There are 2 repositories under market-segmentation topic.
Find community/segment in an attributed graph of Facebook data.
Unsupervised learning for market segmentation
Electric Vehicle Market Segmentation Analysis in India
Identify commercial centers using Points of Interest (POI) data by clustering these points into commercial centers/markets
Uncover hidden relationships and patterns with k-means clustering, hierarchical clustering, and PCA
A customer segmentation project.
This repository contains the market cluster analysis performed on the Philippine's demographic data using JMP by SAS.
Implementation of a d3.js Visual Analytics dashboard for Sales Analysis and Customer Segmentation in Retail
Notebook to Perform Market Segmentation using K-means clustering, PCA, and Auto-encoders.
Market Segmentation Case Study Analysis using Clustering
Bayesian Market Segmentation Algorithm for Hedonic Analysis
The food aggregator company has stored the data of the different orders made by the registered customers in their online portal. Identify areas of growth and improvement for a better customer experience.
Customers RFM Clustering (Market Segmentation based on Behavioral Approach)
Clustering the Mall customers to analyze the different market segments of the Mall
A web server that switches the functionality of an automated time factored publishing of news and prices to Campaign Treasurer Web App based on a preset updates.
In this project, the objective is to segment a portfolio of credit card users according to usage characteristics. Customer segmentation is then used by marketing department to tailor products and services specific to these customer segments.
Customers RFM Clustering (Market Segmentation based on Behavioral Approach)
- Using data crawler, data virtualization, public opinion detection, etc to make NEPV & Tesla business report
The beverage choice that accompanies most American pastime is divided between 🍺 Beer and 🥤 Soda. A market segmentation is performed to study this division - brands, demographic, profit - with the goal of target marketing.
January 2024 - March 2024
I help an espresso machine manufacturer assess the product attribute preferences coffee drinkers have while purchasing espresso machines using conjoint analysis in Microsoft Excel
I use R to identify and visualize target audience clusters for Acme Shopping Mall based on data collected about their shopping habits and preferences, and provide insightful business recommendations to tailor to the different needs of different consumer groups
An comprehensive data analysis of a particular market and its customers.
A market segmentation project with python
Analyzing US crime statistics using hierarchical clustering to uncover patterns in state-level arrest data and Advanced analytics to delineate market segments in retail, optimizing targeted marketing strategies through customer behavior and demographic profiling.
This repository contains an analysis of customer behavior for Tuscan Lifestyles using RFM (Recency, Frequency, Monetary) analysis. The project aims to segment customers based on their historical purchasing behavior and predict their future response rates to marketing efforts
Advanced analytics in R to delineate market segments in retail, optimizing targeted marketing strategies through customer behavior and demographic profiling
This project was developed during a 3-month internship program at Feynn Labs. The project replicates a McDonald's case study using Python. It involves data analysis, PCA for dimensionality reduction, KMeans clustering, segment profiling, and decision tree classification for marketing segmentation,
General Material Compactor: Product Development Course Project
Market Segmentation Analysis on Agri-tech startup for BioPesticides
Exercises from STA 380, a course on predictive modeling in the MS program in Business Analytics at UT-Austin Summer 2019
Independent Project - Kaggle Dataset-- I worked with the Mall Customer Segmentation Dataset, which provided a various instances of shoppers of different ages, incomes, etc. I utilized unsupervised ML clustering algorithms to identify useful customer segments.
Train unsupervised machine learning algorithms to perform customer market segmentation. Market segmentation is crucial for marketers since it enables them to launch targeted ad marketing campaigns that are tailored to customer's specific needs.