Personalization

Rep assignment

Assign each lead or customer to the rep that will handle them best — using AWS Aurora Postgres

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 relies on AWS Aurora Postgres, integrating Rep assignment predictions could make your job a whole lot smoother. By using this type of prediction, you can automatically assign leads and customers to the reps who are most likely to engage them effectively. This means your database not only stores your customer data but also becomes a smart tool for optimizing your team's efforts. It’s a practical step to streamline your operations, help your reps connect better with prospects, and ultimately enhance your customer relationships. It’s a handy feature that fits right into your Aurora setup without making things complicated.

Step 1
Connect your data sources
Use the link below to connect AWS Aurora Postgres to Faraday. You can also skip this step and use CSV files to get started instead.
AWS Aurora Postgres
Step 2
Ingest your data into event streams
This allows Faraday to understand what your data means. These links will guide you through ingesting the data necessary to power this template.
Transaction Signup
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.
Leads
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.
Rep assignment
Step 5
Define your rep assignment pipeline and deploy to AWS Aurora Postgres
Finally, deploy your prediction with the link below.
Rep assignment
Step 6
Deploy to AWS Aurora Postgres
Create a deployment target using the AWS Aurora Postgres connection you created above. Or, get started by simply deploying to CSV.
AWS Aurora Postgres