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 Snowflake, integrating Repeat Purchase Readiness predictions directly into your Snowflake environment could streamline your workflow in some pretty meaningful ways. By having these insights readily available in Snowflake, you can easily cross-reference them with your other data sources, making it simpler to identify which customers are primed to buy again. This seamless integration can help you create more targeted marketing campaigns without having to juggle multiple platforms. It’s all about making informed decisions more conveniently, so you can focus on meeting your customers where they are.

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