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Personalization

Adaptive discounting

Offer your best promos to the customers who most deserve it — using 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.

Postgres logoSure thing. If you're a Faraday user who's also comfortable with Postgres, integrating Adaptive discounting predictions directly into your database can be a smooth move. It allows you to leverage your existing database skills while making smarter promotional decisions based on AI insights. Instead of taking a one-size-fits-all approach, you'll be able to identify which customers are truly worth giving that extra discount to, all from within Postgres. This means you can keep your workflow streamlined, data in one place, and easily run queries to fine-tune your promotional strategies. It's about working smarter, not harder, and making your promotional efforts more effective without complicating your process.
  1. Step 1

    Connect your data sources

    Use the link below to connect 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 adaptive discounting pipeline and deploy to Postgres

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

    Deploy to Postgres

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