Customer Segmentation Project
Using fuzzy c-means and k-means to analyze customer personality data
The KPMG Data Analytics Virtual Internship is designed to help you gain a practical insight into the work we do at KPMG and it is an opportunity for you to build your career skills and experience.
Detailed analysis of a company’s ideal customers, helps a business to better understand its customers and makes it easier for them to modify products according to the specific needs, behaviors and concerns of different types of customers
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.
This repository contains a dashboard created using Tableau and you will find details about customer analysis method
Dataset Northwind Mini Project Data Engineering
KYC: know your customer. In this repository you will know the phases of B2C customer analysis and customer segmentation using k-means and RFM analysis
Used sales data from CSV file to create tables and which were later combined to form an interactive and comprehensive dashboard in Tableau
This repository showcases the outcomes of an Exploratory Data Analysis (EDA), including visualisation, conducted on the comprehensive Amazon Review Data (2018) dataset, consisting of nearly 233.1 million records and occupying approximately 128 gigabytes (GB) of data storage, using MongoDB and PySpark.
Customer analysis on a bike-share program
This repo is about analytics for optimizing your business's top customers and products.
SegmentWise: Unveiling Customer Insights for Exploratory Data Analysis (EDA) and Customer Segmentation
Leveraging K-Means clustering for insightful customer segmentation, enabling businesses to tailor products to specific customer types.
This project showcases how to perform Recency, Frequency, and Monetary (RFM) analysis using the powerful Polars DataFrame library in Python.
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.
Personal projects 1 & 2
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.
This repository contains a data science project aimed at analyzing customer behavior and classifying them based on their likelihood to accept marketing campaigns. Additionally, the project involves clustering customers into different segments for targeted marketing strategies.
Customer Analytics in R
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