in Ho Chi Minh City (HCMC). The web scraping process will involve navigating the websites, accessing property listings, and retrieving data such as property types, prices, locations, and additional details. To accomplish this, I will employ web scraping techniques using appropriate tools and libraries BeautifulSoup and Selenium in Python.
The project utilizes a dataset crawled from the Amazon Book website, using Tableau tools for data visualization.
This project focuses on analyzing music store data using SQL. It involves querying and exploring the dataset to find answers to various questions related to the music store operations. The project is divided into three parts, each addressing different aspects of the data.
The project involves developing a web scraping tool or script that will navigate through the Amazon website, specifically targeting the IT book category.