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Personalization
Thematic personalization
Shape your creative and message to appeal to each target — using Redshift Serverless
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 already using Redshift Serverless, integrating Thematic personalization predictions from Faraday could be a great way to enhance your campaigns without adding extra complexity. These predictions can help you tailor your messages and creative content to resonate more effectively with different segments of your audience. By having these insights directly within Redshift Serverless, you can streamline your workflow, making it easier to analyze and act on the data you have. This could help you create more personalized experiences for your customers, potentially improving engagement and satisfaction. It's a simple way to make your data work a bit harder for you.
- Step 1
Connect your data sources
Use the link below to connect Redshift Serverless 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. This link 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 content personalization pipeline and deploy to Redshift Serverless
Finally, deploy your prediction with the link below. - Step 6
Deploy to Redshift Serverless
Create a deployment target using the Redshift Serverless connection you created above. Or, get started by simply deploying to CSV.
Deploy your thematic personalization 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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