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Personalization
Adaptive discounting
Offer your best promos to the customers who most deserve it — using Recharge
You’ll need a Faraday account to use this template. It’s free to sign up and you can use sample data to start.
Imagine you're using Recharge for your subscriptions and you're trying to figure out the best way to offer promotions to your customers. Faraday's Adaptive discounting predictions can help you out. By figuring out exactly how significant of a promotion each customer is worth, you can make sure you're offering your most compelling discounts to those who will appreciate and respond to them the most. It takes the guesswork out of the equation, helping you make smarter, data-driven decisions. It’s just an easy way to make sure your promos are hitting the right people, at the right time.
- Step 1
Connect your data sources
Use the link below to connect Recharge 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 Recharge
Finally, deploy your prediction with the link below. - Step 6
Deploy to Recharge
Create a deployment target using the Recharge 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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