Analyse customer segmentation, sentiment on product review, and built a product recommender system

Black Friday Sales Analysis explores customer demographics, purchasing behaviors, and product trends to uncover insights and patterns driving sales during Black Friday events.

Multivariate Time Series Classification for Human Activity Recognition with LSTM

Predicting whether users will click on a promotional email for laptops based on historical user data and browsing logs.

Customer journey analysis with PM4PY in Python.

This is a customer loyalty analysis based on historical purchase behavior in R language.

End-to-end data analytics project using Python, SQL, and Power BI to analyze customer shopping behavior, uncover insights, and visualize trends through an interactive dashboard.

Analyze customer behavior using SQL and Python to extract insights on purchase patterns, sentiment analysis, and marketing effectiveness.

Hotel Booking EDA Project -- Exploratory Data Analysis of hotel booking demand data (city & resort hotels) to uncover booking trends, cancellation behavior, customer preferences, and insights for hotel management.

This project explores customer behavior and sales trends to help this small restaurant thrive.

Customer Behavior Analysis project using Python and SQL to analyze customer demographics, engagement, product reviews, and purchase journeys for valuable business insights.

Building a nearest-neighbor classifier to predict online shopping purchase completions based on user browsing behavior. The project uses a dataset of 12,000 sessions, analyzing features like pages visited, session duration, and bounce rates

Estatística aplicada à análise de dados de clientes e planos da operadora Megaline. Projeto prático com Python, visualização e insights para suporte à decisão em telecom.

📊 Analyze customer churn, segment behavior, and uncover insights to improve retention for telecom firms using data visualization and advanced analysis techniques.

Predicts customer upgrade likelihood using logistic regression, random forest, and XGBoost. Features NLP techniques and memory optimization.

An interactive interface for performing CRUD operations (Create, Read, Update, Delete) on a MySQL database related to Zomato data.

This project utilizes machine learning to analyze and segment e-commerce customer behavior. It predicts purchases and clusters customers based on demographic data and product preferences, aiming to optimize marketing strategies and enhance customer satisfaction.

Customer Purchasing Behavior Analysis and Sales Prediction

This project focuses on RFM (Recency, Frequency, and Monetary) Analysis, a powerful customer segmentation technique used in marketing and business analytics. The analysis helps businesses identify their most valuable customers, potential loyalists, at-risk customers, and churned users.