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Customer targeting
Churn scoring
Know which customers are ready to churn while there's still time to save them — using SFTP
You’ll need a Faraday account to use this template. It’s free to sign up and you can use sample data to start.
For Faraday users who also utilize SFTP, having churn scoring predictions available through this secure file transfer protocol can be quite handy. Imagine easily accessing valuable insights on which customers might be ready to leave, all in a format and system you're already comfortable with. It can make your workflow smoother by integrating directly into your existing processes, allowing you to take timely actions to retain those at-risk customers. Plus, the security of SFTP ensures that your sensitive data remains protected throughout the entire process. This can be a practical addition to your toolkit, helping you understand and address potential churn without needing to change how you already do things.
- Step 1
Connect your data sources
Use the link below to connect SFTP to Faraday. You can also skip this step and use CSV files to get started instead. - 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. - 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. - 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. - Step 5
Define your churn scoring pipeline and deploy to SFTP
Finally, deploy your prediction with the link below. - Step 6
Deploy to SFTP
Create a deployment target using the SFTP connection you created above. Or, get started by simply deploying to CSV.
Deploy your churn scoring predictions to . . .
Aurora (MySQL)
AWS Aurora Postgres
Azure SQL
BigQuery
Facebook Custom Audiences
GCS
Google Ads
Google Cloud SQL (MySQL)
Google Cloud SQL (Postgres)
Google Cloud SQL (SQL Server)
HubSpot
Iterable
Klaviyo
LinkedIn Ads
MySQL
Pinterest Ads
Poplar
Postgres
RDS (MySQL)
RDS (Postgres)
RDS (SQL Server)
Recharge
Redshift
Redshift Serverless
S3
Salesforce
Salesforce Marketing Cloud
Segment
SFTP
Shopify
Snowflake
SQL Server
Stripe
The Trade Desk
TikTok
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