Analyse customer segmentation, sentiment on product review, and built a product recommender system
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Updated
Jan 15, 2021 - Jupyter Notebook
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
Analyze customer behavior using SQL and Python to extract insights on purchase patterns, sentiment analysis, and marketing effectiveness.
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.
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.
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.
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.
Customer Purchasing Behavior Analysis and Sales Prediction
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.
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.
End-to-end SQL and Tableau analysis of real user engagement, subscriptions, and learning outcomes on an online education platform.
Analyzing customer ordering behavior and product performance to enhance demand forecasting and customer experience.
Pizza Sales Analytics is an interactive Power BI dashboard that analyzes pizza orders and sales trends. It identifies peak ordering times, most popular pizzas, top-selling categories, and total revenue, helping businesses make data-driven decisions and optimize operations.
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.
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