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Personalization
Rep assignment
Assign each lead or customer to the rep that will handle them best — using Segment
You’ll need a Faraday account to use this template. It’s free to sign up and you can use sample data to start.
Sure thing. If you're using Segment to manage your customer data and want to make sure your leads and customers are handled by the best possible rep, Faraday's Rep assignment predictions can be a real game-changer. Essentially, it helps you figure out which of your reps is most likely to engage effectively with each target, leading to better experiences for your customers and potentially improved results for your team. It's a straightforward way to make your customer interactions more personalized and efficient, right within the Segment platform you're already using. Give it a try if you're curious about optimizing those connections.
- Step 1
Connect your data sources
Use the link below to connect Segment 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. These links 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 rep assignment pipeline and deploy to Segment
Finally, deploy your prediction with the link below. - Step 6
Deploy to Segment
Create a deployment target using the Segment connection you created above. Or, get started by simply deploying to CSV.
Deploy your rep assignment 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
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Skip the ML struggle and focus on your downstream application. We have built-in sample data so you can get started without sharing yours.