Conclusion and next steps

In this tutorial, you've built a Next.js AI agent that uses Snowplow Signals to deliver personalized, context-aware responses based on live user behavior.

Here's what you set up:

• Snowplow Browser tracker capturing page views, page pings, and link clicks
• A Signals attribute group computing real-time session-level attributes
• A Signals service exposing those attributes via API
• A floating chat widget that passes the Snowplow session ID with every request
• A Vercel AI SDK agent that fetches and injects those attributes into its system prompt

Here are some next steps ideas for extending what you've built.

Richer attributes

The Basic Web attribute group template covers basic session-level behavior. For further personalization, try extending your attribute group with:

• Product affinity: count of views per product category to understand user interest
• Engagement score: a computed signal of session depth and intent
• Return visitor flag: whether this is a new or returning user
• Funnel stage: where the user is in a defined conversion journey

Interventions

Signals also includes interventions. These are push-based triggers that fire when a user crosses a behavioral threshold.

Rather than waiting for the user to ask a question, you can proactively provide context to your agent when something significant happens. For example, a user who has viewed pricing 5+ times and not converted.

Try exploring how you could use interventions within this application.

Multi-dimensional context

You can combine Signals real-time stream attributes with automatic ingestion of batch attributes, using data sources within your warehouse, to give your agent a complete picture of the user. This could include attributes such as user profile data, CRM attributes, or product usage history.

Try setting up a batch attribute group to ingest as part of your web-agent-context service.

The Vercel AI SDK's system prompt is just a string: you can compose it from as many sources as you need.

Other Signals tutorials

Check out these other Signals tutorials and solution accelerators for inspiration:

• Set up Signals for real-time calculation
• Implement real-time interventions using Signals
• Score prospects in real time using Signals and ML
• Use AWS BedRock to supplement Signals with persistent user context