OroCRM - an open-source Customer Relationship Management application.

An implementation of the shifted-beta-geometric (sBG) model from Fader and Hardie's "How to Project Customer Retention" (2006)

Data Science & Machine Learning Internship at Flip Robo Technologies

Comprehensive Power BI dashboards showcasing insights on Call Centre Trends, Customer Retention, and Diversity & Inclusion to drive business impact.

Retainful Website

Abandoned Cart Recovery Email and Next Order Coupon Plugin for WooCommerce. Easily recover abandoned carts with a single click and drive repeat purchases with Retainful

Loyalty Bridge is a web-based loyalty management system that enables businesses to track and incentivize customer loyalty.

This demo repository demonstrates how to analyze customer reviews with Azure OpenAI Service (AOAI). I leveraged "ASOS Customer Review" from Kaggle to obtain valuable insight from the customer review content.

Predicts which telecom customers are likely to churn with 95% accuracy using real-world data features from usage, billing, and support data. Implements Sturges-based binning, one-hot encoding, stratified 80/20 train-test split, and a two-level ensemble pipeline with soft voting. Achieves 94.60% accuracy, 0.8968 AUC, 0.8675 precision, 0.7423 recall.

The Bank Churn Classification project predicts customer churn in the banking sector using machine learning algorithms and EDA. It features a user-friendly interface built with HTML and CSS, with model deployment via Flask. This helps banks identify churn patterns and implement strategies to retain customers.

Assessed brand loyalty patterns and price elasticity metrics to provide insights for brand’s market growth. Recommended strategies for the top 3 brands based on competitor analysis, customer profiling and customer retention through RFM analysis and multinomial logit.

Creation of a MultiLayer Perceptron using Back Propagation Algorithm. It was trained to efficiently classify the data into two sets:exit and stay. This was able to predict whether a customer might stay with the bank or leave it in future.

This project predicts Customer Lifetime Value (CLV) for e-commerce. It aims at forecasting the revenue a business can expect from a customer over time. I did an explatory analysis. From Linear Regression to Neural Networks, explore how different models perform in predicting CLV.

Customer Churn Prediction System using XGBoost Regressor, built on Telecom Industry dataset

This data analysis and customer retention report was created for the PricewaterhouseCooper (PwC) Job Simulation program.

PwC Switzerland Power BI in Data Analytics Virtual Case Experience helps build foundation in data analysis and visualization with Power Bi

key performance indicators (KPIs) for the sales of Egypt Telecom. KPIs are metrics used to evaluate the success of sales activities and business performance. In this visual format, the data is likely presented in charts, graphs, or tables to provide a clear overview of how the telecom company is performing in various aspects of its sales operations

Customer churn analysis project using Excel and Power BI. This project investigates the exit patterns of banking customers using various demographics and behavior indicators such as age, gender, credit card status, geography, and credit score. Insights help identify key drivers of churn and guide retention strategies.

Contains Multipage Streamlit applications showing all steps of machine learning pipeline with additional recommendations at the end.

Using cohort analysis to measure customer retention.