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.

Imagine having a clear sense of which customers are most likely to make another purchase soon. If you're using both Faraday and Iterable, integrating Repeat purchase readiness predictions could be a game-changer. These insights can help you tailor your marketing efforts more effectively within Iterable. Instead of sending the same promotions to everyone, you can focus on those most likely to respond, making your campaigns more efficient and personal. It’s a straightforward way to make your marketing smarter without much fuss, and who doesn't appreciate that?

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