A collection of reference Jupyter notebooks and demo AI/ML applications for enterprise use cases: marketing, pricing, supply chain, smart manufacturing, and more.

This repository contains the data source and the tableau workbook used in my YouTube video: https://www.youtube.com/watch?v=_qReGTOrKTk

Customer Personality Analysis Using Clustering

A Python-based repo for modeling and predicting customer behavior. This project focuses on implementing various statistical and probabilistic models to analyze customer preferences, purchase patterns, and future actions.

Explore the world of data-driven customer analysis and lifetime value estimation. This project dives into customer segmentation, geographic analysis, time series insights, stock trends, and product descriptions. Join us on our journey of data exploration and optimization.

Dive into the world of customer retention with this GitHub repository, Utilizing the power of tools like Power BI and Python libraries such as Numpy, Seaborn, and Tidyverse, we explore the factors driving customer churn and pinpoint their impact areas.

By understanding and predicting CLV, PT Asuransi Mobil Sejahtera can make better decisions about how much they should invest in customer acquisition and retention, as well as how they can improve customer satisfaction to increase CLV.

Customer Personality Analysis - A dataset of customer demographics, spending, and campaign history used to segment audiences, optimize targeted marketing, and boost ROI.

Gofood Exploratory Data Analysis and WordCloud (category,product,etc)

Excel dashboard analyzing customer behavior, segmentation, and revenue contribution

This is a Tableau project for data analytics where I have created a dashboard that compiles various sheets that are insights of customer json data. The dashboard is dynamic and varied. It can be extracted as a pdf.

Performed Recency, Frequency, and Monetary (RFM) analysis to classify customers into meaningful segments, supporting personalized marketing and retention strategies.

This is a supply chain analytics project focused on improving business profitability through customer, product, and market performance analysis . This project was built as a part of my internship at unified mentor pvt

Submission for the Data Analytics Program offered by KPMG Australia via Forage.

End-to-end Customer Trends Analysis project using SQL, Python, and Power BI. Includes data cleaning, exploratory data analysis, SQL querying, interactive dashboarding, and business insights.

Business Intelligence analysis of SaaS customer acquisition patterns and data quality audit using Python and Pandas.

Customer analysis on a bike-share program

Customer shopping behavior analysis using PostgreSQL, SQL, and Power BI to identify purchasing trends, customer insights, and sales performance.

Interactive Tableau business intelligence dashboard built using the Adventure Works dataset to analyse sales performance, customer behaviour, product trends, and geographic insights through advanced visualisations, calculated fields, filters, dashboards, and interactive analytics.

End-to-end retail sales data analysis using Python, pandas, and matplotlib. This project explores customer purchasing behavior, regional performance, product trends, and sales insights through data cleaning, exploratory analysis, and visualizations.