About ChickInsights

Open Shiny App Read the User Guide

ChickInsights is an interactive Shiny application for exploring fintech customer behaviour, preparing messy customer datasets, segmenting users with clustering, and comparing predictive models for customer value. It brings data cleaning, exploratory analysis, clustering, and model experimentation into one workflow so business users can move from raw customer data to interpretable insights without switching tools.

The business problem it solves is customer prioritisation. Fintech teams often need to understand which customers are highly engaged, which segments may need intervention, and which behaviours are associated with long-term value. ChickInsights turns those questions into practical analysis by letting users inspect data quality, discover customer patterns, build customer segments, and evaluate models that support targeting, retention, and product strategy decisions.

What it does

• Data Overview — upload or select a dataset and preview its structure
• Data Cleaning — convert column types, handle missing values, export cleaned data
• Exploratory Data Analysis — univariate and bivariate visual exploration
• Clustering — feature selection, cluster selection, and cluster analysis to segment customers
• Model Experimentation & Comparison — build, evaluate, and compare predictive models (e.g. Linear Regression, randomForest, XGBoost)

See the full user guide for a walkthrough of every module.

More projects

ChickInsights is one of several applied data science and analytics projects on this portfolio, spanning R, Python, and SAS Viya. Visit the portfolio homepage to see the full list, or read more about the author.