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Rep assignment
Assign each lead or customer to the rep that will handle them best — using Salesforce Marketing Cloud
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 using Salesforce Marketing Cloud and you're curious about how to maximize the effectiveness of your sales team, Faraday’s Rep Assignment predictions could be a great asset. With these predictions, you can match each lead or customer to the sales rep most likely to engage them effectively. This can lead to more meaningful interactions and potentially better results. It's a straightforward way to enhance your sales strategy without adding too much complexity. If you're already invested in Salesforce Marketing Cloud, integrating Faraday’s predictions could be a smart move to get the most out of your data.
- Step 1
Connect your data sources
Use the link below to connect Salesforce Marketing Cloud 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 Salesforce Marketing Cloud
Finally, deploy your prediction with the link below. - Step 6
Deploy to Salesforce Marketing Cloud
Create a deployment target using the Salesforce Marketing Cloud 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.