Adaptive discounting

You will need a Faraday account to use this template. It is free to sign up and you will just need some sample data to start.

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Adaptive discounting predictions can be a great fit for those using ClickHouse to manage their data. If you're working with consumer brands, you know how important it is to offer the right promotions to the right customers. By integrating Adaptive discounting predictions with ClickHouse, you can efficiently analyze large datasets and identify which customers would benefit most from your best offers. It's all about using your resources wisely and providing value to those customers who matter most. This approach helps you make data-driven decisions without getting bogged down in complexity, and it can be a useful tool in your marketing strategy.

Step 1
Connect your data sources
Use the link below to connect ClickHouse to Faraday. You can also skip this step and use CSV files to get started instead.
ClickHouse
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.
Transaction
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.
Customers
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.
Forecasted spend
Step 5
Define your adaptive discounting pipeline and deploy to ClickHouse
Finally, deploy your prediction with the link below.
Adaptive discounting
Step 6
Deploy to ClickHouse
Create a deployment target using the ClickHouse connection you created above. Or, get started by simply deploying to CSV.
ClickHouse