a-memme/Customer_Churn_and_CLTV

BG/NBD and Gamma Gamma probabilistic models to evaluate and predict customer churn, retention, and lifetime value of an e-commerce business

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VibolvatanakPOCH/Telecom-Customer-Churn-Analysis-Prediction

Telecom Customer Churn Analysis & Prediction project uses Gradient Boosting for precise predictions, Power BI for churn pattern visualizations, and Streamlit for interactive insights. With robust code and meticulous data preprocessing, stakeholders access accurate predictions to optimize retention and drive profitability.

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kevin-titi/Game_Analytics_D14_Retention_Prediction

A predictive model for player retention/churn on day-14 after game installation based on features such as in-game metrics, user behavior, and engagement patterns to identify players at risk of churning, accurately predicting 65% of all retention within the top 6% of total population.

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hakanco/Bank_Customer_Churn_Model

The Bank Customer Churn Model is a predictive analytics solution using a high-accuracy Random Forest model to identify high-risk customers, enabling banks to proactively retain valuable customers, minimize revenue loss, and inform targeted retention initiatives through user-friendly streamlit web application. User can access churn risk probability.

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fadhlurrahmann/cohort-analysis-online-retail

cohort retention analysis using MySQL for online retail dataset

Size: 15.7 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0

slaing77/Player-Retention-Analysis

Investigating player retention using SQL and BigQuery

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Samuel1-ona/Weaver_Contract Fork of weaver-points/Weaver_Contract

Solving the user retention problem on starknet for starknet protocols

Language: Cairo - Size: 166 KB - Last synced at: 10 days ago - Pushed at: 10 days ago - Stars: 0 - Forks: 0

zhull1988/Telecom-Customer-Churn-Analysis

Exploratory data analysis of telecom customer churn using Python. Includes data cleaning, visualization, and statistical tests to understand churn behavior.

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claire-1125/Foodie_Express_Analysis

사이드 프로젝트로 진행한 음식 배달 앱 로그 데이터 분석 프로젝트입니다.

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MasterMindRomii/Customer-Churn-Prediction-Final-Year-Project

Built an ML model to predict customer churn, enhancing retention strategies.

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PhanChenh/CohortAnalysis_Adventurework_SQLProject

Customer Retention and Lifetime Value Analysis Using Cohort Analysis on AdventureWorks Dataset (2011-2014)

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AnshRockstar/MBA_SEM3_project-SSODL

THE INFLUENCE OF LOYALTY PROGRAMS BACKED BY CRM ANALYTICS ON CLIENT RETENTION

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jmson8/HYU_Data_Mining

OTT Service Customer Churn Prediction

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zargiteddy/AB-Testing

Statistical Analysis of Player Retention: An A/B Testing Study on Engagement Strategies for New and Experienced Players using the Cookie Cats Dataset

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elian-stz/AromaProfilR

AromaProfilR is used to reprocess GC-MS data for aromatic profiles and identify aromatic compounds

Language: R - Size: 3.17 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0

sinanw/ann-bank-customer-retention

This is a simple project that aims to create a basic Artificial Neural Network to predict if bank customers are going to maintain/close their accounts.

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ahmedlrashed/customer-retention-dax-report

Extract data from Excel report to convert to a Power BI data model using industry best practices to create a demo replacement customer retention report.

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tnation1392/Legislator-Cohort-Analysis

This is working with SQL queries from the book SQL FOR DATA ANALYSIS by Cathy Tanimura

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maxleungtszchun/customerAnalytics

Customer Analytics in R

Language: R - Size: 5.42 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

anastasiiastepanyan/data_analytics_projects

PORTFOLIO

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anudeepvanjavakam1/Mobile-Games--Cookie-Cats--A_B-Testing-with-bootstrap-analysis

Cookie Cats is a hugely popular mobile puzzle game developed by Tactile Entertainment. In this project, we will look at the impact of a in-game feature change on player retention.

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TayfunBasoglu/Customer-Retention-Rate

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Vaishnokmr/RFM-MODEL

RFM is a customer segmentation model that identifies high-value customers based on their behavior. Machine learning can be used to analyze large datasets and develop predictive models to identify customers likely to become high-value. This enables businesses to target these customers with personalized marketing strategies for increased revenue.

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merrillm1/Ultimate_Challenge

Predicted rider retention for a taxi service and identified most significant factors that contributed to it. Achieved an 80% accuracy with a catboost model, which was chosen for its interpretability.

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TrilokiDA/Employee-Retention

Figuring Out Which Employees May Quit

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