Customer Personality Analysis Using Clustering

Developing a targeted marketing strategy through exploratory analysis, customer profiling, and segmentation. Focuses on data wrangling, merging, grouping, and deriving variables to uncover actionable insights for personalized marketing efforts.

BigData system to capture user actions on buttons and links, as well as their time spent on a website, to subsequently perform unsupervised clustering and analysis of keywords via generative AI and webscraping. Javascript application that connects to MongoDB, using a node.js server, and passes the captured data to a Python backend.

Business Case: Aerofit - Descriptive Statistics & Probability

Analyze the data of Visa applicants, build a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommend a suitable profile for the applicants for whom the visa should be certified or denied.

Customer segmentation is a pivotal task for business analytics. Customer segmentation is the process of splitting customers into different groups with similar characteristics for potential business value proposition. Many companies find that segmenting their customers enable them to communicate, engage with their customers more effectively. Futu…

Data Analysis Project using Python(Numpy, Pandas, Seaborn, matplotlib)

This project optimizes profitability by analyzing acquisition channels, product margins, and regional performance. Using RFM customer segmentation, we identify high-value behaviors to drive targeted retention. Our goal is to reallocate marketing spend toward high-performing sources and prioritize inventory for the most profitable products.

Applied SAS techniques for data analysis and machine learning in a milestone project. Base SAS Programming and SAS Viya tools were utilized for preprocessing, customer profiling, sales analysis, promotions, supplier evaluation, and customer segmentation. Results were visualized comprehensively.

A Fitness Company wants to know the customer behavior towards the threadmill and want recommendations to increase its profits.

Business Case : Aerofit - Descriptive Stats & Probability

Aerofit Business Case Study - Exploratory Data Analysis to derive insights, trends and patterns.

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

Customer Personality Analysis Using Clustering

Ensemble Techniques: Analyze the data of Visa applicants, build a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommend a suitable profile for the applicants for whom the visa should be certified or denied.

This project conducts customer credit risk assessment by preprocessing the data, applying various models, and evaluating their performance with and without SMOTE (Synthetic Minority Over-sampling Technique) to address class imbalance.

Conducted Descriptive Statistics & Probability to extract insights

Identifying customer segmentation from history data of Everything Plus, an online household store using KMeans Algorithm (submitted as final project for course in Practicum Indonesia)

Analyzes user behavior and demographic data to create distinct user segments for targeted advertising and personalized experiences.

This project analyzes AeroFit’s treadmill customer dataset to uncover patterns in demographics, fitness behaviour and income & to profile customers for each treadmill model (KP281, KP481, KP781). The analysis includes descriptive statistics, probability calculations and visualizations to provide insights for targeted marketing & product suggestions