All templates
Personalization
Adaptive discounting
Offer your best promos to the customers who most deserve it — using GCS
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 both Faraday and GCS, integrating Adaptive discounting predictions can be a smart move. It helps you figure out how significant a promotion each of your customers deserves. By offering the best deals to those who value them most, you can make your marketing efforts more efficient and effective. You'll have a clearer understanding of customer worth, enabling you to tailor promotions that resonate. It's a straightforward way to make the most of your data and keep your customers happy, without overcomplicating things.
- Step 1
Connect your data sources
Use the link below to connect GCS 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 GCS
Finally, deploy your prediction with the link below. - Step 6
Deploy to GCS
Create a deployment target using the GCS 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
Ready for easy AI?
Skip the ML struggle and focus on your downstream application. We have built-in sample data so you can get started without sharing yours.