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Personalization
Thematic personalization
Shape your creative and message to appeal to each target — using MySQL
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 navigating the world of customer behavior and you're a MySQL user, Thematic personalization predictions from Faraday can be a real game-changer without any fuss. Imagine you're trying to fine-tune your messaging to connect better with different customer segments—Faraday's insights can help you tailor your content just right. Integrating these predictions into MySQL is pretty straightforward, so you can easily query the data and craft messages and creatives that resonate with your audience. It’s a handy way to use your existing tools to make your marketing more effective, all without adding extra complexity to your workflow.
- Step 1
Connect your data sources
Use the link below to connect MySQL 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 MySQL
Finally, deploy your prediction with the link below. - Step 6
Deploy to MySQL
Create a deployment target using the MySQL 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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