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Personalization
Adaptive discounting
Offer your best promos to the customers who most deserve it — using SFTP
You’ll need a Faraday account to use this template. It’s free to sign up and you can use sample data to start.
As a Faraday user, you might find Adaptive discounting predictions in SFTP particularly useful for streamlining how you manage and distribute your promotional data. With Adaptive discounting, you can precisely target customers who are most likely to respond to your best offers, ensuring that you're not just blasting promotions indiscriminately. Using SFTP, you can securely and conveniently transfer these predictive insights directly into your existing systems or workflows. It's a straightforward way to make sure your promotional efforts are hitting the right mark without any extra hassle. Plus, it's secure and reliable, so you can focus on crafting the best offers for your deserving customers without getting bogged down in the technicalities.
- Step 1
Connect your data sources
Use the link below to connect SFTP 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 SFTP
Finally, deploy your prediction with the link below. - Step 6
Deploy to SFTP
Create a deployment target using the SFTP 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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