Rep assignment

Rep assignment predictions reveal which sales rep is most likely to convert an individual, enabling you to put the best person on any given job.


In this tutorial, we'll show you how to:

  • Create a predictive model for rep assignment using a recommender.

Let's dive in.

  1. You'll need a Faraday account — signup is free!

Confirm your data

Event stream

Unless you’ve already created it for another quickstart or purpose, you’ll need to add the following event stream to your account:

  • Transaction

What’s an event stream?

Predicting a certain customer behavior requires historical examples of customers exhibiting that behavior. Faraday works best when that data comes in the form of “events” — specific actions or occurrences that happened at specific times.

Formulating data this way helps you define cohorts more expressively.

For example, a Customers cohort could be defined as the group of people who have all experienced a Transaction event at least once.

For more, see our docs on Cohorts, Events, Traits, and Datasets (which define how events and traits emerge from your data).


To verify, use a GET /streams request. Your response should look like this:

  "name": "Transaction",
, ...}]

Make note of the IDs of the necessary streams.

If the required event stream isn't there, follow the instructions using this button, then return here to resume.

Configure your prediction

Create a rep assignment recommender


Use a POST /recommenders request:

curl --json '{
  "name": "Rep assignment",
  "stream_name": "transaction",
  "stream_property_name": "rep"

Your recommender will start building in the background. You can proceed immediately with the next set of instructions. When your recommender is done building, you’ll get an email.