Antonio’s Portfolio & Blog

Welcome to my personal repository of data science notebooks.

Here, you will find a collection of studies and analyses in which I make use of data visualization, statistical analysis, data mining, and machine learning to extract important insights from data and solve common case studies on various topics such as business management & marketing, social sciences, sports, and more.

👥 Data-driven Customer Segmentation

RFMT Clustering to Decode Customer Behaviors and Define Business Personas

Online Retail

Clustering

Customer Segmentation

Business Personas

In-depth analysis of customer segmentation using the RFMT model (Recency, Frequency, Monetary Value, Tenure). Employing KMeans clustering, we identify distinct customer personas and propose tailored strategic actions for each group. The study aims to enhance customer engagement, retention, and value generation through precise, data-driven marketing strategies.

Antonio Buzzelli

🙏 Predicting loan approval

Classification model selection and prediction

Finance

Classification

Using a dataset containing demographic and financial attributes of loan applicants, I make use of a classification model to predict loan approval probability.

Antonio Buzzelli

🏍️ Modelling Riders Performance

Leveraging public race data to boost fans interest in motorsports

Motorsports

Performance Metrics

Delving in the world of MotoGP racing, I illustrate how making use of public race data can provide fans with a more structured and comprehensive understanding of the objective performance of race competitors.

Antonio Buzzelli

🛒 Using Market Basket Analysis to penetrate an untapped regional market

Customer-centric bundle deals with Apriori and association rules

Online Retail

Market Basket Analysis

Through the analysis of one year of sales data from an e-commerce website, I was able to identify for the firm a promising regional market with untapped potential, and implement a marketing strategy to target it using bundle deals tailored to the specific preferences of its consumers.

Antonio Buzzelli

🚢 Understanding Survival on the Titanic

Using machine learning to explain phenomena and define business personas

Classification

Business Personas

Businesses can utilize machine learning not only to make predictions but also to unveil valuable insights that are deeply embedded in their data. Using one of the most commonly used datasets in the study of data science – the Titanic dataset –, I demonstrate how supervised learning can serve as a data mining technique to achieve a deep understanding of phenomena and generate Personas.

Antonio Buzzelli