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Customer targeting
Repeat purchase readiness
Know which customers are ready to buy again — using LinkedIn Ads
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 also leverages LinkedIn Ads, integrating repeat purchase readiness predictions can be a smart move. Think about it: LinkedIn is a place where professionals congregate, often in a mindset that's receptive to relevant content. By knowing which of your customers are most likely ready to buy again, you can fine-tune your LinkedIn Ads to target those individuals specifically. It’s a straightforward way to make your ad spend more efficient and boost the relevance of your ads. This approach can help you gently nudge those ready-to-buy customers along their journey, potentially leading to more repeat purchases without unnecessary guesswork.
- Step 1
Connect your data sources
Use the link below to connect LinkedIn Ads 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 LinkedIn Ads
Finally, deploy your prediction with the link below. - Step 6
Deploy to LinkedIn Ads
Create a deployment target using the LinkedIn Ads 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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