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Personalization
Thematic personalization
Shape your creative and message to appeal to each target — using S3
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 being able to tailor your marketing messages and creative content perfectly to each customer. With Faraday’s Thematic Personalization predictions, you can do just that. And, if you're already using Amazon S3, integrating these predictions into your workflow becomes seamless. Store all your personalized data securely in S3 and easily access it whenever you need to craft the right message for the right audience. It's a simple way to make your marketing more effective without overcomplicating your process. Give it a try and see how small adjustments can make a big difference.
- Step 1
Connect your data sources
Use the link below to connect S3 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 content personalization pipeline and deploy to S3
Finally, deploy your prediction with the link below. - Step 6
Deploy to S3
Create a deployment target using the S3 connection you created above. Or, get started by simply deploying to CSV.
Deploy your thematic personalization 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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Skip the ML struggle and focus on your downstream application. We have built-in sample data so you can get started without sharing yours.