Adaptive discounting

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 Snowflake, you'll appreciate how smoothly Adaptive discounting predictions can integrate into your data workflow. Imagine being able to directly tap into the power of Snowflake’s cloud data platform to understand which of your customers should receive your best promotions. By leveraging Faraday's adaptive discounting in Snowflake, you can make data-driven decisions about promotion targeting right from your single source of truth. This integration means less time spent on data wrangling and more time focusing on offering the right deals to the right customers. It's a straightforward way to enhance your promotional strategies with minimal fuss.

Step 1
Connect your data sources
Use the link below to connect Snowflake to Faraday. You can also skip this step and use CSV files to get started instead.
Snowflake
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.
Forecasted spend
Step 5
Define your adaptive discounting pipeline and deploy to Snowflake
Finally, deploy your prediction with the link below.
Adaptive discounting
Step 6
Deploy to Snowflake
Create a deployment target using the Snowflake connection you created above. Or, get started by simply deploying to CSV.
Snowflake