Customer targeting

Churn scoring

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

Sure, here’s a straightforward and friendly take for you: If you’re already using SQL Server and you're curious about which of your customers might be on the verge of leaving, Faraday’s churn scoring predictions could be a valuable addition. By integrating these predictions directly into your SQL Server, you can seamlessly analyze and act on churn risk right where your data lives. This helps you make timely interventions to retain at-risk customers without needing to juggle multiple tools or platforms. It's a handy way to enhance your existing setup with insights that could make a real difference.

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