Personalization

Adaptive discounting

Offer your best promos to the customers who most deserve it — using BigQuery

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 already using BigQuery, integrating Faraday's Adaptive Discounting predictions can really streamline your workflow. These predictions help you figure out how significant of a promotion each customer is worth, directly within the tool you're most comfortable with. By keeping everything in BigQuery, you save time and effort, avoiding the hassle of switching between platforms. It's a practical way to leverage AI-driven insights to make your promotional strategies more effective and efficient without disrupting your current data setup.

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