Analyze IBM Telco Customer data to offer valuable insights for data-driven decision-making on customer retention to reduce churn
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Updated
May 29, 2024 - R
Analyze IBM Telco Customer data to offer valuable insights for data-driven decision-making on customer retention to reduce churn
Developed a desktop application, that uses ML algorithms to accurately predict customer churn based on customer details. The application helps to identify customers at risk of churning using regression models.
Customer churn rate is an important metric for e-commerce businesses. Predicting whether someone will churn or not would be great...
This is a data mining project done mainly on SAS Miner.
Progetto Web Marketing and Communication Management
Code for a Shiny app calculatiing cost/revenue for churn prevention
The projects completed and in pipeline
In this case study we will predict that whether a particular customer of a telecom company will churn or not based on the demographic data and churn data.
Customer Churn Analysis using R & RStudio
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