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Customer targeting
Repeat purchase readiness
Know which customers are ready to buy again — 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 a Faraday user who also works with BigQuery, having Repeat purchase readiness predictions right in BigQuery can make your job a whole lot easier. Imagine being able to seamlessly integrate AI-driven insights about which of your customers are ready to buy again directly into the data warehouse you already use and love. This means you can quickly analyze and act on these predictions without jumping between platforms, streamlining your workflow. It's a straightforward way to harness the power of Faraday's customer behavior predictions while keeping everything neatly in one place.
- 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 repeat purchase scoring 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 repeat purchase readiness 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.