Rep assignment - Faraday

You will need a Faraday account to use this template. It is free to sign up and you will just need some sample data to start.

Get started for free

If you're a Faraday user working with customer engagement data, you might be interested in leveraging Rep assignment predictions through Databricks Delta Sharing to streamline how your team connects with leads. By assigning each lead to the rep that's best suited to engage them, you can see improvements in relationship building and sales outcomes. Using Delta Sharing, you can seamlessly integrate these predictions into your existing data workflows, allowing for efficient data access and collaboration across teams. It offers a way to make your data-driven insights more actionable while simplifying the logistics of sharing predictions within your organization.

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