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Personalization
Thematic personalization
Shape your creative and message to appeal to each target — 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.
If you're a Faraday user who also uses Recharge, you might find adding thematic personalization predictions to be particularly useful. Imagine being able to tailor your messages and creatives so they resonate more with each of your customers—making your communication feel more thoughtful and personalized, without a ton of extra effort. This can be a handy way to keep your audience engaged and interested in your brand on a deeper level. Faraday's thematic personalization predictions can quietly enhance your Recharge campaigns, helping you subtly refine your approach to better appeal to your customers' tastes and preferences.
- 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 content personalization 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 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.