Adaptive discounting

You will need a Faraday account to use this template. It is free to sign up and you will just need some sample data to start.

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If you're a Faraday user who also uses Databricks Delta Sharing, you're in a great spot to make the most out of adaptive discounting predictions. With adaptive discounting, you can fine-tune how you offer promotions, ensuring you're rewarding your most deserving customers with the best deals. By integrating this with Databricks Delta Sharing, you can seamlessly share these insights across your organization in a secure and efficient manner. This means everyone in your team can access consistent, up-to-date predictions, helping you make more informed marketing decisions. It's a smart way to connect your customer insights with your existing data workflows, making collaboration a bit easier and more effective.

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