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Machine LearningCase Study·81% Match

Customer Segmentation & Sales Analysis

Interactive R Shiny application (app.R) for statistical learning and business intelligence. Applies unsupervised ML for customer segmentation, visualises sales trends, and drives product recommendations. Persistent data in SQLite3; rsconnect directory enables deployment to shinyapps.io. Live demo at vaibhavbansal.shinyapps.io/sdmproject.

RShinyRSQLite3Machine Learning
LiveR ShinyFrameworkSQLite3Databaseshinyapps.ioDeployedUnsupervised MLAlgorithm
R Shiny
Framework
SQLite3
Database
shinyapps.io
Deployed
Unsupervised ML
Algorithm
🔴 The Problem
▸

Businesses lacked an interactive tool to explore customer segments without writing queries

▸

Static reports couldn't reflect real-time filter changes

✅ The Solution
▸

R Shiny app with reactive inputs drives live clustering and trend charts

▸

SQLite3 persists data; rsconnect deploys to shinyapps.io in one command

📈 Impact & Results
▸

Live at vaibhavbansal.shinyapps.io/sdmproject

▸

K-Means clustering surfaces customer segments interactively

▸

Sales trend and product recommendation modules included in same dashboard

Full Tech Stack
RShinyRSQLite3Machine Learning

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