Product recommendation
Product recommendation predictions reveal which products individuals are most likely to respond best to, enabling you to find the perfect first-best or next-best offer.
In this tutorial, we'll show you how to:
- Create a predictive model for product recommendation using a recommender.
Let's dive in.
- You'll need a Faraday account — signup is free!
Confirm your data
Event stream
Unless you’ve already created it for another quickstart or purpose, you’ll need to add the following event stream to your account:
- Transaction
What’s an event stream?
Predicting a certain customer behavior requires historical examples of customers exhibiting that behavior. Faraday works best when that data comes in the form of “events” — specific actions or occurrences that happened at specific times.
Formulating data this way helps you define cohorts more expressively.
For example, a Customers cohort could be defined as the group of people who have all experienced a Transaction event at least once.
For more, see our docs on Cohorts, Events, Traits, and Datasets (which define how events and traits emerge from your data).
To verify, use a GET /streams
request. Your response should look like this:
[{ "name": "Transaction", "id": "$TRANSACTION_STREAM_ID" , ...}]
Make note of the IDs of the necessary streams.
If the required event stream isn't there, follow the instructions using this button, then return here to resume.
Configure your prediction
Create a product recommendation recommender
Use a POST /recommenders
request:
curl https://api.faraday.ai/recommenders --json '{ "name": "Product recommendation", "stream_name": "transaction", "stream_property_name": "product" }'
Your recommender will start building in the background. You can proceed immediately with the next set of instructions. When your recommender is done building, you’ll get an email.