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Personalization
Adaptive discounting
Offer your best promos to the customers who most deserve it — using Google 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 using Google Ads and wondering how to make the most of your ad spend, Faraday's Adaptive Discounting might be a great complement. It helps you figure out just how significant a promotion each of your customers is worth. Instead of offering a flat discount to everyone, you can tailor your offers to those who are most likely to convert with the right nudge. This means you can be more efficient with your budget, focusing your best promotions on the customers who are truly deserving. It's a thoughtful approach that can help you optimize your marketing efforts without any unnecessary flash. Just simple, smart targeting.
- Step 1
Connect your data sources
Use the link below to connect Google 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 Google Ads
Finally, deploy your prediction with the link below. - Step 6
Deploy to Google Ads
Create a deployment target using the Google 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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