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Personalization
Adaptive discounting
Offer your best promos to the customers who most deserve it — using 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 already using SQL Server and you're curious about how to fine-tune your promotional offers, Adaptive discounting predictions from Faraday might be a natural fit for you. Think of it as a way to use your existing data to figure out which customers should get the best deals, without any guesswork. Instead of blasting out one-size-fits-all promotions, you can tailor your offers based on who will truly appreciate and respond to them. It’s like giving each customer the VIP treatment they actually deserve. By integrating these predictions into SQL Server, you can seamlessly blend them into your current workflows, making it easier to act on insights and see tangible results.
- Step 1
Connect your data sources
Use the link below to connect 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 SQL Server
Finally, deploy your prediction with the link below. - Step 6
Deploy to SQL Server
Create a deployment target using the 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
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