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Customer targeting
Repeat purchase readiness
Know which customers are ready to buy again — using S3
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 already using S3 for your customer data, integrating Faraday's Repeat Purchase Readiness predictions could be a great next step. Imagine having a smart way to know which customers are most likely to buy again, right at your fingertips. By having these predictions in S3, you can seamlessly blend them into your existing workflows and analytics tools without any extra hassle. It's a straightforward way to get more value out of your customer data and make more informed decisions. We're here to make it a little easier for you to understand your customers and meet their needs.
- Step 1
Connect your data sources
Use the link below to connect S3 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 S3
Finally, deploy your prediction with the link below. - Step 6
Deploy to S3
Create a deployment target using the S3 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.