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Personalization
Adaptive discounting
Offer your best promos to the customers who most deserve it — using Stripe
You’ll need a Faraday account to use this template. It’s free to sign up and you can use sample data to start.
Hey there! If you're a fan of both Faraday and Stripe, you're in luck. Adaptive discounting predictions from Faraday can be a great way to optimize your promotions within Stripe. Imagine knowing exactly how much of a discount each of your customers would respond to best. Instead of offering the same promo to everyone and hoping it sticks, you can use these predictions to tailor your discounts based on customer data. This way, you can offer just the right amount to really appeal to each individual and potentially save some budget while doing it. It's a thoughtful approach that helps you get more out of your promotional efforts in Stripe, making your marketing more efficient and targeted.
- Step 1
Connect your data sources
Use the link below to connect Stripe 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 Stripe
Finally, deploy your prediction with the link below. - Step 6
Deploy to Stripe
Create a deployment target using the Stripe 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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