Mirza Asad

Academic

Career

Verbatim text

Customer Attrition Analytics 
 
 This project aims for predicting customer attrition in an effort to retain them. We worked on data 
 which included customers that have already churned (response) and their characteristics / 
 behaviour (predictors) before the customer turnover happened. By fitting a machine learning 
 model that relates the predictors to the response, we predicted the response for existing 
 customers. With the help of this project, an organization can analyse all relevant customer data and 
 develop focused customer retention programs for a good business. 
 Features Include: 
  Predicting whether customer will Churn or Not 
  Feature Importance Report: Calculating the factors affecting customer attrition and their 
 contribution  
  Extracting and Visualizing key information 
  Interactive Data Visualization to provide the user the freedom to perform the analysis on the data 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Technology Used: 
 Python, DASH, Plotly  
 Scikit-Learn, Bootstrap 
 Supervisor Name: 
 Dr. Hasan Mujtaba 
 Group Members:   
 Ayela Furrokh (i16 - 0030) 
 Usman Attiq (i16 - 0073) 
 Mirza Asad (i16 - 0136)