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Personalization
Rep assignment
Assign each lead or customer to the rep that will handle them best — using Klaviyo
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 a Faraday user who's also using Klaviyo, you might find Rep assignment predictions pretty useful. Imagine you're trying to figure out which of your sales reps should connect with each customer to get the best results. With Rep assignment predictions in Klaviyo, you can streamline this process. It helps you match the right rep with the right lead based on who’s likely to engage them most effectively. This means your team can work more efficiently and your customers get a better experience. It's a modest step that can make your outreach a bit more personal and productive.
- Step 1
Connect your data sources
Use the link below to connect Klaviyo 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 Klaviyo
Finally, deploy your prediction with the link below. - Step 6
Deploy to Klaviyo
Create a deployment target using the Klaviyo 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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