全球电信分析市场的应用、组件、地区和预测

电信分析市场规模与预测

2024 年电信分析市场规模价值 50.6 亿美元，预计到 2031 年将达到 146.4 亿美元，2024 年至 2031 年的复合年增长率为 14.20%。

通讯分析是一个涉及使用数据分析和先进技术来提高通讯业决策和营运效率的领域。

它涉及电讯网路和服务产生的大量数据的收集、处理和解释。

网路最佳化可协助通讯业者监控和提高网路效能、管理流量负载并确保提供最佳服务。

实现预测性维护，减少停机时间并提高网路基础设施的可靠性。

电信分析在客户体验管理中也发挥关键作用：分析客户资料和行为使通讯业者能够个人化服务产品并更有效地进行行销宣传活动，从而提高客户满意度和客户维繫。

电信分析有助于收益管理和诈欺检测，帮助识别异常模式和潜在的收益洩漏并防止财务损失。

儘管通讯分析有许多好处，但它也面临着资料隐私和安全方面的挑战。

为了防止违规和滥用，对客户资料的处理和储存有严格的规定。

为了减轻这些风险并确保遵守法律标准，实施强有力的安全措施至关重要。

全球电信分析市场动态

影响全球通讯分析市场的关键市场动态包括：

关键市场驱动因素

数据产生不断增加：行动装置、物联网 (IoT) 设备和网路流量产生的数据呈指数级增长，推动了对通讯分析解决方案的需求，以管理、分析和洞察这些海量数据。

提升客户体验的需求：通讯业者越来越重视改善和个人化客户体验。分析有助于了解客户的行为、偏好和趋势，使提供者能够客製化服务以提高客户满意度。

网路优化需求：随着通讯网路变得越来越复杂，迫切需要进阶分析来优化网路效能、管理流量和有效利用资源，包括预测性维护和即时网路监控。

收益保障与诈骗侦测：电信分析在识别和减少收益流失和诈欺方面发挥关键作用。透过分析使用模式和交易数据，电信业者可以侦测异常情况并防止财务损失。

法规遵循：随着资料隐私和保护方面的监管要求不断增加，必须使用分析来确保遵守法律标准并保护敏感的客户资讯。

技术进步：人工智慧 (AI)、机器学习和巨量资料技术的进步正在推动通讯分析领域的创新，从而实现更先进的数据分析和洞察。

主要挑战

资料隐私和安全：随着越来越多的敏感客户资料被分析，确保资料隐私和安全至关重要。通讯业者必须遵守严格的资料保护条例，防止未授权存取和资料外洩。

资料整合：整合来自网路流量、客户互​​动、计费系统等各种来源的资料非常复杂。无缝整合不同的资料来源以进行准确的分析是一项技术挑战。

扩充性：随着通讯网路和资料量的成长，扩展分析解决方案以处理大型资料集和即时处理而不影响效能成为一项挑战，需要强大的基础设施和先进的技术。

技能短缺：通讯分析、资料科学和机器学习领域的专业技能人才供不应求。吸引和留住具备所需技能的人才是通讯业者面临的一大挑战。

高成本：高阶分析解决方案的实施和维护成本很高，涉及技术基础设施、软体和专业人员的投资，这对某些组织来说可能是一个障碍。

分析复杂性：分析大量数据以获得有意义的见解需要复杂的演算法和模型，这可能会导致确保准确性和相关性方面的挑战。

主要趋势

人工智慧和机器学习的采用：人工智慧和机器学习技术越来越多地被融入通讯分析中，以增强预测分析、自动化流程并提供对客户行为和网路性能的更深入的洞察。

即时分析：为了实现即时决策并提升客户体验，即时数据处理和分析日益受到重视。通讯业者正在投资各种技术，以即时监控和回应网路问题及客户需求。

巨量资料分析：随着电信业者寻求利用来自各种来源的大量数据，巨量资料分析的使用正在增长，这有助于获得可行的见解，优化网路运营并个性化客户互动。

整合物联网分析：随着物联网 (IoT) 设备的普及，通讯公司正在采用物联网分析来管理和分析来自连接设备的数据，以改善服务交付并创造新的收益来源。

云端基础的分析解决方案：云端基础的分析解决方案因其扩充性、灵活性和成本效益而日益普及。通讯业者正在转向云端平台来处理大量资料集和复杂的分析任务。

专注于诈骗侦测：电讯公司越来越多地使用分析技术来侦测和预防诈欺。先进的分析解决方案可以帮助识别可疑活动，减少收益流失，并加强安全措施。

目录

第一章 全球电信分析市场简介

• 市场概况
• 调查范围
• 先决条件

第二章执行摘要

第三章：已验证的市场研究调查方法

• 资料探勘
• 验证
• 第一手资料
• 资料来源列表

第四章：全球电信分析市场展望

• 概述
• 市场动态
  • 驱动程式
  • 阻碍因素
  • 机会
• 波特五力模型
• 价值链分析

第五章：全球电信分析市场（按应用）

• 概述
• 销售和行销管理
• 风险与合规管理
• 网管
• 客户管理
• 其他的

第六章 全球通讯分析市场（按组件）

• 概述
• 软体
• 服务

7. 全球电信分析市场（按地区）

• 概述
• 北美洲
  • 美国
  • 加拿大
  • 墨西哥
• 欧洲
  • 德国
  • 英国
  • 法国
  • 其他欧洲国家
• 亚太地区
  • 中国
  • 日本
  • 印度
  • 其他亚太地区
• 世界其他地区
  • 拉丁美洲
  • 中东和非洲

第八章：全球通讯分析市场的竞争格局

• 概述
• 各公司市场排名
• 主要发展策略

第九章：公司简介

• Teradata
• SAS Institute
• Adobe
• SAP
• Oracle
• IBM
• Cisco
• Micro Focus
• TIBCO
• MicroStrategy

第十章：重大进展

• 产品发布/开发
• 併购
• 业务扩展
• 伙伴关係和联盟

第十一章 附录

• 相关调查

Telecom Analytics Market Size And Forecast

Telecom Analytics Market size was valued at USD 5.06 Billion in 2024 and is projected to reach USD 14.64 Billion by 2031, growing at a CAGR of 14.20% from 2024 to 2031.

Telecom analytics is a field involving the use of data analysis and advanced technologies to improve decision-making and operational efficiency in the telecommunications industry.

It encompasses the collection, processing, and interpretation of vast amounts of data generated by telecom networks and services.

In network optimization, where it helps telecom operators monitor and enhance network performance, manage traffic loads, and ensure optimal service delivery.

It enables predictive maintenance, reducing downtime and improving the reliability of network infrastructure.

Telecom analytics also plays a crucial role in customer experience management. By analyzing customer data and behavior, telecom companies can personalize service offerings, target marketing campaigns more effectively, and enhance customer satisfaction and retention.

The telecom analytics aids in revenue management and fraud detection. It helps in identifying unusual patterns and potential revenue leakage, thus safeguarding against financial losses.

Despite its benefits, telecom analytics involves challenges related to data privacy and security.

Strict regulations govern the handling and storage of customer data to protect against breaches and misuse.

Implementing robust security measures is essential to mitigate these risks and ensure compliance with legal standards.

Global Telecom Analytics Market Dynamics

The key market dynamics that are shaping the global telecom analytics Market include:

Key Market Drivers

Increased Data Generation: The exponential growth in data generated from mobile devices, Internet of Things (IoT) devices, and network traffic drives the demand for telecom analytics solutions to manage, analyze, and derive insights from this vast amount of data.

Demand for Enhanced Customer Experience: Telecom companies are increasingly focusing on improving customer experience and personalization. Analytics help in understanding customer behavior, preferences, and trends, enabling providers to offer tailored services and improve customer satisfaction.

Need for Network Optimization: With the growing complexity of telecom networks, there is a pressing need for advanced analytics to optimize network performance, manage traffic, and ensure efficient resource utilization. This includes predictive maintenance and real-time network monitoring.

Revenue Assurance and Fraud Detection: Telecom analytics play a critical role in identifying and mitigating revenue leakage and fraudulent activities. By analyzing usage patterns and transaction data, telecom companies can detect anomalies and prevent financial losses.

Regulatory Compliance: Increasing regulatory requirements around data privacy and protection necessitate the use of analytics to ensure compliance with legal standards and to safeguard sensitive customer information.

Technological Advancements: Advances in artificial intelligence (AI), machine learning, and big data technologies are driving innovation in telecom analytics, enabling more sophisticated data analysis and insights.

Key Challenges

Data Privacy and Security: With the increasing volume of sensitive customer data being analyzed, ensuring data privacy and security is a significant challenge. Telecom companies must comply with stringent data protection regulations and prevent unauthorized access and data breaches.

Data Integration: Integrating data from various sources, such as network traffic, customer interactions, and billing systems, can be complex. Ensuring that disparate data sources are seamlessly integrated for accurate analysis poses a technical challenge.

Scalability: As telecom networks and data volumes grow, scaling analytics solutions to handle large datasets and real-time processing without compromising performance can be challenging. This requires robust infrastructure and advanced technologies.

Skill Shortage: The demand for skilled professionals with expertise in telecom analytics, data science, and machine learning exceeds supply. Finding and retaining talent with the necessary skills is a significant challenge for telecom companies.

High Costs: Implementing and maintaining advanced analytics solutions can be costly. This includes investing in technology infrastructure, software, and specialized personnel, which can be a barrier for some organizations.

Complexity of Analysis: Analyzing large volumes of data to extract meaningful insights requires sophisticated algorithms and models. The complexity of these analyses can lead to challenges in ensuring accuracy and relevance.

Key Trends

Adoption of Artificial Intelligence and Machine Learning: AI and ML technologies are increasingly being integrated into telecom analytics to enhance predictive analytics, automate processes, and provide deeper insights into customer behavior and network performance.

Real-Time Analytics: There is a growing emphasis on real-time data processing and analytics to enable immediate decision-making and enhance customer experience. Telecom companies are investing in technologies that allow them to monitor and respond to network issues and customer needs in real-time.

Big Data Analytics: The use of big data analytics is expanding as telecom companies seek to leverage large volumes of data generated from various sources. This helps in deriving actionable insights, optimizing network operations, and personalizing customer interactions.

Integration of IoT Analytics: As the Internet of Things (IoT) devices proliferate, telecom companies are incorporating IoT analytics to manage and analyze data from connected devices, improve service offerings, and create new revenue streams.

Cloud-Based Analytics Solutions: The adoption of cloud-based analytics solutions is on the rise due to their scalability, flexibility, and cost-effectiveness. Telecom companies are moving to cloud platforms to handle large datasets and complex analytics tasks.

Focus on Fraud Detection: Telecom companies are increasingly using analytics to detect and prevent fraud. Advanced analytics solutions help in identifying suspicious activities, reducing revenue leakage, and enhancing security measures.

Global Telecom Analytics Market Regional Analysis

Here is a more detailed regional analysis of the global telecom analytics Market:

North America:

North America is significantly dominating the Global Telecom Analytics Market and is expected to maintain its lead throughout the forecast period.

The North American region is experiencing robust growth in telecom analytics due to the region's advanced technological infrastructure and high adoption of digital transformation initiatives across industries.

Telecom companies in North America are increasingly leveraging analytics to optimize network performance, enhance customer experience, and drive operational efficiencies.

This is driven by the growing volume of data and the need for real-time insights to stay competitive in the market.

Significant investments are being made in advanced technologies like artificial intelligence (AI), machine learning (ML), and big data analytics.

These technologies are pivotal in enabling predictive analytics, automating processes, and deriving actionable insights for strategic decision-making.

North American telecom operators are also focusing on improving customer experience through personalized services and targeted marketing strategies.

The region is witnessing an increased adoption of cloud-based analytics solutions due to their scalability and cost-effectiveness.

This trend aligns with the broader shift towards cloud computing and digital transformation.

Regulatory frameworks in North America are supporting the growth of telecom analytics by providing clear guidelines for data privacy and security.

This regulatory environment helps build trust and ensures compliance while leveraging analytics for business growth.

Telecom companies are investing in technologies that can detect and prevent fraudulent activities, thereby safeguarding their revenue streams.

Asia Pacific:

Asia Pacific is anticipated to be the fastest-growing region in the Global Telecom Analytics Market during the forecast period.

The region's rapid economic growth, large and diverse telecom market, and increasing digitalization are major drivers of telecom analytics adoption.

Asia Pacific's expanding middle class and rising smartphone penetration significantly contribute to the growing volume of telecom data that needs to be analyzed.

Telecom operators in the region are investing heavily in advanced analytics to enhance network performance, customer experience, and operational efficiency.

The deployment of big data analytics, AI, and machine learning is helping manage network traffic, optimize resource allocation, and develop targeted marketing strategies.

The surge in demand for digital services and the expansion of 4G and 5G networks are driving the need for robust analytics solutions, ensuring network reliability and high-quality services.

Government support, cloud-based solutions, and competitive market dynamics further drive growth.

Emerging technologies like edge computing and real-time analytics are set to shape the future, addressing the growing demand for instantaneous insights and maintaining competitive advantage amidst geopolitical and trade influences.

The competitive landscape in Asia Pacific is characterized by continuous innovation and investment, as companies strive to stay ahead in a dynamic market environment.

Global Telecom Analytics Market: Segmentation Analysis

The Global Telecom Analytics Market is segmented based on Application, Component, And Geography.

Telecom Analytics Market, By Application

Sales and Marketing Management

Risk and Compliance Management

Network Management

Customer Management

Based on the Application, the Global Telecom Analytics Market is segmented into Sales and Marketing Management, Risk and Compliance Management, Network Management, and Customer Management. Network Management is experiencing growth in the Global Telecom Analytics Market owing to the increasing complexity of telecom networks and the need for real-time data analytics to ensure network performance and reliability. The demand for advanced analytics tools in this segment is driven by the need to optimize network operations, reduce downtime, and improve service quality.

Telecom Analytics Market, By Component

Software

Services

Based on Component Category, the Global Telecom Analytics Market is segmented into Software and Services. The Software segment is experiencing significant growth in the Global Telecom Analytics Market owing to the increasing adoption of advanced analytics solutions by telecom operators. These software solutions, including real-time analytics, predictive modeling, and data visualization tools, help in optimizing network performance, improving customer experience, and driving operational efficiency. The continuous advancements in software technologies and the integration of artificial intelligence and machine learning are further propelling the demand in this segment.

Telecom Analytics Market, By Geography

North America

Europe

Asia Pacific

Rest of the world

Based on Geography, the Global Telecom Analytics Market is segmented into North America, Europe, Asia Pacific, and the Rest of the World. North America dominates the Global Telecom Analytics Market owing to its advanced telecom infrastructure and high adoption of innovative technologies. The presence of major telecom operators and technology companies in the region drives significant investments in analytics solutions to enhance operational efficiency, customer experience, and network management. The region's focus on digital transformation and big data analytics further supports its leading position.

Key Players

The "Global Telecom Analytics Market" study report provides valuable insight with an emphasis on the global market. The major players in the market are Accenture plc, Adobe, Inc., Cisco Systems, Inc., Dell Technologies, Inc., International Business Machines Corporation, Oracle Corporation, SAP SE, SAS Institute, Sisense, Inc., Tableau Software (Salesforce.com Inc.), Teradata Corporation, TIBCO Software, Inc. This section offers in-depth analysis through a company overview, position analysis, the regional and industrial footprint of the company, and the ACE matrix for insightful competitive analysis. The section also provides an exhaustive analysis of the financial performances of mentioned players in the given market.

Our market analysis also entails a section solely dedicated to such major players wherein our analysts provide an insight into the financial statements of all the major players, along with its product benchmarking and SWOT analysis. The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.

Global Telecom Analytics Market Key Developments

• In February 2023, Bharti Airtel announced plans to collaborate with NVIDIA on an AI-based solution to enhance the customer experience for all inbound calls to its contact center. The corporation utilized an automatic speech recognition algorithm on 84% of the calls received at its contact centers. This initiative was aimed at identifying areas for improvement in agent interactions with consumers, ultimately resulting in a better customer experience.
• In March 2023, IBM Corporation announced that it provide Telecom Egypt (TE) with intelligent automation software to support the establishment of a unified solution for all its operations support systems (OSS) across mobile, fixed, and core networks. Telecom Egypt used IBM Cloud Pak for Watson AIOps running on RedHat OpenShift to implement an IBM Robotic Process Automation (RPA) solution. This solution provided TE with a comprehensive view of its entire IT environment, enabling faster innovation, reduced operating expenses, and shorter timeframes for troubleshooting and resolving network-related events.

TABLE OF CONTENTS

1 INTRODUCTION OF GLOBAL TELECOM ANALYTICS MARKET

• 1.1 Overview of the Market
• 1.2 Scope of Report
• 1.3 Assumptions

2 EXECUTIVE SUMMARY

3 RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH

• 3.1 Data Mining
• 3.2 Validation
• 3.3 Primary Interviews
• 3.4 List of Data Sources

4 GLOBAL TELECOM ANALYTICS MARKET OUTLOOK

• 4.1 Overview
• 4.2 Market Dynamics
  • 4.2.1 Drivers
  • 4.2.2 Restraints
  • 4.2.3 Opportunities
• 4.3 Porters Five Force Model
• 4.4 Value Chain Analysis

5 GLOBAL TELECOM ANALYTICS MARKET, BY APPLICATION

• 5.1 Overview
• 5.2 Sales and Marketing Management
• 5.3 Risk and Compliance Management
• 5.4 Network Management
• 5.5 Customer Management
• 5.6 Others

6 GLOBAL TELECOM ANALYTICS MARKET, BY COMPONENT

• 6.1 Overview
• 6.2 Software
• 6.3 Services

7 GLOBAL TELECOM ANALYTICS MARKET, BY GEOGRAPHY

• 7.1 Overview
• 7.2 North America
  • 7.2.1 U.S.
  • 7.2.2 Canada
  • 7.2.3 Mexico
• 7.3 Europe
  • 7.3.1 Germany
  • 7.3.2 U.K.
  • 7.3.3 France
  • 7.3.4 Rest of Europe
• 7.4 Asia Pacific
  • 7.4.1 China
  • 7.4.2 Japan
  • 7.4.3 India
  • 7.4.4 Rest of Asia Pacific
• 7.5 Rest of the World
  • 7.5.1 Latin America
  • 7.5.2 Middle East & Africa

8 GLOBAL TELECOM ANALYTICS MARKET COMPETITIVE LANDSCAPE

• 8.1 Overview
• 8.2 Company Market Ranking
• 8.3 Key Development Strategies

9 COMPANY PROFILES

• 9.1 Teradata
  • 9.1.1 Overview
  • 9.1.2 Financial Performance
  • 9.1.3 Product Outlook
  • 9.1.4 Key Developments
• 9.2 SAS Institute
  • 9.2.1 Overview
  • 9.2.2 Financial Performance
  • 9.2.3 Product Outlook
  • 9.2.4 Key Developments
• 9.3 Adobe
  • 9.3.1 Overview
  • 9.3.2 Financial Performance
  • 9.3.3 Product Outlook
  • 9.3.4 Key Developments
• 9.4 SAP
  • 9.4.1 Overview
  • 9.4.2 Financial Performance
  • 9.4.3 Product Outlook
  • 9.4.4 Key Developments
• 9.5 Oracle
  • 9.5.1 Overview
  • 9.5.2 Financial Performance
  • 9.5.3 Product Outlook
  • 9.5.4 Key Developments
• 9.6 IBM
  • 9.6.1 Overview
  • 9.6.2 Financial Performance
  • 9.6.3 Product Outlook
  • 9.6.4 Key Developments
• 9.7 Cisco
  • 9.7.1 Overview
  • 9.7.2 Financial Performance
  • 9.7.3 Product Outlook
  • 9.7.4 Key Developments
• 9.8 Micro Focus
  • 9.8.1 Overview
  • 9.8.2 Financial Performance
  • 9.8.3 Product Outlook
  • 9.8.4 Key Developments
• 9.9 TIBCO
  • 9.9.1 Overview
  • 9.9.2 Financial Performance
  • 9.9.3 Product Outlook
  • 9.9.4 Key Developments
• 9.10 MicroStrategy
  • 9.10.1 Overview
  • 9.10.2 Financial Performance
  • 9.10.3 Product Outlook
  • 9.10.4 Key Developments

10 KEY DEVELOPMENTS

• 10.1 Product Launches/Developments
• 10.2 Mergers and Acquisitions
• 10.3 Business Expansions
• 10.4 Partnerships and Collaborations

11 Appendix

• 11.1 Related Research