Customer targeting

Churn scoring

Know which customers are ready to churn while there's still time to save them — using RDS (SQL Server)

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 using RDS (SQL Server) to manage your customer data, integrating Faraday's churn scoring predictions could be a smart move. It can help you easily identify which of your customers are most at risk of leaving, all within the familiar environment of your SQL Server. This means you can take proactive measures to improve customer retention without having to overhaul your current workflow. It’s a straightforward way to get more value out of your existing data and prevent churn, ensuring that your efforts to keep customers happy are timely and effective.

Step 1
Connect your data sources
Use the link below to connect RDS (SQL Server) to Faraday. You can also skip this step and use CSV files to get started instead.
RDS (SQL Server)
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 RDS (SQL Server)
Finally, deploy your prediction with the link below.
Churn scoring
Step 6
Deploy to RDS (SQL Server)
Create a deployment target using the RDS (SQL Server) connection you created above. Or, get started by simply deploying to CSV.
RDS (SQL Server)