Advanced analytics in R to delineate market segments in retail, optimizing targeted marketing strategies through customer behavior and demographic profiling

Market Segmentation Analysis on Agri-tech startup for BioPesticides

To predict 6 months sales using 4 years time series data of a retail store.

An comprehensive data analysis of a particular market and its customers.

Exercises from STA 380, a course on predictive modeling in the MS program in Business Analytics at UT-Austin Summer 2019

The objective of this project is to develop a market segmentation system and the materials that explain it. I will utilize some of the variables from the Simmons National Consumer Study for this analysis.

General Material Compactor: Product Development Course Project

I help an espresso machine manufacturer assess the product attribute preferences coffee drinkers have while purchasing espresso machines using conjoint analysis in Microsoft Excel

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 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,

a sentiment analysis of outdoor brands' Facebook page comments

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.

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.

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

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.

- Using data crawler, data virtualization, public opinion detection, etc to make NEPV & Tesla business report