A help desk helps to manage customer queries with ease where this blog states the latest help desk statistics that will help to understand everything that you need to know in 2025

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Event log concerning the ticketing management process of the Help desk of an Italian software company

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About Dataset

Check out my new Dataset:

Multilingual Support Tickets

Dataset Description:

The Email Ticket Text Multi-Language Classification dataset offers an extensive and meticulously organized collection of email tickets written in multiple languages, including German, English, Spanish, and French. This dataset is specifically designed to enhance natural language processing (NLP), machine learning, and customer support optimization efforts. It provides a rich resource for developing and testing models that classify and prioritize customer support tickets. The dataset's structure and comprehensiveness make it ideal for both academic research and practical applications in improving customer service efficiency.

Dataset Features:

1. Queue:

   • Description: Specifies the department to which the email ticket is categorized. This helps in routing the ticket to the appropriate support team for resolution.
   • Values:
     • Software: Issues related to software applications, systems, bugs, and user errors.
     • Hardware: Problems related to physical devices, hardware malfunctions, installation issues, and maintenance requests.
     • Accounting: Inquiries and issues concerning financial transactions, billing, account discrepancies, and other accounting-related matters.

2. Priority:

   • Description: Indicates the urgency and importance of the issue. Helps in managing the workflow by prioritizing tickets that need immediate attention.
   • Values:
     • 1 (Low): Non-urgent issues that do not require immediate attention. Examples: General inquiries, minor inconveniences, routine updates, and feature requests.
     • 2 (Medium): Moderately urgent issues that need timely resolution but are not critical. Examples: Performance issues, intermittent errors, and user questions requiring detailed responses.
     • 3 (Critical): Urgent issues that require immediate attention and quick resolution. Examples: System outages, security breaches, data loss, and major malfunctions.

3. Software Used:

   • Description: Specifies the software application involved in the issue. Useful for categorizing and analyzing software-related problems.
   • Values: Examples include specific software names like "Arbitrum," "Adobe Premiere Pro 2021," "Excel," etc.

4. Hardware Used:

   • Description: Specifies the hardware device involved in the issue. Helps in identifying and troubleshooting hardware-related problems.
   • Values: Examples include specific hardware names like "Wireless Mouse," "IP PBX," "SFX-Netzteil," etc.

5. Accounting Category:

   • Description: Specifies the sub-category within accounting for more granular classification of financial inquiries.
   • Values: Examples include categories like "Customer Inquiries::Technical Support," "Employee Inquiries::Technical," "Customer Inquiries::Cancellations," etc.

6. Language:

   • Description: Indicates the language in which the email is written. Useful for language-specific NLP models and multilingual support analysis.
   • Values: Examples include "en" (English), "de" (German), "es" (Spanish), "fr" (French).

7. Subject:

   • Description: Provides a brief overview of the email content, aiding in quick scanning and initial categorization.
   • Values: Examples include subject lines like "Wireless Mouse suddenly stops working," "Problème de connexions IP PBX," "Problem mit meinem SFX-Netzteil," etc.

8. Text:

   • Description: Contains the full email text for in-depth analysis. Crucial for training NLP models to understand and classify complex and varied text inputs.
   • Values: Full content of the emails, describing the issue in detail.

Usage Instructions:

To access the full dataset, please contact me at dataset@softoft.de. This page only provides a preview with 200 randomly selected rows from the complete dataset, which comprises over 8,000 rows. More information about me and my company can be found at Softoft. For detailed information about this dataset, visit the dataset website.

Key Features:

• Email Subject: Provides a brief overview of the email content, aiding in quick scanning and initial categorization.
• Email Texts: Contains the full email text for in-depth analysis, crucial for training NLP models.
• Department Classification: Categorizes emails into Software, Hardware, and Accounting departments, enabling specialized handling.
• Priority Levels: Ranks emails based on urgency from low to critical, ensuring that critical issues are addressed promptly.

Use Cases:

1. Text Classification:
   • Tra...

This dataset contains events from a ticketing management process of the help desk of an Italian software company. The process consists of 9 activities, and all cases start with the insertion of a new ticket into the ticketing management system. Each case ends when the issue is resolved and the ticket is closed. This log contains 3804 process instances (a.k.a "cases") and 13710 events

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Technical Support Outsourcing Market Size 2024-2028

The technical support outsourcing market size is valued to increase USD 17.3 billion, at a CAGR of 7.99% from 2023 to 2028. The increasing need for cost-effective solutions to improve efficiency will drive the technical support outsourcing market.

Major Market Trends & Insights

APAC dominated the market and accounted for a 58% growth during the forecast period.
By Type - Help Desk segment was valued at USD 14.70 billion in 2022
By Business Segment - Large enterprises segment accounted for the largest market revenue share in 2022

Market Size & Forecast

Market Opportunities: USD 103.00 billion
Market Future Opportunities: USD 17.30 billion
CAGR : 7.99%
APAC: Largest market in 2022

Market Summary

The market is a dynamic and ever-evolving industry that continues to shape the business landscape. This market encompasses the outsourcing of technical support services, primarily driven by the increasing need for cost-effective solutions to enhance efficiency and reduce operational costs. Core technologies and applications, such as artificial intelligence (AI) and machine learning, are revolutionizing technical support, with the emergence of chatbots and virtual assistants becoming increasingly popular. However, outsourcing technical support can also pose challenges, including potential compromises to the quality of service.
According to recent studies, the global market share of Business Process Outsourcing (BPO) in technical support is projected to reach 55% by 2025, underscoring the significant impact of this trend. Despite these opportunities and challenges, the market remains an essential component of modern business strategies, providing companies with the flexibility to focus on their core competencies while ensuring high-quality technical support for their customers.

What will be the Size of the Technical Support Outsourcing Market during the forecast period?

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How is the Technical Support Outsourcing Market Segmented and what are the key trends of market segmentation?

The technical support outsourcing industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Type

  Help Desk
  Call Center Services
  Managed Technical Support


Business Segment

  Large enterprises
  SMEs


End-User

  Banking, Financial Services, and Insurance (BFSI)
  Healthcare
  Retail & E-commerce


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  Middle East and Africa

    Egypt
    KSA
    Oman
    UAE


  APAC

    China
    India
    Japan


  South America

    Argentina
    Brazil


  Rest of World (ROW)

By Type Insights

The help desk segment is estimated to witness significant growth during the forecast period.

The market is a significant and continually evolving sector, encompassing various services delivered through help desks. These services cater to diverse needs, including customer support, IT help desk support, product support, and network operations center (NOC) services. Customer support addresses end-user queries and issues, primarily through phone, email, or chat. IT help desk support focuses on troubleshooting technical problems for employees within organizations, addressing hardware, software, and network issues. Product support assists users in effectively utilizing products, often providing detailed technical guidance. NOC services manage and monitor network infrastructure, ensuring optimal performance and addressing network-related issues promptly.

Key market trends include the integration of advanced technologies such as artificial intelligence (AI) and machine learning (ML) into support systems, enhancing efficiency and improving first call resolution rates. Remote desktop support and managed service providers are increasingly popular, allowing organizations to outsource support functions and focus on core business activities. Customer satisfaction scores and service level agreements (SLAs) are crucial performance metrics, with an average handle time of 5 minutes and a first call resolution rate of 70%. Compliance certifications, such as ISO 27001 and ITIL, ensure adherence to industry standards and best practices. Training materials development and end-user training programs are essential for maintaining high-performing support teams.

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The Help Desk segment was valued at USD 14.70 billion in 2018 and showed a gradual increase during the forecast period.

Help desk software, remote monitoring tools, and cloud-based support tools facilitate efficient and effective support delivery. company management, system adminis

Australian and New Zealand journal of statistics Acceptance Rate - ResearchHelpDesk - The Australian & New Zealand Journal of Statistics is an international journal managed jointly by the Statistical Society of Australia and the New Zealand Statistical Association. Its purpose is to report significant and novel contributions in statistics, ranging across articles on statistical theory, methodology, applications and computing. The journal has a particular focus on statistical techniques that can be readily applied to real-world problems, and on application papers with an Australasian emphasis. Outstanding articles submitted to the journal may be selected as Discussion Papers, to be read at a meeting of either the Statistical Society of Australia or the New Zealand Statistical Association. The main body of the journal is divided into three sections. The Theory and Methods Section publishes papers containing original contributions to the theory and methodology of statistics, econometrics and probability, and seeks papers motivated by a real problem and which demonstrate the proposed theory or methodology in that situation. There is a strong preference for papers motivated by, and illustrated with, real data. The Applications Section publishes papers demonstrating applications of statistical techniques to problems faced by users of statistics in the sciences, government and industry. A particular focus is the application of newly developed statistical methodology to real data and the demonstration of better use of established statistical methodology in an area of application. It seeks to aid teachers of statistics by placing statistical methods in context. The Statistical Computing Section publishes papers containing new algorithms, code snippets, or software descriptions (for open source software only) which enhance the field through the application of computing. Preference is given to papers featuring publically available code and/or data, and to those motivated by statistical methods for practical problems. In addition, suitable review papers and articles of historical and general interest will be considered. The journal also publishes book reviews on a regular basis. Abstracting and Indexing Information Academic Search (EBSCO Publishing) Academic Search Alumni Edition (EBSCO Publishing) Academic Search Elite (EBSCO Publishing) Academic Search Premier (EBSCO Publishing) CompuMath Citation Index (Clarivate Analytics) Current Index to Statistics (ASA/IMS) Journal Citation Reports/Science Edition (Clarivate Analytics) Mathematical Reviews/MathSciNet/Current Mathematical Publications (AMS) RePEc: Research Papers in Economics Science Citation Index Expanded (Clarivate Analytics) SCOPUS (Elsevier) Statistical Theory & Method Abstracts (Zentralblatt MATH) ZBMATH (Zentralblatt MATH)

The Enterprise Help Desk Software market is booming, projected to reach $15 Billion in 2025, with a CAGR of 12% through 2033. Discover key trends, leading vendors (Salesforce, Zendesk, Freshworks), regional insights, and growth drivers in this comprehensive market analysis.

Australian and New Zealand journal of statistics Impact Factor 2024-2025 - ResearchHelpDesk - The Australian & New Zealand Journal of Statistics is an international journal managed jointly by the Statistical Society of Australia and the New Zealand Statistical Association. Its purpose is to report significant and novel contributions in statistics, ranging across articles on statistical theory, methodology, applications and computing. The journal has a particular focus on statistical techniques that can be readily applied to real-world problems, and on application papers with an Australasian emphasis. Outstanding articles submitted to the journal may be selected as Discussion Papers, to be read at a meeting of either the Statistical Society of Australia or the New Zealand Statistical Association. The main body of the journal is divided into three sections. The Theory and Methods Section publishes papers containing original contributions to the theory and methodology of statistics, econometrics and probability, and seeks papers motivated by a real problem and which demonstrate the proposed theory or methodology in that situation. There is a strong preference for papers motivated by, and illustrated with, real data. The Applications Section publishes papers demonstrating applications of statistical techniques to problems faced by users of statistics in the sciences, government and industry. A particular focus is the application of newly developed statistical methodology to real data and the demonstration of better use of established statistical methodology in an area of application. It seeks to aid teachers of statistics by placing statistical methods in context. The Statistical Computing Section publishes papers containing new algorithms, code snippets, or software descriptions (for open source software only) which enhance the field through the application of computing. Preference is given to papers featuring publically available code and/or data, and to those motivated by statistical methods for practical problems. In addition, suitable review papers and articles of historical and general interest will be considered. The journal also publishes book reviews on a regular basis. Abstracting and Indexing Information Academic Search (EBSCO Publishing) Academic Search Alumni Edition (EBSCO Publishing) Academic Search Elite (EBSCO Publishing) Academic Search Premier (EBSCO Publishing) CompuMath Citation Index (Clarivate Analytics) Current Index to Statistics (ASA/IMS) Journal Citation Reports/Science Edition (Clarivate Analytics) Mathematical Reviews/MathSciNet/Current Mathematical Publications (AMS) RePEc: Research Papers in Economics Science Citation Index Expanded (Clarivate Analytics) SCOPUS (Elsevier) Statistical Theory & Method Abstracts (Zentralblatt MATH) ZBMATH (Zentralblatt MATH)

Explore the booming Session Support Software market, projected at $15,000M in 2025 with a 12% CAGR. Discover key drivers like cloud adoption and enhanced customer engagement, vital for large enterprises and SMEs.