Personalization

Thematic personalization

Shape your creative and message to appeal to each target — using AWS Aurora 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.

If you're a Faraday user and also work with AWS Aurora Postgres, using Thematic Personalization predictions can be a smart move to fine-tune how you connect with your customers. Think of it as a way to shape your creative content and messages so they resonate better with each specific target audience. By integrating these predictions directly into your Aurora Postgres database, you can seamlessly align your data-driven insights with your marketing efforts. This can help you deliver more relevant and engaging experiences, making your outreach feel more personalized and thoughtful without adding extra complexity to your workflow.

Step 1
Connect your data sources
Use the link below to connect AWS Aurora Postgres to Faraday. You can also skip this step and use CSV files to get started instead.
AWS Aurora Postgres
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.
Transaction
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.
Customers
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.
Customer personas
Step 5
Define your content personalization pipeline and deploy to AWS Aurora Postgres
Finally, deploy your prediction with the link below.
Content personalization
Step 6
Deploy to AWS Aurora Postgres
Create a deployment target using the AWS Aurora Postgres connection you created above. Or, get started by simply deploying to CSV.
AWS Aurora Postgres