Customer Personality Analysis Using Clustering

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…

Business Case: Aerofit - Descriptive Statistics & Probability

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.

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.

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.

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.

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.

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

Business Case : Aerofit - Descriptive Stats & Probability

Customer Personality Analysis Using Clustering

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

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.

Conducted Descriptive Statistics & Probability to extract insights

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

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.

📊 Optimize e-commerce profitability through targeted market analysis and strategic marketing spend allocation for maximum returns.