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, you know how helpful it can be to understand your customers better, and that's exactly where Repeat purchase readiness predictions come in handy in Poplar. By integrating this type of prediction, you can efficiently identify which of your customers are most likely ready to make another purchase, allowing you to tailor your outreach and marketing efforts more effectively. This means you can spend less time guessing and more time engaging with those who are already inclined to buy again. It’s just a smarter, more efficient way to stay connected with your customers and meet their needs.

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