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Personalization

Thematic personalization

Shape your creative and message to appeal to each target — using ClickHouse

Thematic personalization

You will need a Faraday account to use this template. It is free to sign up and you will just need some sample data to start.

ClickHouse logoIf you're using Faraday to tap into thematic personalization, integrating your data with ClickHouse could be a nice move. ClickHouse can handle large datasets efficiently, making it a great companion for analyzing customer behaviors and preferences. By using thematic personalization predictions in ClickHouse, you can quickly uncover insights into which messages and creative elements resonate with different customer segments. This could streamline your efforts in crafting personalized campaigns, allowing for data-driven decisions that suit your audience's taste without overcomplicating the process. It's a gentle way to enhance your marketing strategies with the power of both predictive analytics and fast data processing.
  1. Step 1

    Connect your data sources

    Use the link below to connect ClickHouse 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 ClickHouse

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

    Deploy to ClickHouse

    Create a deployment target using the ClickHouse connection you created above. Or, get started by simply deploying to CSV.