Learn how to implement real-time interventions in an ecommerce app using Signals

Welcome to the Snowplow Signals tutorial.

Snowplow Signals computes attributes from your behavioral data in real time and serves them to your applications over an API. It works with both in-session stream data and historical warehouse data.

This tutorial provides a hands-on introduction to Signals. You'll use Python to programmatically define attributes, services, and interventions, then test them with a demo ecommerce application.

To follow this tutorial, you'll need a Snowplow account with Signals enabled.

Snowplow account required

If you don't have a Snowplow account, you can sign up for the Signals free tier to follow along.

This tutorial should take approximately 20-30 minutes to complete.

What you'll learn

In this tutorial, you will:

• Set up your Signals connection through Snowplow Console
• Use the Signals Python SDK to define attributes, services, and interventions
• Calculate real-time user behavior metrics from ecommerce events
• Create intervention rules that trigger personalized experiences
• Test your Signals configuration with an interactive demo application

Deployment

You can enable Signals through Snowplow Console on any Snowplow account, including the Signals free tier. Signals includes event collection, so you don't need to run a Snowplow pipeline first. If you already run Snowplow, Signals reads the events from your existing pipeline.

Enabling Signals in Console provides:

• Access to your production behavioral data
• Full production capabilities and support

Prerequisites

This tutorial requires:

• Python 3.7 or higher
• A Jupyter notebook environment (local or Google Colab)
• Basic familiarity with Python
• A modern web browser for testing the demo application
• A Snowplow account with Signals enabled