Customer Personality Analysis Using Clustering

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

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.

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…

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.

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.

Business Case : Aerofit - Descriptive Stats & Probability

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

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

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)

Customer Personality Analysis Using Clustering

Business Case: Aerofit - Descriptive Statistics & Probability

EDA and an Ensemble model comprised of XGBoost, CatBoost, LightGBM, and other algorithms to predict whether existing customers will respond positively to new insurance offers based on demographic data. Submission as part of Kaggle competition.

Analyze the data of ABC consulting company, build a predictive model based on the parameters like age, salary, work experience and predict the preferred mode of transport.

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

Conducted Descriptive Statistics & Probability to extract insights

Analyzed customer characteristics using user counts, probabilities, and conditional probabilities to profile target audiences for AeroFit's treadmill portfolio. Delivered actionable insights to recommend the most suitable treadmill model—entry-level, mid-level, or advanced—to new customers, enhancing product alignment with user needs.