Introduction

Understanding Products and Signals

Products and Signals are the foundation of how Paid tracks usage and generates bills. Understanding these concepts is key to getting the most out of the platform.

Products

Products represent the AI-powered offerings you sell to customers. A product can be:

  • An AI chatbot that handles customer support
  • A sales assistant that sends outreach emails
  • A data processing pipeline that analyzes documents
  • Any service that performs work on behalf of your customers

Each product in Paid has:

  • A unique identifier for tracking and billing
  • Pricing attributes that define how the product is charged (per message, per task, per outcome, etc.)
  • A product type (standard product, AI agent, or prepaid credit bundle)

Products are the “what” of your billing—they define what you’re selling and how it should be priced.

Signals

Signals are the discrete events generated when your products perform work. Every time your AI:

  • Sends a message
  • Processes a request
  • Completes a task
  • Achieves an outcome

…a Signal captures that activity. Signals include:

  • Event name: What type of action occurred (e.g., message_sent, meeting_booked)
  • Product ID: Which product performed the work
  • Customer ID: Which customer the work was performed for
  • Timestamp: When the action occurred
  • Metadata: Any additional context about the action

Signals are the “how much” of your billing—they measure the volume of work your products perform.

How Products and Signals Work Together

Paid ties each Signal back to its originating Product and Customer to generate usage-based invoices. Here’s the flow:

  1. Your AI agent performs an action

    Your AI chatbot responds to a customer inquiry.

  2. A Signal is generated

    Your application sends a Signal to Paid capturing the event—timestamp, product ID, customer ID, and relevant metadata.

  3. Paid aggregates Signals

    Signals are collected in real time and associated with the correct product, customer, and pricing tier.

  4. Usage is calculated

    At billing time, Paid tallies Signals and applies your pricing rules to calculate charges.

  5. Invoices are generated

    Customers receive itemized invoices showing exactly what they’re paying for.

Signal Types

Signals typically fall into two categories:

Activity Signals

Activity Signals track actions your products take, regardless of outcome:

  • Messages sent
  • API calls made
  • Documents processed
  • Minutes of conversation

These are useful for straightforward usage-based pricing where you charge per action.

Outcome Signals

Outcome Signals track successful results:

  • Meetings booked
  • Leads qualified
  • Tickets resolved
  • Sales closed

These enable outcome-based pricing where customers pay for results, not just activity.

Benefits of This Approach

Clear Value Justification

Every action is tracked and tied to a product. Customers see exactly what they’re paying for, and you can demonstrate the tangible value your AI delivers.

Flexible Pricing Models

Signals let you craft pricing that matches your business model:

  • Charge per action for high-volume, low-value tasks
  • Charge per outcome for high-value results
  • Combine both with hybrid models

Accurate Revenue Tracking

Real-time Signal tracking gives you precise usage data for financial planning and revenue forecasting.

Margin Visibility

By tracking both Signals (revenue) and costs (from AI providers), you can see your true margins per product and per customer.

Example Use Cases

1. Customer Support Chatbot

  • Product: AI chatbot handling customer queries
  • Signals: Each conversation or message is logged as a Signal
  • Billing: Customers pay per conversation or per message

2. AI Sales Assistant

  • Product: AI-powered SDR that sends personalized outreach
  • Signals: Each email sent is an activity Signal; each meeting booked is an outcome Signal
  • Billing: Charge per email sent, or per meeting booked, or both

3. Document Processing Pipeline

  • Product: AI that extracts data from documents
  • Signals: Each document processed is logged as a Signal
  • Billing: Customers pay per document or per page processed

Implementation Overview

1. Technical Integration

  1. Create Products: Define your products in Paid with appropriate pricing attributes.
  2. Identify Signal Points: Decide which actions should generate Signals.
  3. Integrate the SDK: Use Paid’s SDK or API to send Signals in real time.
  4. Configure Pricing: Map Signals to pricing rules in your Paid dashboard.
  5. Monitor Usage: Track Signals and usage patterns to refine pricing.

2. Best Practices

  • Keep Signal definitions clear: Each Signal type should have a unique event name and clear purpose.
  • Include relevant metadata: Add context to Signals that helps with reporting and debugging.
  • Use idempotency keys: Prevent duplicate billing by including unique identifiers with each Signal.
  • Batch when appropriate: For high-volume applications, batch Signals to optimize performance.

Key Takeaways

  1. Products are the AI-powered offerings you sell to customers.
  2. Signals are the discrete events that measure what each product does.
  3. Paid uses Signals to create transparent, usage-based billing that:
    • Demonstrates value to customers
    • Aligns costs with actual usage
    • Enables flexible pricing models

Next Steps

  • Set Up Your Products: Create products in Paid that represent your offerings.
  • Define Signal Types: Identify which actions should be tracked and billed.
  • Integrate with Paid: Implement the SDK and start streaming Signals.
  • Configure Pricing: Set up pricing rules that match your business model.