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Customer targeting
Repeat purchase readiness
Know which customers are ready to buy again — using Salesforce
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 to manage your customer relationships, incorporating Faraday's Repeat Purchase Readiness predictions can be a handy tool. By knowing which customers are most likely to buy again, you can better tailor your follow-up efforts and timing, making your interactions more meaningful. It's a straightforward way to integrate predictive insights directly into your existing CRM workflow, helping you to focus your resources where they're likely to have the most impact. This means less guessing and more knowing when to engage your customers for their next purchase.
- Step 1
Connect your data sources
Use the link below to connect Salesforce 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. This link 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 repeat purchase scoring pipeline and deploy to Salesforce
Finally, deploy your prediction with the link below. - Step 6
Deploy to Salesforce
Create a deployment target using the Salesforce connection you created above. Or, get started by simply deploying to CSV.
Deploy your repeat purchase readiness 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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