How to merge Zendesk tickets?

Merging Tickets in Bulk using the Zendesk API

 

While manual merging of duplicated tickets in Zendesk is an option, it can be time-consuming and error-prone.

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To address these challenges, streamlining the process of merging duplicate tickets can offer a more reliable solution. In this section, we'll discuss a Python script that leverages the Zendesk API to merge tickets in bulk, reducing manual effort and minimizing errors.

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Overview of the Bulk Solution

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The provided Python script automates the merging process by:

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1. Retrieving Open Tickets: Utilizing the Zendesk API’s search endpoint, the script fetches all open tickets. This helps identify potential duplicates that need merging.

2. Grouping Tickets by Requester: The script groups tickets based on the requester_id, identifying those submitted by the same customer.

3. Merging Process: For each group of tickets from the same requester, the script merges them into a single primary ticket. This ensures that all relevant information and communication history are consolidated, making it easier for support agents to manage and respond to customer inquiries.

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Step-by-Step Walkthrough

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1. Setup and Authentication

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The script begins with setting up the necessary configurations, including the Zendesk domain, email, and API token. These credentials are essential for authenticating requests to the Zendesk API.​​

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import requests
import json

# Set up your Zendesk credentials
email_address = 'your_email@example.com'
api_token = 'your_api_token'
subdomain = 'your_subdomain'

base_url = f'https://{subdomain}.zendesk.com/api/v2'

# Set up the headers with authentication
headers = {
    'Authorization': f'Basic {email_address}/token:{api_token}',
    'Content-Type': 'application/json'
}

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​Here, the headers is used to create an authentication object that will be used in all API requests. This method ensures secure access to the Zendesk platform.

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2. Retrieving Open Tickets

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The script defines a function get_open_tickets() to fetch all new and open tickets from Zendesk. It uses the search endpoint with a query to filter tickets based on their status.

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def get_all_open_tickets():
    url = f'{base_url}/search.json'
    params = {
        'query': 'type:ticket status:new status:open',
        'page': 1
    }
    tickets = []
    while True:
        response = requests.get(url, headers=headers, params=params)
        data = response.json()
        tickets.extend(data.get('results', []))
        
        # Check if there is a next page
        if data.get('next_page'):
            params['page'] += 1
        else:
            break
    return tickets

 

This function sends a sequence of GET requests to the Zendesk API, retrieving the list of all new and open tickets, page by page. It returns these tickets as a list of JSON objects.

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3. Grouping Tickets by Requester

 

Next, the script organizes the retrieved tickets by requester_id. This grouping helps in identifying tickets that potentially belong to the same customer.

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# Function to find tickets from the same requester
def group_tickets_by_requester(tickets):
    tickets_by_requester = {}
    for ticket in tickets:
        requester_id = ticket.get('requester_id')
        if requester_id:
            if requester_id not in tickets_by_requester:
                tickets_by_requester[requester_id] = []
            tickets_by_requester[requester_id].append(ticket['id'])
    return tickets_by_requester

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In this segment, the script iterates through the list of open tickets and categorizes them based on the requester_id. The result is a dictionary where each key represents a requester, and the corresponding value is a list of ticket IDs associated with that requester.

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4. Merging Tickets

 

The core functionality of the script is to merge tickets from the same requester. The merge_tickets() function handles this process.

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def merge_tickets(target_ticket_id, ticket_ids_to_merge):
    url = f'{base_url}/tickets/{target_ticket_id}/merge.json'
    data = {
        'ids': ticket_ids_to_merge,
        'source_comment': 'Merging tickets due to same requester',
        'target_comment': f'Combining with tickets {ticket_ids_to_merge}'
    }
    response = requests.post(url, headers=headers, data=json.dumps(data))
    return response.json()

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This function sends a POST request to the Zendesk API, specifying the target ticket ID (the ticket that will retain all merged information) and the source ticket ID(s) (the tickets to be merged into the target ticket). The JSON payload contains the list of ticket IDs to merge and the merging comments.

 

5. Executing the Merging Process

 

Finally, the main section of the script iterates over the grouped tickets and merges them where necessary.

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def main():
    # Step 1: Get all open tickets
    open_tickets = get_open_tickets()

    # Step 2: Group tickets by requester
    tickets_by_requester = group_tickets_by_requester(open_tickets)

    # Step 3: Merge tickets by requester
    for requester_id, ticket_ids in tickets_by_requester.items():
        if len(ticket_ids) > 1:
            # Choose the first ticket as the target and merge others into it
            target_ticket_id = ticket_ids[0]
            ticket_ids_to_merge = ticket_ids[1:]
            merge_response = merge_tickets(target_ticket_id, ticket_ids_to_merge)
            print(f'Merged tickets {ticket_ids_to_merge} into {target_ticket_id}: {merge_response}')

if __name__ == "__main__":
    main()

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In this loop, the script checks if there are multiple tickets for the same requester. If so, it designates the first ticket as the primary and merges the subsequent tickets into it. The print statement provides a log of the merging activity.

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The provided script for merging duplicate tickets in bulk offers a straightforward and efficient solution for consolidating customer issues in Zendesk. However, it does have limitations.

 

One significant drawback is that the merging process is not done in real-time, which means that unmerged tickets can sometimes slip through, allowing different agents to work on the same issue simultaneously. Additionally, the merging criteria used in the script are relatively simple, based solely on the same requester. Many companies require more complex criteria for merging tickets, such as matching multiple ticket fields, using text extraction from ticket comments, or applying different rules for specific subsets of tickets.

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This often means to implement this approach, you need to understand Python or you'll need to pull in an engineer, which many support teams find difficult.

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These challenges underscore the need for a more sophisticated and automated approach — on that provides real-time merging and the ability to apply more complex and flexible criteria.

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