Helpdesk KPI API Documentation

Introduction

Welcome to the Helpdesk KPI API! This API allows you to retrieve key performance indicators (KPIs) related to your helpdesk/customer support operations. The API provides aggregated statistics and metrics based on the provided data. The API accepts a request in the form of an array containing objects with the following attributes:

• creation_datetime (Required, string): The date and time (format e.g.: 2023-07-01 12:02:05) when the ticket was created.
• solved_datetime (string) : The date and time (format e.g.: 2023-07-01 12:02:05) when the ticket was solved.
• customer (string): The name or ID of the customer associated with the ticket.
• agent (string): The name or ID of the agent who handled the ticket.
• source (Required, string): The channel or source through which the ticket was received (e.g., email, chat, phone).
• priority (string): The priority level name or ID of the ticket (e.g., high, medium, low).
• first_response_datetime (string): The date and time (format e.g.: 2023-07-01 12:02:05) of the first response to the ticket.
• num_interactions (Required, integer): The total number of interactions for the ticket.
• effective_time (integer): The total time (in seconds) taken to effectively resolve the ticket.
• satisfaction_score (integer): The satisfaction score provided by the customer.

Endpoint

This endpoint allows you to retrieve aggregated helpdesk KPIs.

[POST] https://helpdesk-kpi.p.rapidapi.com/kpi/helpdesk

X-RapidAPI-Host: helpdesk-kpi.p.rapidapi.com
X-RapidAPI-Key: YOUR_API_KEY
Content-Type: application/json

Request Body (Example Data):

[
   {
      "creation_datetime":"2022-01-04 17:21:21",
      "solved_datetime":null,
      "customer":"211",
      "agent":"23",
      "source":"phone",
      "priority":"2",
      "first_response_datetime":null,
      "num_interactions":"2",
      "efective_time":"900",
      "satisfaction_score":null
   },
   {
      "creation_datetime":"2022-03-02 11:42:16",
      "solved_datetime":"2022-03-02 15:58:21",
      "customer":"211",
      "agent":"23",
      "source":"email",
      "priority":"1",
      "first_response_datetime":"2022-03-02 11:42:16",
      "num_interactions":"2",
      "efective_time":"3600",
      "satisfaction_score":null
   },
   {
      "creation_datetime":"2022-03-28 10:46:56",
      "solved_datetime":"2022-03-28 10:59:59",
      "customer":"211",
      "agent":"23",
      "source":"phone",
      "priority":"2",
      "first_response_datetime":null,
      "num_interactions":"2",
      "efective_time":"1800",
      "satisfaction_score":null
   },
   {
      "creation_datetime":"2022-04-07 10:37:06",
      "solved_datetime":"2022-04-07 11:29:04",
      "customer":"211",
      "agent":"16",
      "source":"email",
      "priority":"1",
      "first_response_datetime":"2022-04-07 10:37:06",
      "num_interactions":"2",
      "efective_time":"1800",
      "satisfaction_score":null
   },
   {
      "creation_datetime":"2022-04-08 16:13:00",
      "solved_datetime":"2022-04-08 16:18:34",
      "customer":"211",
      "agent":"23",
      "source":"phone",
      "priority":"2",
      "first_response_datetime":null,
      "num_interactions":"2",
      "efective_time":"1800",
      "satisfaction_score":null
   },
   {
      "creation_datetime":"2022-04-26 14:20:31",
      "solved_datetime":"2022-04-27 16:56:55",
      "customer":"211",
      "agent":"23",
      "source":"email",
      "priority":"1",
      "first_response_datetime":"2022-04-26 14:20:31",
      "num_interactions":"3",
      "efective_time":"1800",
      "satisfaction_score":null
   },
   {
      "creation_datetime":"2022-05-06 16:05:13",
      "solved_datetime":null,
      "customer":"211",
      "agent":"16",
      "source":"phone",
      "priority":"2",
      "first_response_datetime":null,
      "num_interactions":"2",
      "efective_time":"4500",
      "satisfaction_score":null
   },
   {
      "creation_datetime":"2022-05-31 15:29:10",
      "solved_datetime":"2022-05-31 15:48:51",
      "customer":"211",
      "agent":"16",
      "source":"email",
      "priority":"1",
      "first_response_datetime":"2022-05-31 15:29:10",
      "num_interactions":"2",
      "efective_time":"900",
      "satisfaction_score":null
   }
]

Response:

The API will respond with the aggregated KPIs for the provided data.

{
    "status": true,
    "data": {
        "first_contact_time_average": 0,
        "resolution_time_average": 19428,
        "first_contact_solved_count": 7,
        "unsolved_count": 2,
        "solved_count": 6,
        "unanswered_count": 2,
        "processed_count": 8,
        "first_contact_solved_percentage": 0.875,
        "solved_count_percentage": 0.75,
        "unsolved_count_percentage": 0.25,
        "unanswered_count_percentage": 0.25,
        "classification_scores_count": 0,
        "classification_scores_average": 0.0,
        "volume": {
            "created_count": {
                "2022-01-04": 1,
                "2022-03-02": 1,
                "2022-03-28": 1,
                "2022-04-07": 1,
                "2022-04-08": 1,
                "2022-04-26": 1,
                "2022-05-06": 1,
                "2022-05-31": 1,
                "2022-04-27": 0
            },
            "solved_count": {
                "2022-01-04": 0,
                "2022-03-02": 1,
                "2022-03-28": 1,
                "2022-04-07": 1,
                "2022-04-08": 1,
                "2022-04-26": 0,
                "2022-05-06": 0,
                "2022-05-31": 1,
                "2022-04-27": 1
            }
        },
        "volume_hours": {
            "created_count": {
                "10:00-10:59": 2,
                "11:00-11:59": 1,
                "14:00-14:59": 1,
                "15:00-15:59": 1,
                "16:00-16:59": 2,
                "17:00-17:59": 1
            },
            "solved_count": {
                "10:00-10:59": 1,
                "11:00-11:59": 1,
                "14:00-14:59": 0,
                "15:00-15:59": 2,
                "16:00-16:59": 2,
                "17:00-17:59": 0
            }
        },
        "sources": {
            "email": {
                "processed_count": 4,
                "efective_ticket_time_average": 2025
            },
            "phone": {
                "processed_count": 4,
                "efective_ticket_time_average": 1800
            }
        },
        "priorities": {
            "1": {
                "processed_count": 4,
                "efective_ticket_time_average": 2025
            },
            "2": {
                "processed_count": 2,
                "efective_ticket_time_average": 1800
            }
        },
        "agents": {
            "16": {
                "processed_count": 3,
                "first_contact_solved_count": 3,
                "first_contact_time_average": 0,
                "effective_ticket_time_average": 2400,
                "classification_scores_count": 0,
                "classification_scores_average": 0,
                "effective_ticket_time_count": 7200,
                "num_interactions_average": 2.0,
                "net_promoter_score_count": 0,
                "net_promoter_score_average": 0.0,
                "first_contact_solved_percentage": 1.0
            },
            "23": {
                "processed_count": 5,
                "first_contact_solved_count": 4,
                "first_contact_time_average": 0,
                "effective_ticket_time_average": 1980,
                "classification_scores_count": 0,
                "classification_scores_average": 0,
                "effective_ticket_time_count": 9900,
                "num_interactions_average": 2.2,
                "net_promoter_score_count": 0,
                "net_promoter_score_average": 0.0,
                "first_contact_solved_percentage": 0.8
            }
        },
        "unassigned_count": 0,
        "unassigned_count_percentage": 0,
        "customers": {
            "211": {
                "processed_count": 8,
                "unsolved_count": 2,
                "first_contact_solved_count": 7,
                "first_contact_time_average": 0,
                "effective_ticket_time_average": 2137,
                "classification_scores_count": 0,
                "classification_scores_average": 0,
                "effective_ticket_time_count": 17100,
                "unanswered_count": 2,
                "num_interactions_average": 2.125,
                "net_promoter_score_count": 0,
                "net_promoter_score_average": 0,
                "first_contact_solved_percentage": 0.875
            }
        }
    }
}

Response Attributes:

• status (boolean): Indicates if the request was successful.
• data (object): Contains the aggregated helpdesk KPIs.
  • first_contact_time_average (integer): The average time taken for first contact, in seconds.
  • resolution_time_average (integer): The average resolution time, in seconds.
  • first_contact_solved_count (integer): The count of tickets solved on first contact.
  • unsolved_count (integer): The count of unsolved tickets.
  • solved_count (integer): The count of solved tickets.
  • unanswered_count (integer): The count of unanswered tickets.
  • processed_count (integer): The total count of processed tickets.
  • first_contact_solved_percentage (float): The percentage of tickets solved on first contact.
  • solved_count_percentage (float): The percentage of tickets solved.
  • unsolved_count_percentage (float): The percentage of unsolved tickets.
  • unanswered_count_percentage (float): The percentage of unanswered tickets.
  • classification_scores_count (integer): The count of classification scores.
  • classification_scores_average (float): The average classification score.
  • volume (object): Contains volume statistics for created and solved tickets.
    • created_count (integer): Contains the count of created tickets for specific dates.
    • solved_count (integer): Contains the count of solved tickets for specific dates.
  • volume_hours (object): Contains volume statistics based on hours of the day.
    • created_count (integer): Contains the count of created tickets for specific time intervals (hour by hour).
    • solved_count (integer): Contains the count of solved tickets for specific time intervals (hour by hour).
  • sources (object): Contains statistics based on ticket sources.
    • Source ID (string): Contains statistics for each source, where the key is the source’s ID.
      • processed_count (integer): The total count of processed tickets by source.
      • efective_ticket_time_average (integer): The average of efective time of solved tickets, in seconds by source.
  • priorities (object): Contains statistics based on ticket priorities.
    • Priority ID (string): Contains statistics for each priority, where the key is the priority’s ID.
      • processed_count (integer): The total count of processed tickets by priority.
      • efective_ticket_time_average (integer): The average of efective time of solved tickets, in seconds by priority.
  • agents (object): Contains statistics based on agents.
    • Agent ID (string): Contains statistics for each agent, where the key is the agent’s ID.
      • processed_count (integer): The count of tickets processed by the agent.
      • first_contact_solved_count (integer): The count of tickets solved on first contact by the agent.
      • first_contact_time_average (integer): The average time taken for first contact by the agent.
      • effective_ticket_time_average (integer): The average time taken to handle a ticket effectively by the agent.
      • classification_scores_count (integer): The count of classification scores received by the agent.
      • classification_scores_average (float): The average classification score received by the agent.
      • effective_ticket_time_count (integer): The count of effective ticket handling times recorded for the agent.
      • num_interactions_average (float): The average number of interactions per ticket handled by the agent.
      • net_promoter_score_count (integer): The count of Net Promoter Scores received by the agent.
      • net_promoter_score_average (float): The average Net Promoter Score received by the agent.
      • first_contact_solved_percentage (float): The percentage of tickets solved on first contact by the agent.
  • unassigned_count (integer): The count of unassigned tickets.
  • unassigned_count_percentage (float): The percentage of unassigned tickets.
  • customers (object): Contains statistics based on customers.
    • Customer ID (string): Contains statistics for each customer, where the key is the customer’s ID.
      • processed_count (integer): The count of tickets processed for the customer.
      • unsolved_count (integer): The count of unsolved tickets for the customer.
      • first_contact_solved_count (integer): The count of tickets solved on first contact for the customer.
      • first_contact_time_average (integer): The average time taken for first contact for the customer.
      • effective_ticket_time_average (integer): The average time taken to handle a ticket effectively for the customer.
      • classification_scores_count (integer): The count of classification scores received by the customer.
      • classification_scores_average (float): The average classification score received by the customer.
      • effective_ticket_time_count (integer): The count of effective ticket handling times recorded for the customer.
      • unanswered_count (integer): The count of unanswered tickets for the customer.
      • num_interactions_average (float): The average number of interactions per ticket for the customer.
      • net_promoter_score_count (integer): The count of Net Promoter Scores received by the customer.
      • net_promoter_score_average (float): The average Net Promoter Score received by the customer.
      • first_contact_solved_percentage (float): The percentage of tickets solved on first contact for the customer.

Error Handling

If an error occurs during the request, the API will respond with an appropriate error message and status code. If need help, feel free to contact.

Authentication

To use this API, you need to obtain an API key from RapidAPI and include it in the request headers.