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Global Telecom Analytics Market to reach USD XX million by 2028.

Global Telecom Analytics Market Size study, By Component (Software, Services), By Application (Customer Management, Sales and Marketing Management, Risk and Compliance Management, Network Management, Workforce Management), By Deployment Model (On-premises, Cloud), By Organization Size (Large enterprises, Small and Medium-sized Enterprises (SMEs), and Regional Forecasts 2022-2028

Product Code: ICTICTS-84490726
Publish Date: 14-08-2022
Page: 200

Global Telecom Analytics Market is valued approximately USD XX million in 2021 and is anticipated to grow with a healthy growth rate of more than XX % over the forecast period 2022-2028.

The Telecom Analytics can be defined as a type of business intelligence specifically tailored for the complex needs of telecommunication organizations. Telecommunication companies can utilize the telecom analytics solutions to analyze their vast data base and can use this data to draw actionable insights. These insights help telecom companies in enhancing customer experience, loyalty, and sales volume, as well as are effective in enhancing operational efficiencies. The growing penetration of big data & analytics services and rising concern over data security and customer churn coupled with recent strategic initiatives from leading market players are factors that are accelerating the global market demand. For instance, according to Statista – during 2020, the global big data market was valued at USD 56 billion, and it is projected to grow to USD 103 billion by 2027. Furthermore, leading market players are working towards various strategic initiatives including collaboration and partnerships to leverage the growing demand for telecom analytics solutions. For instance, in May 2021, Vodafone Group announced a six-year partnership deal Google, Inc. (Google Cloud) to collaborate on development of a new analytics system. This new system would be comprised of two parts: an integrated data platform called Nucleus, which would use hybrid cloud technology and a distribution engine called Dynamo, which would pull data from various sources and push key information insights back to end points for further use. Moreover, in August 2021, Paul Aalto, USA based enterprise data cloud company Cloudera, Inc. collaborated with South Korean mobile network operator and Subsidiary of LG Corporation named LG Uplus to build real-time big data analytics Platform. Also, growing emergence of advanced technologies such IoT, big data etc. and increasing competitiveness among telecom operators are anticipated to act as a catalyzing factor for the market demand during the forecast period. However, a lack of awareness towards analytics solutions among telecom operators impedes the growth of the market over the forecast period of 2022-2028.

The key regions considered for the global Telecom Analytics Market study include Asia Pacific, North America, Europe, Latin America, and the Rest of the World. North America is the leading region across the world in terms of market share owing to the growing technological advancements as well as presence of leading market players in the region. Whereas, Asia Pacific is anticipated to exhibit a significant growth rate over the forecast period 2022-2028. Factors such as the thriving growth of telecom sector and rising investment in advanced analytics technologies in the region, would create lucrative growth prospects for the global Telecom Analytics Market across the Asia Pacific region.

Major market players included in this report are:
SAP (Germany)
Oracle (US)
SAS Institute (US)
Adobe (US)
Cisco (US)
Teradata (US)
Micro Focus (UK)
MicroStrategy (US)

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
By Component
By Application
Customer Management
Sales and Marketing Management
Risk and Compliance Management
Network Management
Workforce Management
By Deployment Model
By Organization Size
Large enterprises
Small and Medium-sized Enterprises (SMEs)
By Region:
North America

Asia Pacific
South Korea
Latin America
Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019, 2020
Base year – 2021
Forecast period – 2022 to 2028

Target Audience of the Global Telecom Analytics Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2028 (USD Million)
1.2.1. Telecom Analytics Market, by Region, 2020-2028 (USD Million)
1.2.2. Telecom Analytics Market, by Component, 2020-2028 (USD Million)
1.2.3. Telecom Analytics Market, by Application, 2020-2028 (USD Million)
1.2.4. Telecom Analytics Market, by Deployment Model, 2020-2028 (USD Million)
1.2.5. Telecom Analytics Market, by Organization Size, 2020-2028 (USD Million)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Telecom Analytics Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Telecom Analytics Market Dynamics
3.1. Telecom Analytics Market Impact Analysis (2020-2028)
3.1.1. Market Drivers Growing penetration of big data & analytics services. Rising concern over data security and customer churn. Recent strategic initiatives from leading market players.
3.1.2. Market Challenges Lack of awareness towards analytics solutions.
3.1.3. Market Opportunities Growing emergence of advanced technologies. Increasing competitiveness among telecom operators.
Chapter 4. Global Telecom Analytics Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2028)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
4.5. Top investment opportunity
4.6. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1.1. Assessment of the overall impact of COVID-19 on the industry
5.1.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global Telecom Analytics Market, by Component
6.1. Market Snapshot
6.2. Global Telecom Analytics Market by Component, Performance – Potential Analysis
6.3. Global Telecom Analytics Market Estimates & Forecasts by Component 2018-2028 (USD Million)
6.4. Telecom Analytics Market, Sub Segment Analysis
6.4.1. Software
6.4.2. Services
Chapter 7. Global Telecom Analytics Market, by Application
7.1. Market Snapshot
7.2. Global Telecom Analytics Market by Application, Performance – Potential Analysis
7.3. Global Telecom Analytics Market Estimates & Forecasts by Application 2018-2028 (USD Million)
7.4. Telecom Analytics Market, Sub Segment Analysis
7.4.1. Customer Management
7.4.2. Sales and Marketing Management
7.4.3. Risk and Compliance Management
7.4.4. Network Management
7.4.5. Workforce Management
Chapter 8. Global Telecom Analytics Market, by Deployment Model
8.1. Market Snapshot
8.2. Global Telecom Analytics Market by Deployment Model, Performance – Potential Analysis
8.3. Global Telecom Analytics Market Estimates & Forecasts by Deployment Model 2018-2028 (USD Million)
8.4. Telecom Analytics Market, Sub Segment Analysis
8.4.1. On-premises
8.4.2. Cloud
Chapter 9. Global Telecom Analytics Market, by Organization Size
9.1. Market Snapshot
9.2. Global Telecom Analytics Market by Organization Size, Performance – Potential Analysis
9.3. Global Telecom Analytics Market Estimates & Forecasts by Organization Size 2018-2028 (USD Million)
9.4. Telecom Analytics Market, Sub Segment Analysis
9.4.1. Large enterprises
9.4.2. Small and Medium-sized Enterprises (SMEs)
Chapter 10. Global Telecom Analytics Market, Regional Analysis
10.1. Telecom Analytics Market, Regional Market Snapshot
10.2. North America Telecom Analytics Market
10.2.1. U.S. Telecom Analytics Market Component estimates & forecasts, 2018-2028 Application estimates & forecasts, 2018-2028 Deployment Model estimates & forecasts, 2018-2028 Organization Size estimates & forecasts, 2018-2028
10.2.2. Canada Telecom Analytics Market
10.3. Europe Telecom Analytics Market Snapshot
10.3.1. U.K. Telecom Analytics Market
10.3.2. Germany Telecom Analytics Market
10.3.3. France Telecom Analytics Market
10.3.4. Spain Telecom Analytics Market
10.3.5. Italy Telecom Analytics Market
10.3.6. Rest of Europe Telecom Analytics Market
10.4. Asia-Pacific Telecom Analytics Market Snapshot
10.4.1. China Telecom Analytics Market
10.4.2. India Telecom Analytics Market
10.4.3. Japan Telecom Analytics Market
10.4.4. Australia Telecom Analytics Market
10.4.5. South Korea Telecom Analytics Market
10.4.6. Rest of Asia Pacific Telecom Analytics Market
10.5. Latin America Telecom Analytics Market Snapshot
10.5.1. Brazil Telecom Analytics Market
10.5.2. Mexico Telecom Analytics Market
10.6. Rest of The World Telecom Analytics Market

Chapter 11. Competitive Intelligence
11.1. Top Market Strategies
11.2. Company Profiles
11.2.1. SAP (Germany) Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
11.2.2. Oracle (US)
11.2.3. IBM (US)
11.2.4. SAS Institute (US)
11.2.5. Adobe (US)
11.2.6. Cisco (US)
11.2.7. Teradata (US)
11.2.8. Micro Focus (UK)
11.2.9. TIBCO (US)
11.2.10. MicroStrategy (US)
Chapter 12. Research Process
12.1. Research Process
12.1.1. Data Mining
12.1.2. Analysis
12.1.3. Market Estimation
12.1.4. Validation
12.1.5. Publishing
12.2. Research Attributes
12.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
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Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
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Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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