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Global Data Monetization In Telecom Market
Market Size in USD Billion
CAGR :
%
USD
3.01 Billion
USD
13.09 Billion
2021
2029
Forecast Period
2022 –2029
Market Size(Base Year)
USD
3.01 Billion
Market Size (Forecast Year)
USD
13.09 Billion
CAGR
20.20
%
Major Markets Players
Technologies Redknee Inc. SAP SE SQLstreamInc 1010data Dawex Systems Elevondata Labs Private Limited Gemalto iConnectiva Mahindra Comviva NETSCOUT Optiva Emu Analytics Ltd Adastra Corporation
Global Data Monetization in Telecom Market, By Component (Tools, Services), Data Type (Customer Data, Product Data, Financial Data, Supplier Data), Business Function (Sales and Marketing, Supply Chain Management, Operations, Finance, Others), Deployment Type (On-Premises, Cloud), Organization Size (Small and Medium-Sized Enterprises (SMEs), Large Enterprises) - Industry Trends and Forecast to 2029
Market Analysis and Size
In recent years, the telecom industry has succeeded in building strong external partnerships with third-party enterprises to leverage data for creating innovative offers for their customers. Data is becoming more structured everyday with the help of Artificial Intelligence (AI), and data quality has improved significantly, resulting in refined customer databases. Telecom enterprises are rapidly adopting data monetization to create new opportunities for growth and revenue.
Global Data Monetization in Telecom Market was valued at USD 3.01 billion in 2021 and is expected to reach USD 13.09 billion by 2029, registering a CAGR of 20.20% during the forecast period of 2022-2029. "On-Premises" account for the largest type segment in the respective market due to the high adoption for applications that involve processing sensitive and confidential data. In addition to the market insights such as market value, growth rate, market segments, geographical coverage, market players, and market scenario, the market report curated by the Data Bridge Market Research team also includes in-depth expert analysis, import/export analysis, pricing analysis, production consumption analysis, and pestle analysis.
Market Definition
Data monetization refers to a process of converting the unstructured or unused vast amount of enterprise data into valuable insights. It involves monetizing of this data into currency or exchange of service. The process assists enterprises in declining the cost of their business operations while increasing revenue streams.
Report Scope and Market Segmentation
Report Metric
Details
Forecast Period
2022 to 2029
Base Year
2021
Historic Years
2020 (Customizable to 2014 - 2019)
Quantitative Units
Revenue in USD Billion, Volumes in Units, Pricing in USD
Segments Covered
Component (Tools, Services), Data Type (Customer Data, Product Data, Financial Data, Supplier Data), Business Function (Sales and Marketing, Supply Chain Management, Operations, Finance, Others), Deployment Type (On-Premises, Cloud), Organization Size (Small and Medium-Sized Enterprises (SMEs), Large Enterprises)
Countries Covered
U.S., Canada and Mexico in North America, Germany, France, U.K., Netherlands, Switzerland, Belgium, Russia, Italy, Spain, Turkey, Rest of Europe in Europe, China, Japan, India, South Korea, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, Israel, Egypt, South Africa, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), Brazil, Argentina and Rest of South America as part of South America.
Market Players Covered
Accenture (Ireland), Capgemini (France), Cisco Systems (US), Google (US), Intel (US), Lynx Software Technologies (US), Redknee Inc. (Canda), SAP SE (Germany), SQLstream, Inc (US), 1010data (US), Dawex Systems (US), Elevondata Labs Private Limited (India), Gemalto (Netherlands), iConnectiva (India), Mahindra Comviva (India), NETSCOUT (US), Optiva (Canada), Emu Analytics Ltd (UK), and Adastra Corporation (Canada), among others
Market Opportunities
Rise in need to create insights from a pool of data
Ability to directly monetize data by selling raw data, or by taking out insights from analysed and processed data
Rise in the volume of enterprise data
Data Monetization in Telecom Market Dynamics
This section deals with understanding the market drivers, opportunities, restraints and challenges. All of this is discussed in detail as below:
Drivers
Direct Data Monetization
The ability to directly monetize data by selling raw data or taking out insights from analysed and processed data is one of the major factors driving the data monetization in the telecom market. Google monetizes data through real-time bidding while optimizing their platform's experience as they reinvest data into their platform.
Rise in the Volume of Enterprise Data
The rise in enterprise data volume and increased focus to generate new revenue streams accelerate market growth. Also, the growth in awareness towards the potential benefits of data monetization positively impacts the market.
Incorporation of Various Analytics
The use of numerous analytics and technologies among enterprises further influences the market. Ride-hailing companies such as Ola, Uber, and Lyft use location-based analytics to acquire insight about their customer's data that is generally extracted from pick-up and drop-off locations.
Additionally, rapid urbanization, change in lifestyle, surge in investments and increased consumer spending positively impact the data monetization in telecom market.
Opportunities
Furthermore, rise in need to create insights from a pool of data extend profitable opportunities to the market players in the forecast period of 2022 to 2029. According to a report by IBM, only 23% of companies surveyed have been reported to own an enterprise-wide big data strategy. Also, adoption of AI for data processing will further expand the market.
Restraints/Challenges
On the other hand, varying structure of regulatory policies, and lack of organizational capabilities and cultural barriers are expected to obstruct market growth. Also, the quality of data collected by organizations for monetization and privacy and security concerns are projected to challenge the data monetization in the telecom market in 2022-2029.
This data monetization in telecom market report provides details of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on data monetization in telecom market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.
COVID-19 Impact on Data Monetization in Telecom Market
COVID-19 had a positive impact on the data monetization in telecom market due to the rise in number of industry verticals adopting data monetization tools during the outbreak of COVID-19. Numerous industries, especially the telecommunication sector, were deploying data monetization to increase their revenue from the collected data. The data monetization in telecom market is expected to witness high growth in the post-pandemic scenario owing to the rise in awareness regarding the potential benefits of data monetization.
Recent Developments
Microsoft introduced a new Microsoft Azure service in July’2019. This service is a cloud service that assists organizations in sharing their internal data. The company aims to deliver the service for its customers to share data to comply with regulations and privacy policies.
Salesforce announced the acquisition of Tableau in June’2019 to deliver a full view of their consumers across touchpoints by combining the CRM platform.
Global Data Monetization in Telecom Market Scope and Market Size
The data monetization in telecom market is segmented on the basis of component, data type, business function, deployment type and organization type. The growth amongst these segments will help you analyze meager growth segments in the industries and provide the users with a valuable market overview and market insights to help them make strategic decisions for identifying core market applications.
Data Monetization in Telecom Market Regional Analysis/Insights
The data monetization in telecom market is analyzed and market size insights and trends are provided by country, component, data type, business function, deployment type and organization type as referred above.
The countries covered in the data monetization in telecom market report are U.S., Canada and Mexico in North America, Germany, France, U.K., Netherlands, Switzerland, Belgium, Russia, Italy, Spain, Turkey, Rest of Europe in Europe, China, Japan, India, South Korea, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, Israel, Egypt, South Africa, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), Brazil, Argentina and Rest of South America as part of South America.
North America dominates the data monetization in the telecom market due to the adoption of advanced solutions and increased investments within the region.
Asia-Pacific (APAC) is expected to witness significant growth during the forecast period of 2022 to 2029 because of the region's expansion of the telecommunication sector.
The country section of the report also provides individual market impacting factors and changes in regulation in the market domestically that impacts the current and future trends of the market. Data points like down-stream and upstream value chain analysis, technical trends and porter's five forces analysis, case studies are some of the pointers used to forecast the market scenario for individual countries. Also, the presence and availability of global brands and their challenges faced due to large or scarce competition from local and domestic brands, impact of domestic tariffs and trade routes are considered while providing forecast analysis of the country data.
Competitive Landscape and Data Monetization in Telecom Market
The data monetization in telecom market competitive landscape provides details by competitor. Details included are company overview, company financials, revenue generated, market potential, investment in research and development, new market initiatives, global presence, production sites and facilities, production capacities, company strengths and weaknesses, product launch, product width and breadth, application dominance. The above data points provided are only related to the companies' focus related to data monetization in telecom market.
Some of the major players operating in data monetization in telecom market are
Accenture (Ireland)
Capgemini (France)
Cisco Systems (US)
Google (US)
Intel (US)
Lynx Software Technologies (US)
Redknee Inc. (Canda)
SAP SE (Germany)
SQLstream, Inc (US)
1010data (US)
Dawex Systems (US)
Elevondata Labs Private Limited (India)
Gemalto (Netherlands)
iConnectiva (India)
Mahindra Comviva (India)
NETSCOUT (US)
Optiva (Canada)
Emu Analytics Ltd (UK)
Adastra Corporation (Canada)
SKU-55528
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Research Methodology
Data collection and base year analysis are done using data collection modules with large sample sizes. The stage includes obtaining market information or related data through various sources and strategies. It includes examining and planning all the data acquired from the past in advance. It likewise envelops the examination of information inconsistencies seen across different information sources. The market data is analysed and estimated using market statistical and coherent models. Also, market share analysis and key trend analysis are the major success factors in the market report. To know more, please request an analyst call or drop down your inquiry.
The key research methodology used by DBMR research team is data triangulation which involves data mining, analysis of the impact of data variables on the market and primary (industry expert) validation. Data models include Vendor Positioning Grid, Market Time Line Analysis, Market Overview and Guide, Company Positioning Grid, Patent Analysis, Pricing Analysis, Company Market Share Analysis, Standards of Measurement, Global versus Regional and Vendor Share Analysis. To know more about the research methodology, drop in an inquiry to speak to our industry experts.
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