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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.

AWS Aurora Postgres logoIf 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.
  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. Step 5

    Define your content personalization pipeline and deploy to AWS Aurora Postgres

    Finally, deploy your prediction with the link below.
  6. 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.