Repeat purchase readiness

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.
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.
One-time purchasers Repeat purchasers 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.
Likelihood to buy again
Step 5
Define your repeat purchase scoring pipeline and deploy to BigQuery
Finally, deploy your prediction with the link below.
Repeat purchase scoring
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