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Webhook

Definition

A webhook is an HTTP callback mechanism that automatically sends data from one system to another when a specific event occurs. Instead of continuously polling an API for updates, the source system pushes data to a configured URL in real time. Webhooks are the backbone of real-time integrations between SaaS applications.

How it works

Webhooks follow a simple pattern:

  1. Configure: You register a URL endpoint where you want to receive data
  2. Trigger: An event occurs in the source system (new message, ticket created, payment received)
  3. Deliver: The source system sends an HTTP POST request to your URL with event data as JSON
  4. Process: Your endpoint receives the data and takes action (update database, send notification, trigger workflow)

Webhooks are event-driven, they fire only when something happens, unlike API polling which checks repeatedly whether anything changed. This makes webhooks more efficient and provides near-instant data delivery.

In customer support, webhooks connect chatbots to CRMs, ticketing systems, payment processors, and internal tools, enabling the AI to trigger actions and receive updates from across the business tech stack.

Why it matters

Webhooks transform chatbots from isolated Q&A tools into connected systems that can trigger real actions. Without webhooks, a chatbot can tell you about your order status. With webhooks, it can update your shipping address, process a refund, and notify the fulfillment team, all within the same conversation. Webhooks are what make agentic AI possible in practice.

How Chatsy uses it

Chatsy supports webhook integrations that enable AI chatbots to send and receive data from external systems. When a conversation reaches a specific point (lead captured, escalation triggered, issue classified), Chatsy can fire a webhook to your CRM, ticketing system, or automation platform with full conversation context, enabling real-time workflows that extend beyond the chat widget.

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What else should I know about Webhook?

They are more efficient than API polling, no wasted requests, near-instant data delivery

Key takeaways

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Example scenarios

  1. 01

    Lead capture to CRM

    When the AI chatbot qualifies a lead (collects name, email, company, and use case), a webhook fires to Salesforce or HubSpot, creating a new contact record with the full conversation transcript. The sales team gets notified instantly and can follow up while the lead is still warm.

  2. 02

    Escalation to ticketing system

    When the AI determines a conversation needs human attention, a webhook creates a ticket in Zendesk or Linear with the conversation summary, customer details, priority classification, and AI-attempted resolution steps. The support agent opens a fully contextualized ticket, not a blank one.

  3. 03

    Real-time Slack notifications

    A webhook sends a Slack notification to the #support channel whenever the AI chatbot escalates a conversation or a customer gives negative feedback. The team can jump in immediately from Slack, reducing escalation response time from minutes to seconds.

Key takeaways

  • Webhooks send data automatically when events occur, providing real-time integration between systems
  • They are more efficient than API polling, no wasted requests, near-instant data delivery
  • In customer support, webhooks connect chatbots to CRMs, ticketing systems, and automation platforms
  • Webhooks enable agentic capabilities by allowing chatbots to trigger real-world actions beyond text responses
  • Reliable webhook implementations include retry logic, signature verification, and idempotency handling

Frequently asked questions

An API requires you to make a request to get data (pull model). A webhook sends data to you automatically when an event occurs (push model). APIs are for on-demand data retrieval; webhooks are for real-time event notifications. Most integrations use both: webhooks for real-time notifications and APIs for data retrieval.

Use tools like webhook.site, ngrok, or RequestBin to create temporary endpoints that capture incoming webhook payloads. These let you see exactly what data is being sent, debug formatting issues, and test your processing logic before deploying to production.

Well-designed webhook systems implement retry logic, typically 3-5 retries with exponential backoff (wait 1 second, then 10, then 60, then 300). If all retries fail, the event is logged for manual review. Your receiving endpoint should return a 200 status quickly and process data asynchronously to avoid timeouts.

Webhook security requires: HTTPS endpoints (encrypted transport), signature verification (confirming the sender is legitimate using a shared secret), and payload validation (checking data structure before processing). Never trust webhook data blindly, always verify the signature and validate the payload.

Stand up an HTTPS endpoint on your server that accepts POST requests and returns a 200 status, then register that URL in the source system (CRM, payment processor, chatbot platform). The source system sends a JSON payload to your endpoint when the chosen event happens. Add signature verification using the source's shared secret before trusting any payload.

The webhook itself is the event-delivery mechanism, but yes, the visible piece you configure is a URL: an HTTPS endpoint that listens for POST requests. The full system is: a registered URL, an event that triggers a delivery, the JSON payload, and the receiver code that processes it.

When an AI chatbot captures a qualified lead, the chat platform fires a webhook to your CRM's URL with the contact info and conversation transcript as JSON. The CRM creates the record automatically and notifies the sales rep, no manual data entry, no batch sync, all within seconds of the conversation ending.

Related terms

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Further reading

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