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Personalization
Adaptive discounting
Offer your best promos to the customers who most deserve it — using Azure SQL
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 Faraday and also working with Azure SQL, integrating Adaptive discounting predictions can be a smart move. Think of it as a way to connect your powerful AI insights directly with your data infrastructure. This means you can seamlessly determine how significant a promotion each customer deserves, right within your existing setup. By keeping everything in one place, you can streamline your workflow and make smarter, data-driven decisions about your promotional offers. It's a practical approach to maximizing your marketing efforts without complicating your technology stack.
- Step 1
Connect your data sources
Use the link below to connect Azure SQL 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 Azure SQL
Finally, deploy your prediction with the link below. - Step 6
Deploy to Azure SQL
Create a deployment target using the Azure SQL 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?
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