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Customer targeting

Churn scoring

Know which customers are ready to churn while there's still time to save them — using Facebook Custom Audiences

You’ll need a Faraday account to use this template. It’s free to sign up and you can use sample data to start.

Facebook Custom Audiences logoIf you're using Facebook Custom Audiences and also a Faraday user, integrating churn scoring predictions could be a game-changer for your marketing efforts. Imagine being able to identify which of your customers are most likely to churn and then targeting them specifically with tailored ads through Facebook. This means you can address their concerns or re-engage them with incentives before they decide to leave. It's a proactive way to maintain your customer base and make your ad spend more efficient. Plus, it's all grounded in solid, data-driven insights. It’s a smart step to better understand and retain your customers without overcomplicating things.
  1. Step 1

    Connect your data sources

    Use the link below to connect Facebook Custom Audiences 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. These links 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 churn scoring pipeline and deploy to Facebook Custom Audiences

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

    Deploy to Facebook Custom Audiences

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