Signal Collection is optional but highly recommended. You can deliver offers via the REST API without Signal Collection, but enabling it significantly improves ad relevance and personalization.
Why Use Signal Collection?
Without Signal Collection:- Offers are matched based only on the current query
- Limited personalization
- No learning from past interactions
- Offers are matched using accumulated user context and preferences
- Highly personalized recommendations
- Continuous improvement over time
How It Works
There are two ways to send signals to ZeroClick:MCP Signal Server (Recommended)
The MCP Signal Server lets your LLM automatically extract signals from conversations:- Connect your agent: Your AI agent connects to the ZeroClick Signal Collection server
- Tools are exposed: The server exposes the
broadcast_signaltool to your LLM - Automatic signal collection: The LLM calls
broadcast_signalwhen it detects commercial intent - Profile building: Signals are stored and aggregated per user to build preference profiles
- Better ads: Later, when you request offers via REST API, ZeroClick uses these signals to deliver more relevant ads
REST API
If you have pre-structured signal data (e.g., IAB categories, page context, or parsed user intent), you can send signals directly via HTTP:Key Features
- Silent collection: When enabled, signals are collected without interrupting conversations
- Automatic extraction: The LLM decides when to extract signals based on conversation context
- Flexible context: Configure user context via headers for attribution
- Privacy-first: No cookies, PII must be hashed
- MCP standard: Uses the Model Context Protocol for seamless integration
Signal Categories
Thebroadcast_signal tool can extract the following types of commercial intent:
| Category | Description | Example |
|---|---|---|
interest | General interest in a product or topic | ”I’ve been thinking about getting a new laptop” |
evaluation | Actively comparing options | ”How does React compare to Vue?” |
problem | Has a problem needing a solution | ”My current database is too slow” |
purchase_intent | Active intent to buy | ”I want to buy running shoes” |
price_sensitivity | Budget indicators | ”Looking for something under $500” |
brand_affinity | Brand preferences | ”I prefer Apple products” |
user_context | Personal context | ”As a student…” |
business_context | Professional context | ”For our enterprise team…” |
recommendation_request | Asking for recommendations | ”What CI/CD tool do you recommend?” |