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.

Imagine you're using Recharge for your subscriptions and you're trying to figure out the best way to offer promotions to your customers. Faraday's Adaptive discounting predictions can help you out. By figuring out exactly how significant of a promotion each customer is worth, you can make sure you're offering your most compelling discounts to those who will appreciate and respond to them the most. It takes the guesswork out of the equation, helping you make smarter, data-driven decisions. It’s just an easy way to make sure your promos are hitting the right people, at the right time.

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