Summarize Closed Zendesk Tickets into New Asana Tasks

9 min setup
No coding required
Runs automatically

Save time reviewing support history and keep your team aligned by turning lengthy Zendesk ticket threads into concise, actionable updates. This workflow template automatically summarizes the comment thread of any closed Zendesk support ticket and sends that summary to Asana, ensuring your team has the key context without sifting through every message. With important details captured and shared instantly, you can speed up follow-up work, improve collaboration, and keep projects moving forward efficiently.

How it works

8 steps to start sending closed Zendesk ticket summaries to Asana automatically

Ticket Status Updated

App connector: [Zendesk](/content/apps/zendesk/integrate "View Zendesk integration page"/index.html)• Time to complete: 0 minutes (Auto-configured)
Why this matters: This trigger monitors your Zendesk tickets and kicks off the workflow whenever a ticket's status changes, catching closed tickets in real-time so you can capture insights immediately.

Retrieve Ticket

App connector: [Zendesk](/content/apps/zendesk/integrate "View Zendesk integration page"/index.html)• Time to complete: 0 minutes (Auto-configured)
Why this matters: The trigger only provides the ticket ID, so this step fetches all the detailed information about the ticket including its current status, recipient email, and timestamps needed for the summary.

Filter: Check if ticket status is closed

App connector: [Filter](/content/apps/filter/integrate "View Filter integration page"/index.html)• Time to complete: 0 minutes (Auto-configured)
Why this matters: Not every status change means a ticket closed—this filter makes sure you only summarize and document tickets that have actually been resolved and closed, preventing premature summaries of open conversations.

Get List of Comments

App connector: [Zendesk](/content/apps/zendesk/integrate "View Zendesk integration page"/index.html)• Time to complete: 0 minutes (Auto-configured)
Why this matters: The AI needs the full conversation history to generate an accurate summary—this step retrieves all comments and messages exchanged between your support team and the customer throughout the ticket's lifecycle.

Loop Over Comments

App connector: [Loop](/content/apps/loop/integrate "View Loop integration page"/index.html)• Time to complete: 0 minutes (Auto-configured)
Why this matters: The AI needs the comments formatted as a single text stream rather than separate objects—this loop extracts just the comment bodies and combines them into comma-separated text that's easy for AI to process.

Generate Title

App connector: [AI](/content/apps/ai/integrate "View AI integration page"/index.html)• Time to complete: 1 minute
Why this matters: A descriptive title helps you quickly identify what each ticket was about when reviewing your Asana board—the AI creates this by reading the conversation and extracting the core issue in plain language.

Based on the customer support thread provided {{loop_2.comma_separated}}, generate a short, descriptive title that captures the essence of the customer's concern or situation. Avoid technical jargon.

Example Input:
"Customer: I can't access my dashboard, Support: Can you try clearing your cache?, Customer: That worked, thanks!"

Example Output:
Login Issue Resolved After Basic Troubleshooting

Generate Summary

App connector: [AI](/content/apps/ai/integrate "View AI integration page"/index.html)• Time to complete: 1 minute
Why this matters: While the title provides quick context, the summary gives you the full picture including customer sentiment, resolution status, and the solution provided—this helps you identify patterns and training opportunities across multiple tickets.

Summary Writing Instructions for Support Threads:
When reviewing a customer support thread (messages separated by commas), write a short, clear summary that includes only:

-General nature of the customer's problem (no technical detail)
-Their experience or sentiment (e.g., frustration, confusion, satisfaction)
-Resolution status (resolved, pending, unclear)
-The solution provided

Example
Input:
Customer: I can't access my dashboard, Support: Can you try clearing your cache?, Customer: That worked, thanks!

Output:
The customer was unable to access their dashboard but regained access after clearing the cache. They appeared satisfied with the outcome. {{loop_2.comma_separated}}

Create Task

App connector: [Asana](/content/apps/asana/integrate "View Asana integration page"/index.html)• Time to complete: 2 minutes
Why this matters: This step delivers the AI-generated insights to your team in Asana where you can review, discuss, and act on patterns emerging from customer support conversations.

This step creates a new task in your specified Asana workspace and project using the AI-generated title as the task name. The task notes include the AI summary, original ticket number, customer email, and the timestamp when the ticket was last updated. You need to configure two fields: the workspace ID and project ID where tasks should be created—you can find these in your Asana URL when viewing the project. The task appears immediately in Asana once created.

Frequently asked questions

What happens if a ticket gets reopened and closed again later?

The workflow will run again and create a new Asana task with an updated summary that includes the additional conversation. You'll end up with two tasks for the same ticket number, which actually helps you see when issues resurface and require multiple rounds of support.

Can the AI summary include specific data like order numbers or account IDs?

Yes, the AI reads the entire conversation thread so if order numbers or account details appear in the comments, they'll be included in the summary. However, the default prompt instructs the AI to focus on general insights rather than technical details—you can modify the summary prompt if you need more specific data captured.

How accurate are the AI-generated titles and summaries?

The AI performs best with complete conversations that have clear resolution, typically achieving high accuracy for standard support interactions. Very short tickets or those with heavy technical jargon may produce less descriptive summaries—you can always edit the Asana task after creation to add context or clarification if needed.