Snowplow Signals Documentation

Snowplow Signals computes user attributes from your behavioral data in real time, and serves them to your applications over an API. Attributes are calculated from your Snowplow event stream as events arrive, or synced from tables in your warehouse.

Use Signals to:

• Personalize content, recommendations, and pricing based on what the user is doing in their current session
• Give chatbots and AI agents context about the user they're interacting with
• Trigger actions automatically when users meet criteria you define, such as offering a discount when a high-value cart is abandoned
• Serve up-to-date behavioral features to ML models, for use cases like lead scoring

Try Signals

Signals calculates attributes from events flowing through a Snowplow pipeline. If you don't have one, you can start on the Signals free tier. It needs no credit card.

Explore Signals

Attributes

Calculate user attributes in real time

Learn about attributes Define attributes Retrieve attributes

Interventions

Trigger actions automatically

Learn about interventions Define interventions Subscribe to interventions

Signals Python SDK

Use Signals within a notebook

Connect to Signals Define attributes Define interventions

Get hands on with Signals

More resources

Visit our Developer Hub for demo videos, blog posts, workshops, and more.

Build a personalized travel agent

Set up a demo travel site, and integrate with Snowplow Signals to personalize content and chatbot responses based on user behavior

Score prospects in real time using Signals and ML

Try out Signals for live prospect scoring with machine learning

Implement real-time interventions in an ecommerce app

Explore Signals interventions in a demo e-shop application

See all tutorials ->

For a comparison of Signals with feature stores, CDPs, and building the same thing in-house, see Evaluate Signals.