Customer targeting

Churn scoring

Know which customers are ready to churn while there's still time to save them — using Google Cloud SQL (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 Google Cloud SQL (SQL Server) and you're concerned about customer churn, integrating Faraday's churn scoring predictions could be a highly practical move. Simply put, knowing which customers are most likely to leave your service allows you to take timely, preventative actions. Faraday's AI can generate these valuable predictions, and by embedding them directly into your Google Cloud SQL database, you streamline the process. This means fewer data transfers and a smoother workflow—allowing your team to focus on developing effective retention strategies based on reliable insights. It’s a straightforward way to make your customer retention efforts more data-driven and efficient.

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