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Personalization
Thematic personalization
Shape your creative and message to appeal to each target — using Google Cloud SQL (Postgres)
You’ll need a Faraday account to use this template. It’s free to sign up and you can use sample data to start.
Many Faraday users also rely on Google Cloud SQL (Postgres) for their data management, and integrating Thematic personalization predictions into this environment can be incredibly helpful. By storing your predictions in Postgres, you can easily join them with your existing customer data, making it simpler to shape your creative and messaging to appeal to each target audience. This seamless integration can help streamline your workflows, keeping everything in one place and easy to access. Plus, leveraging the power of AI to fine-tune your marketing efforts can lead to more meaningful customer interactions, all while utilizing a familiar and robust database system like Postgres.
- Step 1
Connect your data sources
Use the link below to connect Google Cloud SQL (Postgres) 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 Google Cloud SQL (Postgres)
Finally, deploy your prediction with the link below. - Step 6
Deploy to Google Cloud SQL (Postgres)
Create a deployment target using the Google Cloud SQL (Postgres) 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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