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Personalization
Adaptive discounting
Offer your best promos to the customers who most deserve it — 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 already using LinkedIn Ads to reach your audience, you might find that integrating Faraday's Adaptive discounting predictions can give you a helpful edge. This tool helps you identify which members of your target audience are most likely to respond to different levels of promotions. Instead of offering the same discount to everyone, you can strategically allocate your best offers to those who are most likely to convert, and offer smaller discounts to others. It's a practical way to make the most out of your advertising budget and drive better results without having to guess who will respond best to your promotions.
- 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 adaptive discounting 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 adaptive discounting 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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