Chat with your Zendesk Chat (Zopim) data

AI to analyze Zendesk Chat (Zopim) data with Claude and ChatGPT

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No credit card required | 14 days | 10 million records | 30 pipelines

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Zendesk Chat (Zopim)
You
How many chat sessions did we handle last week?
Zendesk Chat
You handled 1,247 chat sessions last week with an average duration of 4.2 minutes per conversation.
Via Kondado MCP
You
What was our average customer satisfaction rating this month?
Support Metrics
Your current satisfaction score is 4.6 out of 5 based on 892 rated conversations this month.
Via Kondado MCP
You
Which agent had the fastest response time yesterday?
Agent Performance
Agent Sarah M. achieved the fastest average response time of 42 seconds across 34 handled chats.
Via Kondado MCP
You
How does this month's chat volume compare to last month?
Chat Analytics
Chat volume increased by +18% MoM with 3,421 sessions compared to 2,898 last month.
Via Kondado MCP
Works in Claude, ChatGPT and any MCP client

AI to analyze Zendesk Chat (Zopim) data with Claude and ChatGPT

Ask Claude, ChatGPT, or any other MCP client about your Zendesk Chat (Zopim) data using natural language chat. Customer support managers can query agent response times, operations teams can monitor chat volume trends, and CX analysts can investigate satisfaction rating patterns across specific date ranges. Simply start a conversation to uncover insights about session duration, visitor behavior, and team performance without writing SQL or opening a spreadsheet.

Kondado exposes Zendesk Chat (Zopim) data through an MCP server, enabling direct analysis in Claude and ChatGPT using natural language. The setup includes 1 pipeline with 76 fields covering chat sessions, agent performance, and visitor interactions. The same replicated data also powers ready reports in Power BI and Looker Studio for visual monitoring.

Support supervisors benefit from asking about individual agent productivity and conversation outcomes, while e-commerce managers can correlate chat activity with sales periods. Operations directors use this to identify peak traffic hours and staffing needs, and finance teams can analyze support cost efficiency through resolution metrics. All these roles simply type questions in chat to receive immediate answers about their Zendesk Chat (Zopim) metrics.

I prefer ready dashboards

Dashboard templates in Power BI and Looker Studio, connected to your Zendesk Chat (Zopim) data by Kondado in minutes.

View Zendesk Chat (Zopim) dashboards →

I want to ask the AI

Claude, ChatGPT and other MCP clients query your Zendesk Chat (Zopim) data in natural language.

View MCP setup →

Data available for AI analysis

The pipeline listed below contains comprehensive chat session information ready for your AI queries. The Chats pipeline includes 76 fields capturing duration timestamps, average response intervals, and satisfaction scores alongside visitor identification and agent assignment details. You can investigate specific conversation outcomes, compare performance across different support agents, or segment sessions by visitor behavior patterns using these detailed records. While this source currently offers one primary pipeline, the depth of session data enables sophisticated analysis of customer interactions and support efficiency. Data updates on a configurable schedule, ensuring your AI responses reflect recent chat activity without manual refreshes.

How to connect Zendesk Chat (Zopim) to Claude, ChatGPT and other AI clients

MCP is an open standard. Add the Kondado server to the connections of Claude (Web or Desktop), ChatGPT, or any other MCP client you use, and authorize via OAuth at app.kondado.com.br. Setup through the UI, no code.

Kondado MCP server: https://mcp.kondado.io/mcp
Detailed guide: Claude Detailed guide: ChatGPT
AI vocabulary

Zendesk Chat (Zopim) tables and metrics available via Kondado

Each item below is something Claude, ChatGPT or another MCP client already knows how to query — no schema setup, no manual mapping.

1
Table
76
Fields
∞
Ad-hoc questions
Chats
Chats table includes information such as duration, average response time, and satisfaction rating. Fields include id, visitor name, agent name, and session data.
Full docs on the wiki → Connect Zendesk Chat (Zopim) now →

How to connect and use AI with your data

In 3 steps: connect on Kondado, pick dashboard or chat, analyze.

1
Connect Zendesk Chat and select destination

Log in to app.kondado.com.br, add Zendesk Chat (Zopim) as a data source, and choose a 'Via Kondado' destination so your data lands ready for AI access and the dashboard templates.

2
Configure Claude or ChatGPT settings

In Claude (Web or Desktop) or ChatGPT, open the connection settings, add the Kondado MCP server, and complete OAuth authorization at app.kondado.com.br. Both clients use the same GUI-based setup with no CLI commands or code required.

3
Start analyzing in chat or dashboards

Ask questions in natural language about your Zendesk Chat data to get immediate answers, or open a ready Power BI or Looker Studio dashboard template for visual recurring monitoring of your support metrics.

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Related on Kondado

Frequently asked questions about AI

How ready dashboards and chat via Claude / ChatGPT work together with your data via Kondado.

What specific business questions can I ask Claude or ChatGPT about my Zendesk Chat data? ▼
You can ask about agent performance comparisons, average response time trends, customer satisfaction ratings by date range, chat volume during specific campaigns, and visitor session patterns. The AI interprets your natural language questions and queries the 76 available fields to return specific metrics and summaries.
How do I configure Claude or ChatGPT to access my Zendesk Chat data? ▼
In Claude (Web or Desktop) or ChatGPT, navigate to the connection settings and add the Kondado MCP server. The interface guides you through OAuth authorization at app.kondado.com.br, where you grant permission once for the AI to read your replicated Zendesk Chat data. Other MCP clients also work with the same server configuration.
Can the AI execute actions in Zendesk Chat or write data back to the source? ▼
No, the AI provides read-only analytical chat capabilities. You can ask questions, request calculations, and explore trends, but the MCP connection does not create tickets, update chat statuses, or modify any data in your Zendesk Chat account.
How does authentication work when connecting Zendesk Chat to the AI? ▼
You authenticate once via OAuth at app.kondado.com.br, where you select your Zendesk Chat data source and authorize the connection.
How frequently is my Zendesk Chat data updated for AI analysis? ▼
Data replicates on a configurable schedule that you set in Kondado, ensuring the AI answers based on recent information without manual exports. The update frequency can be adjusted based on your operational needs for chat analytics.
What is the difference between asking the AI in chat and using the ready dashboards? ▼
Chat provides exploratory, on-demand answers to specific questions using natural language, while ready reports in Power BI and Looker Studio offer visual templates for recurring monitoring and standardized KPI tracking. Both use the same underlying replicated data from your Zendesk Chat account.
Which dashboard templates are available for Zendesk Chat data? ▼
Kondado offers ready report templates in Power BI and Looker Studio specifically designed for support analytics, including agent performance scorecards, chat volume trends, and customer satisfaction monitoring dashboards.

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