Global QoE Analytics For Telecom Operators Market - Global Industry Size, Share, Trends, Competition, Opportunity, and Forecast, By Component (Software, Network Analytics, Performance Monitoring Tools, Customer Experience Management, Predictive and Prescriptive Analytics, Other Softwares, Services, Professional Services, Managed Services, Support and Maintenance Services), By Deployment Mode (Cloud, On-Premises, Hybrid), By Analytics Type (Descriptive Analytics, Diagnostic Analytics, Predictive Analytics, Prescriptive Analytics, Other Analytics Types), By Application (Network Performance Management, Service Quality Monitoring, Customer Experience Management, Churn Prediction and Retention Management, Root-Cause Analysis and Anomaly Detection, Network Investment and Capacity Planning, Other Applications), By Operator Type (Mobile Network Operators, Fixed-Line Operators, Converged Operators, Cable Operators, Other Operator Types), By Organization Size (Large Enterprise, Small and Medium-Sized Operators), By Region, By Company 2021-2031F 2021-2031F

Key Insights	Details
Forecast Period	2026 - 2031
Market Size (2025)	USD 0.0 Billion
CAGR (2026-2031)	8.92%
Fastest Growing Segment	Africa
Largest Market	North America
Market Size (2031)	USD 0.0 Billion

Market Overview

The Global QoE Analytics For Telecom Operators Market is expected to grow from USD 0.0 Billion in 2025 to USD 0.0 Billion by 2031 at a 8.92% CAGR. QoE analytics for telecom operators involves the comprehensive monitoring and evaluation of end-user experience across telecommunication networks and services. Key drivers supporting market growth include the escalating demand for superior service quality, operators' imperative to reduce customer churn, and the increasing complexity of network environments. The rapid expansion of advanced mobile technologies further underscores this need, as according to the International Telecommunication Union, in 2025, 5G subscriptions reached nearly 3 billion users globally, representing approximately one-third of all mobile broadband subscriptions. This significant growth in high-bandwidth connections necessitates robust QoE analysis to ensure optimal performance and user satisfaction.

Despite these compelling drivers, a notable challenge impeding market expansion is the inherent complexity associated with integrating diverse QoE analytics solutions into existing legacy network infrastructure. This integration often requires substantial investment and technical expertise, posing operational hurdles for many telecom operators seeking to deploy comprehensive QoE analytical capabilities.

Key Market Drivers

5G Standalone Architecture Drives Slice-Specific QoE Analytics
Deployment and Evolution of 5G Standalone Architecture significantly influences the QoE analytics market by introducing advanced network capabilities that necessitate more sophisticated monitoring. Unlike non-standalone 5G, 5G SA operates on a cloud-native 5G core, enabling features such as network slicing and ultra-low latency, which are critical for delivering differentiated services and specialized enterprise applications. This architectural shift creates a complex environment where traditional QoE metrics are insufficient, driving the demand for analytical solutions that can precisely measure performance within specific network slices and across diverse use cases. According to the Global mobile Suppliers Association, in October 2026, fewer than 100 operators (98) had launched 5G SA services, indicating a developing market that requires tailored QoE analytics to ensure the reliable delivery of enhanced services and to identify potential issues arising from this new infrastructure.

AI/ML-Driven Analytics Enable Proactive Network Experience Management
The Integration of Artificial Intelligence and Machine Learning in Analytics further propels the market by enabling telecom operators to manage this complexity and derive actionable insights from vast volumes of network data. AI and ML algorithms can automate the detection of anomalies, predict network congestion, and identify root causes of service degradation, moving beyond reactive troubleshooting to proactive experience management. This capability is essential for optimizing network performance and enhancing customer satisfaction in real time. According to NVIDIA's "State of AI in Telecommunications" survey report, February 2026, 89% of telecommunications operators planned to boost AI spending in 2026, reflecting the growing recognition of AI's strategic importance in operational efficiency and service quality. Concurrently, mobile network data traffic continues to grow by 23 percent between Q2 2025 and Q2 2026, according to the Ericsson Mobility Report in 2026, underscoring the continuous need for advanced analytics to manage escalating data volumes and maintain service quality.

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Key Market Challenges

Legacy-Network Integration Challenges for QoE Analytics
The inherent complexity associated with integrating diverse Quality of Experience (QoE) analytics solutions into existing legacy network infrastructure significantly impedes the growth of the Global QoE Analytics For Telecom Operators Market. This difficulty arises from the necessity to align various disparate systems, data formats, and operational protocols that have developed within an operator's environment over time. Successfully deploying comprehensive QoE analytical capabilities requires substantial financial investment and highly specialized technical expertise, presenting considerable operational hurdles. These challenges directly delay the adoption and full utilization of advanced QoE analytics.

Capex Pressures and Extended Timelines Impeding QoE Analytics Adoption
According to a GSMA report from February 2026, telecom operators worldwide are projected to spend approximately 20% of their total capital expenditure on network modernization and software integration by 2030, with a significant portion allocated to overcoming legacy system compatibility issues in the near term. This substantial allocation of resources and extended project timelines often increases implementation risks, thereby slowing the pace at which operators can effectively deploy and benefit from comprehensive QoE analytical frameworks. Such prolonged integration cycles and high upfront costs deter many operators, particularly those managing extensive legacy infrastructure, from investing in new QoE tools, consequently hampering overall market expansion.

Key Market Trends

Shift to Cloud-Native QoE Analytics
Increased adoption of cloud-native Quality of Experience (QoE) analytics platforms represents a significant shift as telecom operators seek greater agility, scalability, and operational efficiency in managing complex network data. These platforms leverage containerization and microservices to enable flexible deployment across hybrid cloud environments, facilitating continuous integration and delivery of analytics capabilities. The inherent elasticity of cloud-native architectures allows operators to dynamically scale resources to meet fluctuating demands for data processing and analysis, reducing infrastructure costs while accelerating time-to-insight. For instance, according to Nokia's press release in September 2026, their Mobile Core Early Access program, which provides a live environment to evaluate cloud-native network functions for operations and analytics, initially launched with a select group of 30 companies before opening to the wider industry. This trend underscores a strategic move away from traditional monolithic systems towards more adaptable and resource-efficient analytical solutions.

Growing Demand for Ready-to-Use QoE Applications
A growing demand for ready-to-use application-based QoE solutions is also shaping the market, driven by the need for rapid deployment and quicker realization of value. Telecom operators increasingly favor pre-built, purpose-specific applications that address particular use cases, such as customer experience management or network performance optimization, without requiring extensive development or integration efforts. These solutions often incorporate embedded artificial intelligence and machine learning algorithms, offering out-of-the-box analytical capabilities designed for specific operational challenges. According to Ericsson, in April 2026, the company was embedding AI throughout its Operations Support Systems and Business Support Systems via more than 20 cloud native Telco IT AI Apps. This preference for readily deployable applications simplifies the adoption of advanced analytics, enabling operators to quickly respond to service quality issues and enhance customer satisfaction.

Segmental Insights

Africa Emerges as Fastest-Growing Segment in QoE Analytics for Telecom Operators Market
The key segmental insight for the Global QoE Analytics For Telecom Operators Market highlights Africa as the fastest-growing segment. This accelerated expansion is primarily driven by the continent's rapidly increasing mobile penetration and smartphone adoption, alongside a burgeoning digitally native population demanding enhanced digital services. Telecom operators in Africa are heavily investing in expanding and upgrading 4G and 5G network infrastructure to support rising data consumption, necessitating advanced QoE analytics to monitor network performance and ensure optimal customer experience in a competitive landscape. Furthermore, diverse regulatory environments across the continent, often encouraging improved service quality and network expansion, also contribute to the heightened demand for sophisticated analytics solutions to manage service delivery effectively.

Regional Insights

North America Leads the Global QoE Analytics Market for Telecom Operators.
North America holds a leading position in the global QoE Analytics for Telecom Operators Market, primarily driven by its advanced telecommunications infrastructure and substantial investments in technology. The region benefits from early adoption of 5G standalone networks and mature data-driven network practices among its competitive national carriers. Furthermore, the strong embrace of cloud-native solutions and the integration of artificial intelligence and machine learning technologies contribute significantly to this dominance. The persistent demand for data-driven decision-making to optimize network performance and elevate customer experiences, coupled with oversight from regulatory bodies like the Federal Communications Commission, further propels market expansion.

Recent Developments

• In November 2025, Dhiraagu, a telecommunications provider, formed a strategic partnership with Infovista to implement AI-powered network optimization throughout the Maldives’ first end-to-end 5G deployment. This collaboration was designed to enhance operational efficiencies and accelerate time-to-market for new services. The integration of Infovista’s automated assurance suite, Ativa™, with Dhiraagu’s network management, allowed for unified policy management and real-time operational insights. The partnership aimed to deliver superior customer experiences by maintaining high network quality across all technologies from 2G to 5G.
• In July 2025, Ericsson reported its strategic focus on leveraging Artificial Intelligence (AI) to advance network design and enhance 5G Quality of Experience. The company communicated that AI presented opportunities for network automation and the creation of new industry revenue streams. Ericsson anticipated that AI would contribute to increasing consumer and business demand for 5G connectivity by enabling lower-latency connections and improved support for uplink capabilities. This emphasis on AI integration reflected the company's commitment to technological leadership and innovation within the telecom sector.
• In February 2024, Ericsson highlighted its research on the significance of video streaming for mobile Quality of Experience (QoE) strategies. The company underscored that video traffic constituted approximately 74 percent of global mobile network traffic in 2024, making it a critical area for QoE assessment. Ericsson’s analysis emphasized the importance of standardized QoE models, such as the ITU-T P.1203, for objectively measuring and comparing perceived quality across different networks. This initiative provided valuable insights for telecom operators focusing on optimizing service delivery and enhancing user satisfaction.
• In February 2024, Infovista showcased its advanced business-driven network automation solutions at MWC Barcelona. The company demonstrated how its offerings assist telecom operators in achieving desired Quality of Experience while optimizing capital expenditure investments. Infovista’s exhibited capabilities focused on validating and optimizing user experience for both native and over-the-top applications and services. This approach aimed at maximizing revenues and minimizing customer churn by providing a comprehensive view of services, integrating customer, device, and network data to deliver differentiated service level agreements for 5G business clients.

Key Market Players

• Ericsson
• Nokia Corporation
• Cisco Systems, Inc.
• Mobileum Inc.
• RADCOM Ltd.
• NETSCOUT SYSTEMS, INC.
• Infovista S.A.S.
• MedUX
• Ookla, LLC
• Rohde & Schwarz GmbH & Co KG

By Component	By Deployment Mode	By Analytics Type	By Application	By Operator Type	By Organization Size	By Region
Software Network Analytics Performance Monitoring Tools Customer Experience Management Predictive and Prescriptive Analytics Other Softwares Services Professional Services Managed Services Support and Maintenance Services	Cloud On-Premises Hybrid	Descriptive Analytics Diagnostic Analytics Predictive Analytics Prescriptive Analytics Other Analytics Types	Network Performance Management Service Quality Monitoring Customer Experience Management Churn Prediction and Retention Management Root-Cause Analysis and Anomaly Detection Network Investment and Capacity Planning Other Applications	Mobile Network Operators Fixed-Line Operators Converged Operators Cable Operators Other Operator Types	Large Enterprise Small and Medium-Sized Operators	North America Europe Asia Pacific South America Middle East & Africa

Report Scope:

In this report, the Global QoE Analytics For Telecom Operators Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

• QoE Analytics For Telecom Operators Market, By Component:

• Software
• Network Analytics
• Performance Monitoring Tools
• Customer Experience Management
• Predictive and Prescriptive Analytics
• Other Softwares
• Services
• Professional Services
• Managed Services
• Support and Maintenance Services

• QoE Analytics For Telecom Operators Market, By Deployment Mode:

• Cloud
• On-Premises
• Hybrid

• QoE Analytics For Telecom Operators Market, By Analytics Type:

• Descriptive Analytics
• Diagnostic Analytics
• Predictive Analytics
• Prescriptive Analytics
• Other Analytics Types

• QoE Analytics For Telecom Operators Market, By Application:

• Network Performance Management
• Service Quality Monitoring
• Customer Experience Management
• Churn Prediction and Retention Management
• Root-Cause Analysis and Anomaly Detection
• Network Investment and Capacity Planning
• Other Applications

• QoE Analytics For Telecom Operators Market, By Operator Type:

• Mobile Network Operators
• Fixed-Line Operators
• Converged Operators
• Cable Operators
• Other Operator Types

• QoE Analytics For Telecom Operators Market, By Organization Size:

• Large Enterprise
• Small and Medium-Sized Operators

• QoE Analytics For Telecom Operators Market, By Region:

• North America
• United States
• Canada
• Mexico
• Europe
• France
• United Kingdom
• Italy
• Germany
• Spain
• Asia Pacific
• China
• India
• Japan
• Australia
• South Korea
• South America
• Brazil
• Argentina
• Colombia
• Middle East & Africa
• South Africa
• Saudi Arabia
• UAE