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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. - 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. - 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. - 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. - Step 5
Define your adaptive discounting pipeline and deploy to BigQuery
Finally, deploy your prediction with the link below. - Step 6
Deploy to BigQuery
Create a deployment target using the BigQuery connection you created above. Or, get started by simply deploying to CSV.
Deploy your adaptive discounting predictions to . . .
Aurora (MySQL)
AWS Aurora Postgres
Azure SQL
BigQuery
Facebook Custom Audiences
GCS
Google Ads
Google Cloud SQL (MySQL)
Google Cloud SQL (Postgres)
Google Cloud SQL (SQL Server)
HubSpot
Iterable
Klaviyo
LinkedIn Ads
MySQL
Pinterest Ads
Poplar
Postgres
RDS (MySQL)
RDS (Postgres)
RDS (SQL Server)
Recharge
Redshift
Redshift Serverless
S3
Salesforce
Salesforce Marketing Cloud
Segment
SFTP
Shopify
Snowflake
SQL Server
Stripe
The Trade Desk
TikTok
Ready for easy AI?
Skip the ML struggle and focus on your downstream application. We have built-in sample data so you can get started without sharing yours.