### Introduction
For startups and operations teams using helpdesk solutions like Zendesk, tracking ticket volume by client is critical for workload management, SLA adherence, and billing. Zendesk’s Client Tags feature allows tagging tickets automatically to segment and analyze client interactions, but this comes at an additional cost and often locked in the Zendesk ecosystem.
In this article, we’ll build an automation workflow using n8n that replicates the Client Tags feature. This solution is ideal for startups and automation engineers seeking to reduce SaaS expenses by using open-source tools and customizable workflows. We’ll integrate Zendesk’s API (or your existing helpdesk API), n8n’s powerful workflow engine, and Google Sheets for analytics and reporting.
### What Problem Does This Solve and Who Benefits?
– **Problem:** Automatically tag support tickets with client-specific labels to categorize and analyze ticket volume without incurring extra fees.
– **Who Benefits:** Customer support managers, automation engineers, CTOs, and finance teams who want granular client ticket data while reducing tool costs.
### Tools and Services Integrated
– **n8n:** Open-source workflow automation platform.
– **Zendesk (or any helpdesk system with API):** Source of tickets.
– **Google Sheets:** Used as a flexible, accessible reporting and tracking tool.
—
## Step-by-Step Technical Tutorial
### Prerequisites
– n8n instance set up (self-hosted or cloud).
– Zendesk account with API access enabled.
– Google account with a Google Sheet created for tracking.
– API tokens and credentials for Zendesk and Google Sheets.
—
### 1. Define the Automation Goal
Automatically poll Zendesk for new or updated tickets, extract client information, tag tickets with the client name as metadata via API or update a field, and log aggregated ticket counts per client in Google Sheets.
### 2. Create the Workflow in n8n
#### Node 1: Zendesk Trigger or Poll
– Since Zendesk’s webhook mechanism requires complex setup, we’ll use a **Polling** approach:
– Use the **HTTP Request** node in n8n to call Zendesk’s Tickets API endpoint `/api/v2/incremental/tickets.json` to get recently created or updated tickets.
– We will store the last timestamp processed in n8n to poll incrementally.
##### Configuration:
– Set Request Method to GET.
– URL: `https://yourdomain.zendesk.com/api/v2/incremental/tickets.json?start_time={{$json[“last_processed_time”]}}`
– Authentication: Zendesk API Token or Basic Auth with email/token.
#### Handling Pagination:
– Zendesk incremental API supports pagination with `end_of_stream` and `next_page`.
– Use the `next_page` URL in a Loop until `end_of_stream` is `true`.
#### Node 2: Extract Client Info
– Use a **Function** node to parse each ticket and extract the client identifier, typically from `requester_id` or a custom field such as `client_name`.
– Retrieve additional client details via Zendesk Users API if needed.
Example function snippet:
“`js
return items.map(item => {
const ticket = item.json;
return {
json: {
ticket_id: ticket.id,
client_id: ticket.requester_id,
created_at: ticket.created_at
}
};
});
“`
#### Node 3: Retrieve Client Details (Optional)
– Use **HTTP Request** to get client names by calling `/api/v2/users/{{client_id}}.json`.
– Map client names back to tickets.
#### Node 4: Tag Ticket with Client Name
– Use the **HTTP Request** node to update the ticket with a tag containing the client name.
– Zendesk API endpoint: `/api/v2/tickets/{{ticket_id}}.json`
– Method: PUT
– Body:
“`json
{
“ticket”: {
“tags”: [“client-{{client_name}}”]
}
}
“`
*Note:* Zendesk doesn’t allow removing all tags at once via API; take care not to overwrite existing tags unintentionally. Instead, retrieve existing tags and append.
#### Node 5: Aggregate Ticket Counts Per Client
– Use a **Code** or **Function** node to aggregate tickets by client in the current batch.
Example:
“`js
const counts = {};
items.forEach(item => {
const client = item.json.client_name;
counts[client] = (counts[client] || 0) + 1;
});
return Object.entries(counts).map(([client, count]) => {
return { json: { client, count } };
});
“`
#### Node 6: Update Google Sheets
– Use the **Google Sheets** node to append or update rows with client names and their ticket counts.
– Structure Sheet as:
– Client Name | Ticket Count | Last Updated
Configure the node:
– Authentication with Google.
– Sheet ID and Sheet Name.
– Use “Append Row” action or “Update Row” if client already exists.
#### Node 7: Store Last Processed Time
– Maintain state using **Set** or **Storage** nodes to save the last ticket creation or update timestamp.
– This timestamp feeds back into the Zendesk API query for incremental fetching.
—
## Common Errors & Tips
– **API Rate Limits:** Zendesk imposes rate limits, so add delays or error handling with retries.
– **Tag Overwrite:** Always get existing tags before updating tickets to avoid removing essential tags unintentionally.
– **Authentication Issues:** Ensure API tokens are current and have correct permissions.
– **Pagination Handling:** Failing to correctly loop over `next_page` results in missed tickets.
– **Google Sheets Quotas:** Batch updates when possible and avoid excessive API calls.
—
## How to Adapt or Scale This Workflow
– **Add More Data Sources:** Integrate other helpdesk tools or CRMs to consolidate ticket volumes.
– **Real-Time Updates:** Replace polling with Zendesk webhooks to trigger n8n workflows instantly.
– **Dashboard Integration:** Export aggregated data from Google Sheets to BI tools for visualization.
– **Multi-Team Tagging:** Extend tagging logic to include product lines, support tiers, or priority levels.
—
### Summary
This guide outlined how to replace Zendesk’s Client Tags feature with a custom n8n automation workflow. Using Zendesk API, n8n’s nodes, and Google Sheets, startup teams can track ticket volume by client efficiently while avoiding additional SaaS license costs. This modular workflow provides flexibility, scalability, and cost savings.
### Bonus Tip
Leverage n8n’s built-in credential management and environment variables to securely store API keys and make your workflows more portable and secure. Additionally, consider containerizing your n8n instance for robust, scalable deployment.