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市场调查报告书
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1939055

电信分析：市场占有率分析、产业趋势与统计、成长预测（2026-2031）

Telecom Analytics - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2026 - 2031)
出版日期: | 出版商: Mordor Intelligence | 英文 120 Pages | 商品交期: 2-3个工作天内

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简介目录

2025 年电信分析市场价值为 82.2 亿美元，预计到 2031 年将达到 146.9 亿美元，高于 2026 年的 90.6 亿美元。

预计在预测期（2026-2031 年）内，复合年增长率将达到 10.17%。

电信分析-市场-IMG1

这一强劲的成长势头得益于5G的稳步部署、人工智慧工具包的快速成熟以及诈欺成本的不断攀升，这些因素都在推动通讯业者向预测性和即时分析转型。云端原生架构如今已成为大多数大规模部署的基础，而边缘节点在对延迟高度敏感的应用场景（例如私人5G和大规模物联网）中发挥关键作用。网路供应商、超大规模资料中心超大规模资料中心业者和细分领域的专业厂商正在加剧竞争，力求将生成式人工智慧、自动化模型生命週期管理和基于切片的仪表板等功能整合到各自的产品中。同时，通讯业者正将重点从资本密集的软体投资转向以结果为导向的分析服务，这些服务有望带来可衡量的解约率降低和收入保障。

全球电信分析市场趋势与洞察

快速部署 5G 推动了网路分析技术的应用

独立组网的5G部署正在推动资料量和效能变数的激增，迫使营运商部署频谱、切片感知的分析引擎，以优化频谱、功率和服务品质。预计到2028年，中国的5G普及率将达到88%，届时该地区将成为全球最大的网路遥测资料来源地。切片专属的仪錶板能够确保企业应用场景的确定性延迟和吞吐量，释放高达2000亿美元的商业潜力。边缘运算节点的出现带来了新的复杂性，因为遥测资料现在来自多个层级，每个层级都需要毫秒级的洞察。在亚太地区，这些需求正推动电信分析市场以13.26%的复合年增长率快速成长，国营通讯业者竞相为工业4.0提供超可靠的服务。

更容易遭受诈欺

到2024年，电信诈骗的损失将飙升至398.9亿美元，占全球通讯业者收入的2.22%。诈骗如今正利用人工智慧技术自动实施SIM卡交换、合约诈欺和漫游漏洞利用，暴露了传统规则引擎的限制。这通讯业者转向基于图的分析和自学习异常检测系统，以近乎即时的方式融合通话详细记录（CDR）、信令数据和客户画像。在新兴市场，用户的快速成长超过了反诈骗投入，因此诈欺分析已成为采购计画中的重中之重。产业研究表明，儘管数据标註仍然是一项挑战，但83%的反诈骗团队计划在2025年前采用生成式人工智慧。

资料隐私和跨境传输限制

随着资料保护法规网路的日益收窄，全球分析基础设施正变得日益碎片化。 GDPR、印度的《数位个人资讯保护法》以及中国的《个人资讯保护法》均规定了本地处理义务，迫使营运商复製基础设施并采用隐私纳入设计控制措施。跨国通讯服务提供者（CSP）在跨境传输用户记录之前必须对其进行加密、令牌化或匿名化处理，这会增加延迟并降低模型准确性。合规负担在亚太地区尤其沉重，因为不同的国家法律要求每个市场都必须制定客製化的安全方案。

细分市场分析

欺诈管理分析是成长最快的细分市场，复合年增长率高达16.90%，这主要受产业损失的影响，预计到2024年，诈欺造成的损失将超过398.9亿美元。这些平台将图分析与深度学习引擎结合，可在数秒内识别可疑的通话详细记录和漫游模式，使营运商能够在诈欺流量造成收入损失之前将其冻结。然而，客户分析仍将保持主导地位，预计到2025年将占据36.24%的市场份额，因为通讯业者正在加强个人化客户维繫宣传活动、客户流失预测模型和客户生命週期价值评分。

网路分析是自主切片编配的基础，它将关键绩效指标 (KPI) 预测结果回馈到封闭回路型控制设备，以避免网路拥塞并提升 5G 体验的一致性。随着通讯业者将即时体验评分发布到企业仪錶板，服务品质和体验分析的重要性日益凸显，这对于製造业、采矿业和医疗保健等行业实现服务等级协议 (SLA) 的货币化至关重要。行销和销售分析应用趋势建模来提升宣传活动报酬率 (ROI)，而定价和收入管理分析则优化了套餐组合和动态折扣。应用层工具实现了全面的跨域视觉性，为零接触营运奠定了基础。

边缘和混合配置将以 21.92% 的复合年增长率增长，主要受关键业务垂直行业（如港口、工厂和公共产业）的驱动，这些行业需要低于 10 毫秒的洞察循环。通讯业者现在将轻量级推理引擎嵌入基频单元和本地边缘节点，以执行延迟预算和资料主权规则。即使到了 2025 年，云端模式仍将占据电信分析市场 65.45% 的份额，用于託管 CPU 密集型训练作业和长週期批量分析。

混合设计融合了两者的优势：云爆发可以处理可变工作负载，而边缘站点则执行异常警报等确定性任务。在监管严格的地区以及传统BSS/OSS系统迁移困难的地区，本地部署仍将持续。随着5G Advanced和6G蓝图的逐步成型，供应商正在将多丛集监控功能、联合身分和自动化策略部署整合到配置范本中，以简化计算域之间的迁移。

区域分析

北美将在2025年占据电信分析市场34.55%的份额，这主要得益于5G早期商业化进程的推进以及企业对专用网路的需求。美国通讯业者正利用其在5G领域的私有投资（预计到2027年将超过37亿美元），为製造业、医疗保健和国防等产业量身订做网路即服务（NaaS）产品，并融入分析技术。此外，诸如T-Mobile收购光纤业务等整合倡议，也推动了分析技术的投资，以整合固定和行动网路的品质指标。

亚太地区是成长最快的地区，复合年增长率高达13.06%，这主要得益于中国积极的部署蓝图和印度的快速数位化。该地区的行动业务收益预计将从2023年的3,219亿美元成长到2028年的3,887亿美元，因此，将流量转化为营收的关键在于运用分析技术。随着世界各国政府大力推动本土人工智慧框架的建设，通讯业者被迫采用联邦学习模型，虽然将原始资料保留在本地，但模型权重在全球共用。

在欧洲，GDPR持续推动对隐私增强技术和混合部署的需求，并保持稳定成长。通讯业者被要求证明审核和即时违规检测能力，这促使分析供应商将同意管理和资料沿袭追踪功能整合到系统中。

中东/非洲和南美洲的绝对交易量落后，但随着新的 5G 部署绕过传统的 OSS 并直接转向云原生分析堆迭，这些地区展现出成长潜力。

其他福利：

  • Excel格式的市场预测（ME）表
  • 分析师支持（3个月）

目录

第一章 引言

  • 研究假设和市场定义
  • 调查范围

第二章调查方法

第三章执行摘要

第四章 市场情势

  • 市场概览
  • 市场驱动因素
    • 降低客户流失率的需求日益增长。
    • 更容易遭受诈欺
    • 快速部署 5G 推动了网路分析技术的应用
    • 通讯业者加速采用云端原生分析技术
    • 私有 5G 网路的网路切片分析的兴起
    • 人工智慧驱动的零接触操作催生了对封闭回路型分析的需求。
  • 市场限制
    • 通讯业者缺乏意识
    • 资料隐私和跨境传输限制
    • 频谱竞标会增加营运成本 (OPEX) 并抑制现场投资。
    • 缺乏针对特定通讯业者的AI模型标註资料集
  • 产业价值链分析
  • 监管环境
  • 技术展望
  • 波特五力分析
    • 新进入者的威胁
    • 买方的议价能力
    • 供应商的议价能力
    • 替代品的威胁
    • 竞争对手之间的竞争
  • 疫情影响评估

第五章 市场规模与成长预测

  • 透过使用
    • 客户分析
    • 网路分析
    • 行销与销售分析
    • 定价和收益管理分析
    • 服务品质与客户体验分析
    • 欺诈管理分析
    • 其他用途
  • 透过部署
    • 云
    • 本地部署
    • 边缘/混合
  • 按组件
    • 软体
    • 服务
      • 专业服务
      • 託管服务
  • 最终用户公司规模
    • 中小企业
    • 大公司
  • 通讯业者类型
    • 行动网路营运商（MNO）
    • 固定通讯业者
    • 网际服务供应商(ISP)
    • 行动虚拟网路营运商（MVNO）
    • 综合通讯业者
  • 按地区
    • 北美洲
      • 我们
      • 加拿大
      • 墨西哥
    • 南美洲
      • 巴西
      • 阿根廷
      • 哥伦比亚
      • 其他南美洲
    • 欧洲
      • 英国
      • 德国
      • 法国
      • 西班牙
      • 义大利
      • 俄罗斯
      • 其他欧洲地区
    • 亚太地区
      • 中国
      • 印度
      • 日本
      • 韩国
      • 澳洲
      • 东南亚
      • 亚太其他地区
    • 中东和非洲
      • 中东
        • 沙乌地阿拉伯
        • 阿拉伯聯合大公国
        • 土耳其
        • 其他中东地区
      • 非洲
        • 南非
        • 奈及利亚
        • 肯亚
        • 其他非洲地区

第六章 竞争情势

  • 市场集中度
  • 策略趋势
  • 市占率分析
  • 公司简介
    • Accenture plc
    • Amdocs Inc.
    • Cisco Systems, Inc.
    • Dell Inc.
    • Ericsson AB
    • Guavus, Inc.
    • Huawei Technologies Co., Ltd.
    • IBM Corporation
    • InfoFaces, Inc.
    • Microsoft Corporation
    • Nokia Corporation
    • Oracle Corporation
    • SAS Institute Inc.
    • SAP SE
    • Subex Limited
    • TEOCO Corporation
    • Teradata Corporation
    • Wipro Limited
    • ZTE Corporation
    • Mu Sigma, Inc.

第七章 市场机会与未来展望

简介目录
Product Code: 50058

The telecom analytics market was valued at USD 8.22 billion in 2025 and estimated to grow from USD 9.06 billion in 2026 to reach USD 14.69 billion by 2031, at a CAGR of 10.17% during the forecast period (2026-2031).

Telecom Analytics - Market - IMG1

This robust trajectory is propelled by relentless 5G roll-outs, fast-maturing AI toolkits, and the rising cost of fraud, each of which is nudging operators toward predictive, real-time analytics. Cloud-native architectures now underpin most large deployments, while edge nodes are assuming a pivotal role in latency-sensitive use cases such as private 5G and massive IoT. Competition is intensifying as network vendors, hyperscalers, and niche specialists race to embed generative AI, automated model lifecycle management, and slice-aware dashboards into their offers. At the same time, operators are shifting focus from capital-intensive software investments to outcome-based analytics services that guarantee measurable churn reduction and revenue assurance

Global Telecom Analytics Market Trends and Insights

Rapid 5G Deployment Spurring Network Analytics Adoption

Standalone 5G roll-outs are magnifying data volumes and performance variables, compelling operators to adopt real-time slice-aware analytics engines that optimize spectrum, power, and quality of service. China is on track for 88% 5G penetration by 2028, turning the region into the largest single source of network telemetry. Slice-specific dashboards unlock a USD 200 billion monetization pool by guaranteeing deterministic latency and throughput for enterprise use cases. Edge compute nodes add fresh complexity because telemetry now arrives from multiple hierarchy layers, each demanding millisecond-level insight. In Asia-Pacific, these requirements underpin a 13.26% CAGR in Telecom Analytics market adoption as state-owned carriers race to deliver ultra-reliable services for Industry 4.0.

Increasing Vulnerability to Fraudulent Activities

Telecom fraud losses ballooned to USD 39.89 billion in 2024, equivalent to 2.22% of global operator revenue . Fraud rings now weaponize AI to automate SIM-swap, subscription, and roaming exploits, exhausting the cAsia Pacificity of legacy rule engines. Operators therefore pivot to graph-based analytics and self-learning anomaly detectors that fuse CDRs, signaling data, and customer profiles in near real time. Emerging markets bear the brunt because rapid subscriber growth outpaces fraud-mitigation investment, pushing fraud-centric analytics to the top of procurement roadmaps. A recent industry poll shows 83% of fraud teams intend to deploy generative AI by 2025, even though poor data labeling remains a hurdle.

Data Privacy and Cross-Border Transfer Restrictions

A tightening web of data-protection rules is splintering global analytics footprints. GDPR, India's Digital Personal Data Protection Act, and China's PIPL each impose local-processing mandates that force operators to duplicate infrastructure and embed privacy-by-design controls. Multinational CSPs must encrypt, tokenize, or anonymize subscriber records before moving them across borders, adding latency and diluting model accuracy. The compliance burden is most acute in Asia Pacific, where divergent national laws require bespoke security blueprints for every market.

Other drivers and restraints analyzed in the detailed report include:

  1. AI-Driven Zero-Touch Operations Creating Closed-Loop Analytics Demand
  2. Accelerated Adoption of Cloud-Native Analytics by Telcos
  3. Scarcity of Telco-Specific Labeled Datasets for AI Models

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Fraud Management Analytics has become the fastest-expanding segment, growing at a 16.90% CAGR on the back of industry losses that exceeded USD 39.89 billion in 2024. These platforms blend graph analytics and deep-learning engines to pinpoint suspicious call-detail records and roaming patterns within seconds, enabling operators to freeze illicit traffic before revenue leakage occurs. Customer Analytics nevertheless retains leadership with 36.24% of the Telecom Analytics market in 2025 as carriers intensify personalized retention campaigns, churn-prediction models, and lifetime-value scoring.

Network Analytics underpins autonomous slice orchestration, feeding closed-loop controllers with KPI forecasts that avert congestion and improve 5G experience consistency. Service-Quality and Experience Analytics is gaining ground as operators publish real-time experience scores to enterprise dashboards, a prerequisite for monetizing SLAs in manufacturing, mining, and healthcare. Marketing and Sales Analytics applies propensity modeling to boost campaign ROI, while Pricing and Revenue-Management Analytics optimizes tariff bundling and dynamic discounting. Collectively, application-layer tools propel cross-domain visibility, a prerequisite for zero-touch operations.

Edge and hybrid configurations are registering a 21.92% CAGR due to mission-critical verticals ports, factories, and utilities demanding sub-10 millisecond insight loops. Operators now embed lightweight inference engines at base-band units and on-prem edge nodes to enforce latency budgets and data-sovereignty rules. The cloud model still controlled 65.45% of the Telecom Analytics market in 2025 by hosting CPU-hungry training jobs and long-cycle batch analytics.

Hybrid blueprints marry the two worlds: cloud bursting handles volatile workloads, while edge sites execute deterministic tasks like anomaly alarms. On-prem deployments persist in heavily regulated jurisdictions or where legacy BSS/OSS systems resist migration. As 5G Advanced and 6G roadmaps unfold, vendors are baking multi-cluster observability, federated identity, and automated policy rollout into deployment templates, making it easier to pivot between compute domains.

The Telecom Analytics Market Report is Segmented by Application (Customer, Network Analytics, and More), Deployment (Cloud and More), Component (Software, Services), End-User Enterprise Size (Small and Medium Enterprises, Large Enterprises), Telecom Operator Type (Mobile Network Operators, Fixed-Line Operators, and More), and Geography (North America, Europe, and More). The Market Forecasts are Provided in Terms of Value (USD).

Geography Analysis

North America dominated the Telecom Analytics market with 34.55% share in 2025, buoyed by early 5G monetization and enterprise-grade private-network demand. The U.S. carriers are leveraging analytics to orchestrate network-as-a-service offers for manufacturing, healthcare, and defense, capitalizing on a private-5G spend that will surpass USD 3.7 billion by 2027. Consolidation moves such as T-Mobile's fiber acquisitions are also stoking analytics investment to integrate fixed and mobile quality metrics.

Asia-Pacific is the fastest-growing region at 13.06% CAGR, led by China's aggressive deployment roadmap and India's rapid digitalization. The region's mobile-services revenue could climb from USD 321.9 billion in 2023 to USD 388.7 billion in 2028, and analytics is crucial for converting that traffic into profit. Governments are championing indigenous AI frameworks, prompting operators to adopt federated-learning models that keep raw data local while sharing model weights globally.

Europe maintains steady expansion as GDPR drives demand for privacy-enhancing technologies and hybrid deployments. Operators must demonstrate auditability and real-time breach detection, pushing analytics vendors to incorporate consent management and lineage tracking.

Middle East and Africa and South America trail in absolute size but show upside as green-field 5G launches bypass legacy OSS and leapfrog directly to cloud-native analytics stacks.

  1. Accenture plc
  2. Amdocs Inc.
  3. Cisco Systems, Inc.
  4. Dell Inc.
  5. Ericsson AB
  6. Guavus, Inc.
  7. Huawei Technologies Co., Ltd.
  8. IBM Corporation
  9. InfoFaces, Inc.
  10. Microsoft Corporation
  11. Nokia Corporation
  12. Oracle Corporation
  13. SAS Institute Inc.
  14. SAP SE
  15. Subex Limited
  16. TEOCO Corporation
  17. Teradata Corporation
  18. Wipro Limited
  19. ZTE Corporation
  20. Mu Sigma, Inc.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

  • 4.1 Market Overview
  • 4.2 Market Drivers
    • 4.2.1 Surge in need for churn reduction
    • 4.2.2 Increasing vulnerability to fraudulent activities
    • 4.2.3 Rapid 5G deployment spurring network analytics adoption
    • 4.2.4 Accelerated adoption of cloud-native analytics by telcos
    • 4.2.5 Emergence of network slicing analytics for private 5G networks
    • 4.2.6 AI-driven zero-touch operations creating closed-loop analytics demand
  • 4.3 Market Restraints
    • 4.3.1 Lack of awareness among telecom operators
    • 4.3.2 Data privacy and cross-border transfer restrictions
    • 4.3.3 OPEX strain from spectrum auctions curbing on-prem investments
    • 4.3.4 Scarcity of telco-specific labelled datasets for AI models
  • 4.4 Industry Value-Chain Analysis
  • 4.5 Regulatory Landscape
  • 4.6 Technological Outlook
  • 4.7 Porter's Five Forces Analysis
    • 4.7.1 Threat of New Entrants
    • 4.7.2 Bargaining Power of Buyers
    • 4.7.3 Bargaining Power of Suppliers
    • 4.7.4 Threat of Substitutes
    • 4.7.5 Competitive Rivalry
  • 4.8 Pandemic Impact Review

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

  • 5.1 By Application
    • 5.1.1 Customer Analytics
    • 5.1.2 Network Analytics
    • 5.1.3 Marketing and Sales Analytics
    • 5.1.4 Pricing and Revenue-Management Analytics
    • 5.1.5 Service Quality and Experience Analytics
    • 5.1.6 Fraud Management Analytics
    • 5.1.7 Other Application
  • 5.2 By Deployment
    • 5.2.1 Cloud
    • 5.2.2 On-premises
    • 5.2.3 Edge / Hybrid
  • 5.3 By Component
    • 5.3.1 Software
    • 5.3.2 Services
      • 5.3.2.1 Professional Services
      • 5.3.2.2 Managed Services
  • 5.4 By End-User Enterprise Size
    • 5.4.1 Small and Medium Enterprises (SMEs)
    • 5.4.2 Large Enterprises
  • 5.5 By Telecom Operator Type
    • 5.5.1 Mobile Network Operators (MNOs)
    • 5.5.2 Fixed-line Operators
    • 5.5.3 Internet Service Providers (ISPs)
    • 5.5.4 Mobile Virtual Network Operators (MVNOs)
    • 5.5.5 Converged Operators
  • 5.6 By Geography
    • 5.6.1 North America
      • 5.6.1.1 United States
      • 5.6.1.2 Canada
      • 5.6.1.3 Mexico
    • 5.6.2 South America
      • 5.6.2.1 Brazil
      • 5.6.2.2 Argentina
      • 5.6.2.3 Colombia
      • 5.6.2.4 Rest of South America
    • 5.6.3 Europe
      • 5.6.3.1 United Kingdom
      • 5.6.3.2 Germany
      • 5.6.3.3 France
      • 5.6.3.4 Spain
      • 5.6.3.5 Italy
      • 5.6.3.6 Russia
      • 5.6.3.7 Rest of Europe
    • 5.6.4 Asia Pacific
      • 5.6.4.1 China
      • 5.6.4.2 India
      • 5.6.4.3 Japan
      • 5.6.4.4 South Korea
      • 5.6.4.5 Australia
      • 5.6.4.6 Southeast Asia
      • 5.6.4.7 Rest of Asia Pacific
    • 5.6.5 Middle East and Africa
      • 5.6.5.1 Middle East
        • 5.6.5.1.1 Saudi Arabia
        • 5.6.5.1.2 United Arab Emirates
        • 5.6.5.1.3 Turkey
        • 5.6.5.1.4 Rest of Middle East
      • 5.6.5.2 Africa
        • 5.6.5.2.1 South Africa
        • 5.6.5.2.2 Nigeria
        • 5.6.5.2.3 Kenya
        • 5.6.5.2.4 Rest of Africa

6 COMPETITIVE LANDSCAPE

  • 6.1 Market Concentration
  • 6.2 Strategic Moves
  • 6.3 Market Share Analysis
  • 6.4 Company Profiles {(includes Global level Overview, Market level overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share for key companies, Products and Services, and Recent Developments)}
    • 6.4.1 Accenture plc
    • 6.4.2 Amdocs Inc.
    • 6.4.3 Cisco Systems, Inc.
    • 6.4.4 Dell Inc.
    • 6.4.5 Ericsson AB
    • 6.4.6 Guavus, Inc.
    • 6.4.7 Huawei Technologies Co., Ltd.
    • 6.4.8 IBM Corporation
    • 6.4.9 InfoFaces, Inc.
    • 6.4.10 Microsoft Corporation
    • 6.4.11 Nokia Corporation
    • 6.4.12 Oracle Corporation
    • 6.4.13 SAS Institute Inc.
    • 6.4.14 SAP SE
    • 6.4.15 Subex Limited
    • 6.4.16 TEOCO Corporation
    • 6.4.17 Teradata Corporation
    • 6.4.18 Wipro Limited
    • 6.4.19 ZTE Corporation
    • 6.4.20 Mu Sigma, Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

  • 7.1 White-space and Unmet-need Assessment