Time-to-Close – Analyze and report average resolution times for Zendesk

Tracking and optimizing your Time-to-Close — the average resolution times of support tickets — is critical for providing stellar customer service and operational efficiency 🚀. For Zendesk teams, having clear insight into your resolution timelines helps focus efforts on bottlenecks and improves SLA adherence.

In this article, you’ll learn a practical, step-by-step guide to building powerful automation workflows using popular tools like n8n, Make, and Zapier. We’ll integrate services such as Gmail, Google Sheets, Slack, and HubSpot to analyze, report, and communicate Zendesk ticket resolution metrics automatically.

Designed for startup CTOs, automation engineers, and operations specialists, this tutorial covers end-to-end architecture, node-by-node configuration, error handling, and scaling tips — helping you transform raw Zendesk data into actionable insights.

Understanding Time-to-Close and Its Importance in Zendesk

Time-to-Close refers to the average duration between the creation and resolution of tickets in Zendesk. Monitoring this metric helps teams measure responsiveness and efficiency.

High average resolution times can indicate resource bottlenecks or inefficient workflows, causing reduced customer satisfaction and SLA breaches. Automating the analysis and reporting process allows teams to proactively address delays and optimize support performance.

Overview of the Automation Workflow

Our goal is to build a reliable automation pipeline that:

1. Extracts ticket data from Zendesk when tickets are closed.
2. Calculates the resolution time (Time-to-Close) for each ticket.
3. Aggregates average resolution times periodically.
4. Updates a Google Sheet dashboard with summarized metrics.
5. Sends alert notifications to Slack or emails if average resolution times exceed thresholds.
6. Logs data into HubSpot for customer success visibility.

We will demonstrate this using three popular automation platforms: n8n, Make, and Zapier for comparison and choice flexibility.

Step-by-step Automation Using n8n

Prerequisites

• Zendesk account with API access.
• n8n instance (self-hosted or cloud).
• Google account for Sheets API.
• Slack workspace and webhook URL.
• HubSpot API key (optional).

Workflow Architecture

The workflow trigger is a Webhook that listens for ticket updates from Zendesk. When a ticket closes, Zendesk sends data via webhook to n8n.

The workflow then calculates the resolution time by subtracting the ticket creation timestamp from the closing timestamp. Data is appended to a Google Sheet for historical record-keeping. Average resolution times are calculated periodically by n8n’s scheduler node.

If the average resolution surpasses a set threshold (e.g., 24 hours), a Slack notification and Gmail alert are sent. Lastly, ticket data is enriched and pushed to HubSpot.

Node-by-Node Breakdown

1. Webhook Trigger: Configure method POST, path /zendesk-ticket-closed.
   Expected payload includes ticket_id, created_at, solved_at, and requester info.
2. Function Node (Calculate Time-to-Close): Use JavaScript:
   const created = new Date(items[0].json.created_at);
const solved = new Date(items[0].json.solved_at);
const resolutionMs = solved - created;
items[0].json.time_to_close_hours = resolutionMs / 3600000;
return items;
3. Google Sheets – Append Row: Connect to your Sheet with columns: Ticket ID, Created At, Solved At, Time to Close (hours).
   Map fields accordingly.
4. Scheduler Node: Runs daily at 00:00 to trigger average time calculation.
5. Google Sheets – Read Rows: Retrieve last 30 days of Time to Close values.
6. Function Node (Calculate Average): Aggregate and calculate average time to close using JavaScript.
7. If Node (Check Threshold): Condition average > 24 hours triggers alerts.
8. Slack Node: Post message to support channel informing about SLA issues.
9. Gmail Node: Send email alert to support manager.
10. HubSpot Node: Enrich contact or ticket data with resolution info.

Handling Errors and Robustness

• Use Error Trigger nodes to handle failures gracefully.
• Implement retries with exponential backoff for API calls to respect rate limits.
• Use idempotency keys to avoid duplicate rows in Google Sheets.
• Log all errors and successful runs in a dedicated logging Google Sheet or database.

Security and Compliance

• Store API keys and tokens securely using n8n credentials management.
• Limit scope of API keys to minimum necessary permissions.
• Mask or anonymize any Personally Identifiable Information (PII) in logs.
• Verify webhook payload origins using shared secrets or signature verification.

Scaling and Adaptations

• For high volume Zendesk tickets, switch Webhook trigger to a queue-based processing system.
• Use concurrency controls in n8n to limit parallel executions.
• Modularize workflow by separating data extraction, transformation, and alerting in sub-workflows.
• Use webhook vs polling reconciliation: if webhook is unreliable, fallback to scheduled incremental API pulls.

Automation Example Using Make

Scenario

Make (formerly Integromat) offers visual scenario building. We set up Zendesk module to watch ticket events.

Scenario Steps

1. Zendesk Watch Tickets Module: Filters for status ‘solved’.
2. Google Sheets Add a Row: Append the ticket info with calculated resolution time using Make’s built-in date functions.
3. Iterator and Aggregator: Process batch data for average calculation.
4. Conditional Router: Checks average resolution time and routes to alert modules if needed.
5. Slack > Send Message and Gmail > Send Email if SLA breached.

Tips & Configurations

• Use bundle filters to exclude irrelevant tickets.
• Set HTTP header Authorization with Bearer token for Zendesk API calls.
• Use built-in date/time functions for reliable Time-to-Close calculation.
• Schedule scenario to run repeatedly every hour for near real-time insight.

Zapier Workflow for Time-to-Close Analysis ⚡

Core Zap Setup

• Trigger: Zendesk New Ticket or Updated Ticket — filter for status = Solved.
• Action 1: Formatter by Zapier – Date/Time Calculate to find duration between created_at and solved_at.
• Action 2: Google Sheets – Create Spreadsheet Row with ticket details and duration.
• Action 3: Filter – Check if average duration in last 24 hrs exceeds threshold.
• Action 4: Slack – Send channel notification.
• Action 5: Gmail – Email notification to management.

Zapier Limitations and Workarounds

• Zapier has built-in task limits; batching averages may require multi-step Zaps or external services.
• Use Google Sheets formulas to calculate rolling averages automatically.
• Combine with webhooks by Zapier for advanced customizations.

Comparing Automation Platforms for Zendesk Time-to-Close Workflows

Platform	Cost	Pros	Cons
n8n	Free (self-hosted), Paid cloud plans	Open source, highly customizable, strong error handling, no per-task cost	Self-host requires maintenance, learning curve
Make (Integromat)	Free tier up to 1,000 ops/mo, Paid plans from $9/mo	Visual drag-and-drop, robust data parsing, great for complex scenarios	Pricing grows with ops, some delay on free plan
Zapier	Free tier 100 tasks/day, Paid plans start $19.99/mo	Easy to start, tons of supported apps, good docs	Task limits, less customization, expensive scaling

Webhook vs Polling for Zendesk Data Integration

Method	Latency	Resource Usage	Use Case
Webhook	Near real-time	Low	Best for event-driven updates
Polling	Delayed (dependent on schedule)	High with frequent polls	Fallback when webhooks unsupported or unreliable

Google Sheets vs Database for Time-to-Close Data Storage

Storage Option	Cost	Pros	Cons
Google Sheets	Free with limits	Easy to set up, share, lightweight analysis, integrations	Limited scalability, potential data consistency issues
Relational Database	Varies by provider	Scalable, transactional integrity, complex queries	Requires setup, admin, more complex

Monitoring, Testing, and Maintenance

Testing with Sandbox Data

Use Zendesk sandbox and test tickets to verify the workflow. Check event payloads, time calculations, and data writes without affecting production.

Run History and Logs

All platforms provide execution logs and error details. Set up alerts for failed runs or API rate limit warnings.

Alerts and Notifications

Configure secondary notifications (email or Slack) for errors or skipped tickets to keep your team informed.

Regular Maintenance

Periodically review API tokens, update workflow versions, and test after Zendesk API changes to ensure continuity.

Conclusion

Analyzing and reporting average resolution times (Time-to-Close) in Zendesk is essential for operational excellence. By leveraging automation platforms such as n8n, Make, or Zapier integrated with Gmail, Google Sheets, Slack, and HubSpot, you can build efficient, actionable workflows that keep your support team agile and SLA-compliant.

Focus on robust error handling, security best practices, and scalability to ensure long-term reliability. Start by implementing simple workflows with real ticket data, then incrementally enhance to include real-time alerts and advanced analytics.

Ready to optimize your Zendesk support metrics? Automate your Time-to-Close analysis today and unlock data-driven customer service improvements!