R Studio Projects

Customer Segmentation Analysis in R

This project demonstrates how to segment customers using K-means clustering in R. The analysis includes data preprocessing, scaling, clustering, and visualization using tidyverse and ggplot2. The RStudio script organizes the workflow to generate actionable insights for targeted marketing strategies.

Sales Forecasting with Time Series Analysis in R

Data Preprocessing: The script loads and formats the sales data, ensuring the date column is recognized as a date type.

Time Series Creation: The sales data is converted into a time series with monthly frequency.

ARIMA Modeling: An ARIMA model is fitted automatically to capture the underlying patterns in the time series.

Forecast and Visualization: The script forecasts sales for the next 12 months and saves a plot of the forecast.

This project showcases time series forecasting techniques in R and provides insights that can help in inventory management and strategic planning.

Customer Review Sentiment Analysis in R

A data analytics project that processes customer reviews using natural language processing (NLP) to determine sentiment patterns. The R script analyzes text data to classify reviews as positive, negative, or neutral, creates visualizations including word clouds and sentiment trends over time, and generates actionable insights for improving customer satisfaction. Using libraries like tidytext and syuzhet, this analysis helps businesses understand customer feedback at scale and track sentiment trends.