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  • Machine Learning

Business Analytics Platform

A web-based analytics platform that helps businesses analyze historical data and make informed decisions.

Overview

Upload a dataset and the platform predicts which customers are likely to disengage, forecasts future sales from historical trends, segments customers into marketing-ready clusters, and presents all of it on an interactive dashboard.

Problem Statement

Small businesses sit on years of transaction history and never model it, because the gap between a spreadsheet and a working ML pipeline is too wide for a non-technical owner to cross.

Proposed Solution

Wrap churn prediction, sales forecasting and customer segmentation behind a single upload-and-explore interface, so the analysis runs without the user writing any code.

Key Features

  • Customer Churn Analyzer

    ML model predicting customers likely to disengage.

  • Sales Forecasting

    Predictive ML algorithms estimating future sales from historical data.

  • Customer Segmentation

    Clustering techniques for personalized marketing.

  • Interactive Dashboard & Visualization

    Upload datasets, view predictions, and explore business insights.

Technologies Used

Machine Learning

  • Scikit-Learn
  • K-Means
  • Random Forest
  • Prophet

Data

  • Pandas
  • NumPy
  • CSV / Excel ingestion

Application

  • Flask
  • Plotly
  • Bootstrap
  • SQLite

Project Workflow

  1. 1

    Dataset upload

    Historical business data is uploaded and validated.

  2. 2

    Preprocessing

    Missing values and outliers are handled automatically.

  3. 3

    Modelling

    Churn, forecasting and clustering models are trained.

  4. 4

    Visualisation

    Predictions and segments are rendered on the dashboard.

What You'll Receive

  • Complete, runnable source code with folder structure
  • Project report and technical documentation
  • Ready-to-present PPT content
  • Setup and installation walkthrough
  • Line-by-line project explanation session
  • Viva question bank with answers
  • Bug fixing and troubleshooting help
  • Post-delivery support after submission

Frequently Asked Questions

How much does this project cost?

Every project is quoted individually, because the price depends on the modules you need, your technology stack, your college's format and your deadline. Send us the project name on WhatsApp and we'll share a quote the same day.

Can the project be customised to my college requirements?

Yes. Share your guide's requirements, preferred technology stack and abstract format, and we adapt the modules, dataset or UI accordingly.

Will I be able to explain this project during my viva?

That is the point of the explanation session. We walk you through the architecture, every module, the flow of data and the results, and hand over a viva question bank with answers.

What if the project does not run on my laptop?

We help you with setup end to end — dependencies, environment, database and configuration — over chat or a call until it runs on your machine.

Do I get support after submission?

Yes. Post-delivery support is included, so you can come back for fixes, doubts or demo help even after the project is delivered.

Want This Project?

Get complete source code, documentation, PPT, explanation, and support.

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