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  • Machine Learning
  • Blockchain
  • Gen-AI
  • NLP

Comprehensive Customer Churn Analysis System with Blockchain Integration

An enterprise-grade analytics platform that predicts customer churn and secures customer insights on-chain.

Overview

Machine learning flags customers at risk of leaving, behavioural analytics explains the usage trends behind that risk, and generative AI reads review text for sentiment. Predictions and analytics are then committed to a blockchain so the record of what was predicted, and when, cannot be quietly revised.

Problem Statement

Churn models are usually judged after the fact, when the results have already been reinterpreted to fit the outcome. Businesses also treat reviews and usage logs as separate silos, so the reason behind a churn risk score stays invisible.

Proposed Solution

Combine numeric usage signals with sentiment mined from customer text, then anchor every prediction on-chain so model performance can be audited honestly over time.

Key Features

  • ML-Based Churn Prediction

    Early identification of high-risk customers.

  • Customer Behavior Analytics

    Trend analysis of customer behavior and usage patterns.

  • GenAI Sentiment Analysis

    Evaluates customer reviews and comments for sentiment insights.

  • Blockchain-Based Data Storage

    Secure, immutable storage of customer analytics and predictions.

Technologies Used

Machine Learning

  • Scikit-Learn
  • XGBoost
  • Pandas
  • Python

Gen-AI / NLP

  • LLM sentiment analysis
  • Transformers
  • Text preprocessing

Blockchain

  • Solidity
  • Smart contracts
  • Web3.js

Application

  • Flask
  • React
  • Chart.js

Project Workflow

  1. 1

    Data ingestion

    Customer usage, transaction and review data are collected.

  2. 2

    Behaviour analytics

    Usage trends and engagement patterns are computed.

  3. 3

    Sentiment scoring

    Generative AI scores review and comment sentiment.

  4. 4

    Churn prediction

    The ML model assigns each customer a churn risk level.

  5. 5

    On-chain commit

    Predictions and analytics are stored immutably for audit.

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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