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Personalization
Adaptive discounting
Offer your best promos to the customers who most deserve it — using Segment
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 Faraday and Segment, integrating Adaptive discounting predictions can bring even more value to your marketing efforts. With Adaptive discounting predictions, you can figure out which customers should receive your best promotions and tailor your offers accordingly. This helps you avoid wasting big discounts on those who don't need them while making sure your most deserving customers feel valued. It's a smart way to use your data from Segment to make your promotions more effective and personalized without overcomplicating your process. Overall, it's about making informed decisions to get the most from your marketing efforts.
- Step 1
Connect your data sources
Use the link below to connect Segment 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 Segment
Finally, deploy your prediction with the link below. - Step 6
Deploy to Segment
Create a deployment target using the Segment 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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