Customer targeting

Churn scoring

Know which customers are ready to churn while there's still time to save them — using MySQL

You’ll need a Faraday account to use this template. It’s free to sign up and you can use sample data to start.

If you're already comfortable with MySQL, incorporating Faraday's churn scoring predictions is a smooth way to enhance your data insights without switching tools. By bringing churn scoring directly into MySQL, you can quickly identify which customers are most at risk of leaving, all within the environment you're used to. This makes it easier to cross-reference with your existing customer data and take timely action to retain them. It's a practical solution that integrates seamlessly with your workflow, helping you make data-driven decisions to reduce customer attrition.

Step 1
Connect your data sources
Use the link below to connect MySQL to Faraday. You can also skip this step and use CSV files to get started instead.
MySQL
Step 2
Ingest your data into event streams
This allows Faraday to understand what your data means. These links will guide you through ingesting the data necessary to power this template.
Transaction Cancellation
Step 3
Organize your customer data
You'll create groups, called cohorts, that are the essential building blocks of Faraday and allow you to easily predict any customer behavior.
Customers Churned customers
Step 4
Declare your prediction objectives
With your cohorts defined, it's easy to instruct Faraday to predict the necessary behaviors. Follow the docs with the link below.
Likelihood to churn
Step 5
Define your churn scoring pipeline and deploy to MySQL
Finally, deploy your prediction with the link below.
Churn scoring
Step 6
Deploy to MySQL
Create a deployment target using the MySQL connection you created above. Or, get started by simply deploying to CSV.
MySQL