How to predict and reduce customer churn

Practical session, 1 hour, with Tips and step-by-step steps to create efficient, low-cost and highly automated analytics projects.  

‍After this session, you will be able to:

➡️ Understand how to obtain the necessary data and automate flows

➡️ Accelerate data projects and democratize access throughout the company

➡️ Choose models to create value for the business, enrich, and segment customers

➡️ Make data available for Consumption: visualization to make decisions

Aimed at:

• Marketing and Sales Leaders, Product Owners
• Data and analysis leaders on both the business and technological sides
• BI teams (middle managers and individual collaborators), Data Engineers, Project Managers and software developers
• CIO, IT Managers, Infra, Platforms

Step 1: The problem of taking data from different sources to be used to make decisions

Step 2: Design and rapid deployment of data pipelines to organize them in the data lake

Step 3: Exploratory analysis of a real dataset (telco customers)

Step 4: Evaluation of predictive models for customer churn (churn) and what is the best

Step 5: Deploy the best predictive customer churn model in a cloud environment, automated

Step 6: Visualization of the predictive segmentation model