Personalization

Adaptive discounting

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

Imagine you’re working with AWS Aurora Postgres and trying to figure out the best way to offer promotions to your customers. Adaptive discounting predictions from Faraday can make this a lot easier. It helps you determine how significant a promotion each customer is worth, so you’re not just throwing out discounts willy-nilly. With these insights, stored right in your Aurora Postgres database, you can make more informed decisions and give the best promos to the customers who deserve them the most. It’s straightforward and integrates smoothly into your existing workflow, making your promotional efforts more effective and intelligent.

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