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Customer targeting
Churn scoring
Know which customers are ready to churn while there's still time to save them — using Segment
You’ll need a Faraday account to use this template. It’s free to sign up and you can use sample data to start.
Are you a Segment user curious about making the most out of your customer data? With Faraday's churn scoring predictions integrated into Segment, you can easily identify which of your customers are most likely to leave. This foresight lets you take proactive steps to keep them engaged and happy. Whether you're designing targeted campaigns or personalizing customer experiences, having this insight directly within Segment makes it super convenient to act quickly. It's all about giving you the tools to build stronger relationships with your customers while keeping the process smooth and straightforward.
- Step 1
Connect your data sources
Use the link below to connect Segment 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 Segment
Finally, deploy your prediction with the link below. - Step 6
Deploy to Segment
Create a deployment target using the Segment 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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