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 using Faraday and also have Redshift in your tech stack, integrating Adaptive discounting predictions could be a smart move for you. With Adaptive discounting, you can tailor your promotions to offer the right deals to the right customers, figuring out who deserves the best discounts. Seamlessly pulling this data into Redshift means you can leverage your existing infrastructure for faster queries and more efficient data handling. This way, you keep all your insights in one place, making it simpler to track, analyze, and act on them. No need to juggle multiple platforms; everything flows easily into your current setup, saving you time and effort.

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