All templates
Personalization
Adaptive discounting
Offer your best promos to the customers who most deserve it — using RDS (SQL Server)
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 relies on RDS (SQL Server), integrating Adaptive discounting predictions could really enhance your promotional strategies. The key benefit is that it helps you figure out the perfect level of discount to offer each customer. By leveraging Faraday’s insights directly within your SQL Server, you can seamlessly incorporate these tailored promotions into your database workflows. It’s not about throwing out big discounts to everyone; instead, you’re making smart, data-driven decisions on who gets what, ensuring you get the best return on each promotion. It’s a straightforward way to get more value from your existing RDS setup without adding extra complexity.
- Step 1
Connect your data sources
Use the link below to connect RDS (SQL Server) 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 RDS (SQL Server)
Finally, deploy your prediction with the link below. - Step 6
Deploy to RDS (SQL Server)
Create a deployment target using the RDS (SQL Server) 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.