## Introduction
Response SLAs (Service Level Agreements) in Zendesk help customer support teams measure how fast agents reply to tickets, ensuring timely responses and high customer satisfaction. However, Zendesk’s SLA feature can be costly for startups or small teams looking to optimize their support workflows without ballooning expenses. This article guides technical audiences such as startup teams, automation engineers, and operations specialists on how to replicate the core SLA metric—tracking agent response times—using the open-source automation tool n8n.
By integrating Zendesk’s ticketing API with n8n, we can build a custom SLA tracking workflow that notifies the team of ticket response deadlines, reports on agent responsiveness, and maintains an overview dashboard, all at a fraction of the cost of Zendesk’s native SLA feature.
## What Problem Does This Automation Solve?
– **Problem:** Expensive SLA features within Zendesk for monitoring first reply times and agent responsiveness.
– **Who Benefits:** Startup founders, support managers, and automation specialists seeking cost-efficient, customizable SLA tracking. Also suitable for teams wanting transparent, tailored SLA metrics beyond Zendesk’s default configurations.
## Tools and Services Integrated
– **Zendesk API:** To fetch and update tickets, including timestamps on ticket creation, first agent replies, and ticket statuses.
– **n8n:** Orchestrates the automation workflow, performing periodic checks and calculations.
– **Google Sheets (optional):** To log SLA metrics and enable reporting.
– **Slack (optional):** For SLA breach alerts.
## How the Workflow Works
1. **Trigger:** A scheduled trigger node runs periodically (e.g., every 10 minutes) to check for new or updated tickets in Zendesk.
2. **Fetch Tickets:** Use Zendesk API to retrieve tickets created within a defined time window that are still open and awaiting agent response.
3. **Calculate SLA:** For each ticket, compute elapsed time since ticket creation and check if the first response deadline is approaching or has passed.
4. **Notify or Log:** Based on SLA status, send alerts (e.g., Slack messages) or log data to Google Sheets for reporting.
5. **Update Ticket Tags or Fields:** Optionally update Zendesk ticket tags or custom fields to indicate SLA statuses.
## Technical Tutorial: Step-by-Step
### Prerequisites
– Access to Zendesk account with API credentials (email/token).
– An n8n instance running (cloud or self-hosted).
– Google account for Sheets integration (optional).
– Slack workspace for notifications (optional).
### Step 1: Set Up the Scheduled Trigger in n8n
– In n8n, create a new workflow.
– Add the **Cron** node.
– Configure it to run every 10 minutes:
– Mode: Every X minutes
– Minutes: 10
### Step 2: Fetch Relevant Tickets from Zendesk
– Add an **HTTP Request** node for Zendesk API call.
– Configure as follows:
– Method: GET
– URL: `https://{your_subdomain}.zendesk.com/api/v2/search.json?query=type:ticket status
– Replace `{your_subdomain}` accordingly.
– Adjust the query to fetch open tickets created within the last day or period of interest.
– Authentication: Basic Auth with email/token.
– This will return tickets that are open and require response.
### Step 3: Process Tickets and Determine SLA Status
– Add a **Function** node to iterate through tickets and calculate time difference.
– Input variables:
– Ticket creation time (created_at).
– Timestamp of first public comment by agent (if any).
– Logic:
– If the first agent reply is missing, calculate time since creation.
– If elapsed time > SLA threshold (e.g., 1 hour for first reply), mark as breached.
**Example JavaScript for calculating SLA breach:**
“`javascript
const tickets = items;
const SLA_THRESHOLD_HOURS = 1;
const now = new Date();
return tickets.map(item => {
const ticket = item.json;
const createdAt = new Date(ticket.created_at);
// Find first agent comment timestamp
let firstAgentReply = null;
for (const comment of ticket.comments || []) {
if(comment.author.role === ‘agent’ && comment.public === true) {
firstAgentReply = new Date(comment.created_at);
break;
}
}
let slaStatus = ‘pending’;
if(firstAgentReply) {
const timeDiff = (firstAgentReply – createdAt) / (1000 * 60 * 60); // in hours
slaStatus = timeDiff <= SLA_THRESHOLD_HOURS ? 'met' : 'breached';
} else {
const timeDiff = (now - createdAt) / (1000 * 60 * 60); // in hours
slaStatus = timeDiff > SLA_THRESHOLD_HOURS ? ‘breached’ : ‘pending’;
}
item.json.slaStatus = slaStatus;
return item;
});
“`
> Note: You will need an additional API call to fetch comments for each ticket (see Step 4).
### Step 4: Fetch Comments for Tickets (to find first agent reply)
– Because ticket objects from search do not always include comments, add a **HTTP Request** node.
– Use n8n’s **SplitInBatches** node after the ticket list to process one ticket at a time.
– Fetch comments from `https://{your_subdomain}.zendesk.com/api/v2/tickets/{ticket_id}/comments.json`.
– Attach comments data to each ticket for Step 3’s Function node.
### Step 5: Notify via Slack or Log to Google Sheets
– **Slack Notification (optional):**
– Add a **Slack** node.
– Configure to post a message when SLA is breached.
– Format message to include ticket ID, URL, and SLA status.
– **Google Sheets Logging (optional):**
– Add a **Google Sheets** node.
– Append rows containing ticket details and SLA status.
– This facilitates reporting and long-term tracking.
### Step 6: Update Zendesk Ticket with SLA Status (Optional)
– Use Zendesk API PATCH request to add tags or update custom fields to indicate SLA breach.
## Common Errors and Tips
– **Rate Limiting:** Zendesk API has rate limits; handle with n8n’s wait nodes or retries.
– **Partial Comment Data:** Always verify if comments are included; otherwise, fetch separately.
– **Timezone Handling:** Use consistent timezones (preferably UTC) for timestamp comparisons.
– **Batch Size:** Limit batch sizes in SplitInBatches to avoid API overload.
– **Error Handling:** Add error workflows to capture API failures or authentication errors.
## How to Adapt or Scale This Workflow
– **Different SLA thresholds:** Adjust the SLA_THRESHOLD_HOURS constant.
– **Additional SLA Metrics:** Track metrics like ticket resolution time or follow-up times by extending the same logic.
– **Integrate More Channels:** Expand to include tickets from other platforms by adding appropriate API nodes.
– **Dashboard Creation:** Pipe data to BI tools or custom dashboards for real-time SLA visualization.
– **User Customizations:** Add options for support managers to modify SLA rules via Google Sheets or webhooks.
## Summary
This guide detailed the creation of an automation workflow using n8n to replicate Zendesk’s Response SLA tracking feature—measuring agent first reply times and notifying teams of SLA breaches. By leveraging Zendesk’s APIs and n8n’s powerful automation capabilities, startups and technical teams can save costs, customize SLA rules, and gain deeper insights into their support performance.
By extending this template, teams can scale SLA tracking across multiple channels and integrate alerts into their preferred communication tools, ensuring customer issues are always prioritized effectively without incurring extra SaaS expenses.
## Bonus Tip
To further optimize, integrate n8n with your ticketing dashboards or include machine learning models for automatic ticket prioritization based on SLA breach risk predictions, improving operational efficiency even more.