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 using Faraday for rep assignment predictions and you're also into Databricks Delta Sharing, you're in for a treat. Imagine seamlessly integrating Faraday's AI-driven insights with your existing data workflows in Databricks. It means you can easily share and collaborate on those insights with others in your organization without any fuss. Assigning leads or customers to the perfect rep becomes a breeze when your data moves smoothly across platforms. This setup can help you make informed decisions more quickly, ensuring your reps are matched with the leads they'll engage with most effectively. It's all about making your data work harmoniously to support your team.

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