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

Customer journey analysis with PM4PY in Python.

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

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

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

Customer Purchasing Behavior Analysis and Sales Prediction

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

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

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

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.

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

Cab Investment Strategy in the US examines market trends, customer demographics, and profitability for Pink Cab and Yellow Cab, offering insights to guide strategic investment decisions through data analysis, visualizations, and forecasting.

The "Store Sales Database" project analyzes 100K sales entries, leveraging Python, SQL, and Power BI to manage, analyze, and visualize store performance. It provides insights into sales trends, regional performance, and customer behavior through real-time analytics, detailed reporting, and dynamic dashboards to support data-driven decisions.

This repository contains Power BI projects showcasing data analysis and interactive dashboards. Each project includes detailed visualizations and insights on diverse topics such as loan analysis, sales performance, and customer behavior.

This project segments customers based on purchasing behavior and demographics to enhance marketing strategies and improve customer satisfaction. A Decision Tree classifier is utilized to predict customer responses to marketing campaigns using various customer attributes.

An interactive Tableau project showcasing advanced data visualization techniques for sales performance and customer analytics. This dashboard provides key business insights using KPIs, trend analysis, and customer segmentation. Designed for executives, sales managers, and marketing teams to drive data-driven decision-making.

This project is focused on identifying key products that contribute significantly to revenue and analyzing customer purchase behavior