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Intercom

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Last updated 2 months ago

Perfect, here’s the full Intercom Integration doc page in the same format as Slack. Just plug your screenshots in the right spots 📸

💬 Intercom Integration – Step-by-Step Guide

Intercom is packed with valuable customer insights — tickets, chats, events, and engagement data. With Calk, you can connect it and power your AI agents with everything they need to help, respond, and generate with relevance.

✅ What You Can Pull from Intercom

Once connected, Calk will have access to:

  • 👤 Users & Companies View all your users, segments, and company info

  • 🧵 Conversations & Messages Pull full chat history to feed your agents

  • 🎟️ Tickets & Events Get a timeline of customer touchpoints and support

  • 📊 Engagement Data Use open/click rates to personalize messaging

  • 🏷️ Tags & Segments Add filters to personalize your prompts

Your agents will instantly have more context to respond like a human.

🔄 How to Connect Intercom to Calk (Step-by-Step)

  1. Go to the Knowledge Hub → Click “Knowledge” in the sidebar → Under Integrations, click Intercom

  2. Click “Connect” → A pop-up will open to authenticate with Intercom → Select your Intercom workspace → Authorize Calk access to read data

Done ✅ Your Intercom integration will now appear in your Knowledge panel. You can add this tool to any agent during its creation.

🔐 Intercom Permissions Calk Uses

Name
What It Does

Read and list users and companies

Full visibility on customer base

Read conversations

Feed agents your customer support history

Export engagement data

Let agents prioritize based on opens/clicks

Read tags & events

Helps contextualize behavior over time

Read tickets

Allow agents to summarize, follow-up, or auto-respond

📌 You can revoke access or manage permissions anytime from your Knowledge Hub.

🤖 Use Cases With Intercom + Calk

  • Auto-summarize conversations: Generate a quick summary of the last 5 customer chats using your agent.

  • Draft smarter replies: Ask your agent to write a reply based on past conversations and tags.

  • Understand churn signals: Use event and message data to identify disengaged customers.

  • Pre-fill outbound messages: Combine CRM and conversation data for hyper-personalized AI emails.