Market Name Market Synopsis

Data Monetization Market Size Was Valued at USD 3.47 Billion in 2023, and is Projected to Reach USD 17.22 Billion by 2032, Growing at a CAGR of 19.50% From 2024-2032.

The economic process by which businesses use their data assets to increase revenue, improve business value, and spur innovation is known as the "data monetization market." This market includes a range of approaches and tactics for deriving income from data, such as selling data directly, providing services and goods based on data, and using data insights to optimize internal operations. It includes a wide range of sectors, including technology, retail, healthcare, and finance, where data is turned into focused marketing campaigns, actionable analytics, and enhanced consumer experiences. A wide range of players are involved in the industry, including sellers of technology, analytics software, data providers, and regulatory agencies. These entities all contribute to the ecosystem in which data is viewed as a vital resource and competitive advantage.

• The increasing amount of data being generated across industries has led to a rapid growth in the worldwide data monetization market. This market uses both direct and indirect means to harness the value of data and turn it into a commercial asset. Businesses use data to improve consumer experiences, develop new revenue streams, and strengthen their business models. This rise is further fueled by the widespread use of artificial intelligence (AI), advanced analytics, and Internet of Things (IoT) devices, which allow organizations to extract strategic advantages and actionable insights from their data.
• The trend in the data monetization market towards data-as-a-service (DaaS) offerings and subscription-based models is one of the major developments. With the help of these models, companies may acquire significant datasets and analytical tools by subscribing to data services, all without having to make large upfront investments. By democratizing data access, this strategy gives small and medium-sized businesses (SMEs) the ability to take on bigger businesses. Furthermore, laws pertaining to data security and privacy, including the California Consumer Privacy Act (CCPA) and the General Data Protection Regulation (GDPR), are influencing market dynamics and guaranteeing that data monetization methods adhere to moral and legal standards.
• Leading industrial areas leading the charge in implementing data monetization techniques include finance, healthcare, retail, and telecommunications. Financial institutions use data analytics for credit risk assessment, fraud detection, and customer service personalization. Data is used by healthcare providers to enhance patient outcomes, expedite workflow, and promote medical research. Retailers employ data for targeted marketing, supply chain optimization, and improved consumer interaction. Telecommunications firms make money from data by providing insights into customer behavior and network optimization, thanks to their enormous data libraries.
• The market for data monetization confronts obstacles like poor data quality, expensive implementation costs, and worries about data security and privacy despite the industry's bright future. In order to protect the quality and value of their data, organizations need to invest in strong data governance frameworks and cutting-edge analytical technologies. To overcome these obstacles and realize the full potential of data monetization, cooperation between technology suppliers, data scientists, and business executives is essential.
• In conclusion, the market for data monetization is expected to increase significantly due to the convergence of technology and the growing understanding of data as a vital resource. Businesses in a variety of sectors are using data-driven tactics more frequently in order to obtain a competitive advantage and create new revenue streams. To maintain this growth and win over customers' trust, it will be crucial to solve the issues of data security, privacy, and quality. Innovative company strategies and regulatory compliance will be crucial in determining the market's future course as it develops.

Data Monetization Market Trend Analysis

The Role of AI and ML in Enhancing Data Monetization Strategies

• The integration of artificial intelligence (AI) and machine learning (ML) technologies into data analytics is revolutionizing how businesses approach data monetization. Large volumes of data may be processed by AI and ML algorithms at previously unheard-of speeds, revealing patterns and insights that are invisible to humans. With the help of these technologies, organizations can improve their analytical skills and get a deeper comprehension of their data. Businesses can automate the data analysis process and cut down on the time and resources needed to obtain relevant insights by utilizing AI and ML. Effective decision-making depends on accurate data interpretation, which is ensured by this automation in addition to increased efficiency.
• AI and ML are particularly shown to be very useful in predictive analytics. With the use of these technologies, businesses are able to create highly accurate predictive models that project future trends, consumer behavior, and market dynamics. Retail companies, for instance, can utilize predictive analytics to plan ahead for inventory needs, enhance pricing tactics, and customize marketing campaigns based on the preferences of certain customers. Financial institutions are better able to forecast changes in the market and evaluate credit risk. AI and ML enable firms to remain ahead of the competition and make better strategic decisions by offering a forward-looking viewpoint. By using a proactive approach, businesses may improve operational efficiency and create new revenue streams by monetizing their data more effectively by providing more personalized products and services based on predicted insights.

The Emergence and Impact of Data Marketplaces on Data Monet

• By offering a centralized platform for the exchange of various data kinds, data marketplaces are becoming increasingly popular and changing the landscape of data monetization. These markets serve as virtual crossroads where businesses may safely and effectively acquire and sell data. Data marketplaces provide firms with a wealth of information by combining data from many sources, giving them a competitive advantage. For example, businesses might purchase market research data to guide their strategic planning, or they can purchase customer insights to better personalize their products and services to match market expectations. Due to the removal of conventional obstacles to data collecting, including expensive and time-consuming procedures, organizations of all sizes may now more easily take advantage of data-driven decision-making.
• An increasingly dynamic and networked data economy is being fostered by the emergence of data marketplaces. Data is becoming more and more seen in this new ecosystem as a valuable item that can be exchanged and made money off of. Businesses are being encouraged by this trend to investigate new revenue streams and collaborations that revolve around data sharing. Businesses that possess enormous volumes of proprietary data, for instance, might make money by selling these assets to other businesses that want a certain set of insights. Furthermore, by putting strong security measures and compliance standards in place and making sure that data transactions are carried out lawfully and ethically, data marketplaces foster openness and confidence. Because they know their data is safe and they are according to regulations, businesses are therefore more eager to take part in the data economy. Because businesses can leverage the combined power of shared data to improve operations and achieve greater market success, this collaborative environment is spurring innovation and growth.

Data Monetization Market Segment Analysis:

Data Monetization Market Segmented based on By Component, By  DataType, By  Business Function, By Deployment Type, By Organization Size and By Vertical.

By Component, Tools segment is expected to dominate the market during the forecast period

• The tools segment holds the dominant share in the market due to the increasing need for advanced software and applications to manage and analyze vast amounts of data. As businesses generate more data than ever before, the demand for sophisticated data management tools has surged. These tools offer essential capabilities such as data visualization, predictive analytics, and machine learning, which allow organizations to transform raw data into meaningful insights. Data visualization tools help in creating intuitive and interactive graphical representations of data, making it easier for stakeholders to understand trends, patterns, and anomalies. Predictive analytics leverages historical data to forecast future trends, enabling businesses to make proactive decisions. Machine learning algorithms further enhance these capabilities by learning from data, identifying hidden patterns, and making accurate predictions, which are crucial for optimizing operations, enhancing customer experiences, and driving innovation.
• Moreover, the rapid advancements in technology and the increasing adoption of digital transformation initiatives across various industries have fueled the growth of the tools segment. Businesses are investing heavily in these tools to gain a competitive edge, improve efficiency, and reduce operational costs. The tools segment includes a wide range of software applications, from simple data management tools to complex, integrated analytics platforms. These tools are designed to cater to the diverse needs of businesses across different sectors, such as finance, healthcare, retail, and manufacturing. As organizations continue to recognize the value of data-driven decision-making, the demand for advanced data management and analytics tools is expected to remain robust, cementing the tools segment's dominant position in the market.

By BFSI, Consumer Goods and Retail segment held the largest share in 2023

• Data is widely used by the retail and consumer products industries to enhance many parts of their business processes, improving customer satisfaction and increasing revenue. Inventory management is one of the main uses of data in this vertical. Retailers can optimize stock levels, estimate demand precisely, and guarantee prompt inventory replenishment by utilizing data analytics. This enhances operational effectiveness and lowers inventory management expenses in addition to helping to prevent stockouts and overstock scenarios. Retailers can stay competitive in a changing market by quickly adapting to shifts in customer demand patterns, seasonal variations, and industry trends with the use of real-time data analytics.
• In the retail and consumer products industries, sales forecasting is yet another crucial area where data is essential. Retailers can more accurately forecast future sales volumes by examining past sales data, market patterns, and outside variables like the state of the economy and rival activity. This enables them to optimize resources and maximize income potential by modifying marketing strategy, promotional campaigns, and inventory levels as necessary. Retailers can more successfully target particular client categories, find growth possibilities, and adjust product offerings to suit changing consumer tastes by using data-driven sales forecasting.
• Furthermore, personalized marketing is transforming the way retail and consumer products companies interact with their clientele. Retailers can offer targeted promotions, build tailored shopping experiences, and make product recommendations based on customer behavior and individual interests by utilizing data analytics. In addition to increasing client satisfaction, this degree of customisation increases conversion rates and cultivates customer loyalty. Retailers are able to better target their customers with timely and relevant messaging by using sophisticated data analytics approaches including segmentation, predictive modeling, and machine learning algorithms.

Data Monetization Market Regional Insights:

North America is Expected to Dominate the Market Over the Forecast period

• The market for data monetization is dominated by North America, mostly because of the region's large investments in artificial intelligence (AI) and data analytics, as well as its rapid adoption of cutting-edge technology. The population of the region is tech-savvy and has established digital infrastructure, which makes the region a good place for data-driven business models. Businesses from a variety of industries, such as manufacturing, retail, finance, and healthcare, are using data analytics more and more to improve decision-making, boost operational effectiveness, and customize customer experiences. Large volumes of data have been produced by the spread of IoT devices and developments in AI and machine learning, giving organizations hitherto unheard-of prospects for revenue. This technological skill is especially demonstrated by American businesses, who are pioneers in incorporating cutting-edge technologies into their daily operations.
• Major technological companies like Microsoft, Amazon, and Google are present in North America, which further fuels the market's growth. These companies offer advanced analytics tools that help businesses derive meaningful insights from their data, in addition to cloud services that make data processing and storage easier. The region's success has been largely attributed to the early adoption of cloud services, which provide real-time analytics and scalable data solutions. Additionally, strict data privacy laws like the California Consumer Privacy Act (CCPA) are having an impact on how businesses manage and monetize data. These rules force companies to guarantee strong data protection protocols and to be open and honest about their data operations. This builds customer confidence and promotes moral data monetization methods. Because of this, American businesses are not only at the forefront of technology adoption but are also establishing industry standards for data security and privacy in the data monetization space.

Active Key Players in the Data Monetization Market

• Microsoft Corporation (Microsoft),
• Salesforce.com,Inc. (Salesforce),
• Oracle Corporation (Oracle),
• SAP SE (SAP),
• SAS Institute Inc. (SAS),
• Sisense Inc, (Sisense),
• TIBCO Software Inc. (TIBCO Software),
• IBM Corporation (IBM),
• QlikTech International AB (Qlik),
• Domo, Inc. (Domo),
• Accenture plc (Accenture),
• Virtusa Corporation (Virtusa),
• Infosys Limited (Infosys),
• Other Key Players

Key Industry Developments in the Data Monetization Market:

• In April 2022, The Eaxct company announced an OEM partnership with Exact to serve small and mid-sized businesses across the globe with Qlik Sense enterprise-grade analytics capabilities.
• In March 2022, Domo has made a new agreement with Moss Adams, one of the nation's largest accounting, consulting, and wealth management firms. This partnership will enable Moss Adams to assist its clients in implementing analytics leveraging Domo's modern BI platform to further enhance its client-centric strategy.
• In February 2022, Yieldbroker, the licensed electronic trading platform for Australian and New Zealand debt securities and derivatives has collaborated with Sisense to use its AI-driven interactive data visualization capabilities for Yieldbroker’s new data and analytics product, “YBEdge.”

Chapter 1: Introduction
 1.1 Scope and Coverage

Chapter 2:Executive Summary

Chapter 3: Market Landscape
 3.1 Market Dynamics
  3.1.1 Drivers
  3.1.2 Restraints
  3.1.3 Opportunities
  3.1.4 Challenges
 3.2 Market Trend Analysis
 3.3 PESTLE Analysis
 3.4 Porter's Five Forces Analysis
 3.5 Industry Value Chain Analysis
 3.6 Ecosystem
 3.7 Regulatory Landscape
 3.8 Price Trend Analysis
 3.9 Patent Analysis
 3.10 Technology Evolution
 3.11 Investment Pockets
 3.12 Import-Export Analysis

Chapter 4: Data Monetization Market by Component
 4.1 Data Monetization Market Snapshot and Growth Engine
 4.2 Data Monetization Market Overview
 4.3 Tools
  4.3.1 Introduction and Market Overview
  4.3.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  4.3.3 Key Market Trends, Growth Factors and Opportunities
  4.3.4 Tools: Geographic Segmentation Analysis
 4.4 Services
  4.4.1 Introduction and Market Overview
  4.4.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  4.4.3 Key Market Trends, Growth Factors and Opportunities
  4.4.4 Services: Geographic Segmentation Analysis
 4.5 Consulting
  4.5.1 Introduction and Market Overview
  4.5.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  4.5.3 Key Market Trends, Growth Factors and Opportunities
  4.5.4 Consulting: Geographic Segmentation Analysis
 4.6 Support & Maintenance & Implementation & Integration
  4.6.1 Introduction and Market Overview
  4.6.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  4.6.3 Key Market Trends, Growth Factors and Opportunities
  4.6.4 Support & Maintenance & Implementation & Integration: Geographic Segmentation Analysis

Chapter 5: Data Monetization Market by DataType
 5.1 Data Monetization Market Snapshot and Growth Engine
 5.2 Data Monetization Market Overview
 5.3 Customer Data
  5.3.1 Introduction and Market Overview
  5.3.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  5.3.3 Key Market Trends, Growth Factors and Opportunities
  5.3.4 Customer Data: Geographic Segmentation Analysis
 5.4 Product Data
  5.4.1 Introduction and Market Overview
  5.4.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  5.4.3 Key Market Trends, Growth Factors and Opportunities
  5.4.4 Product Data: Geographic Segmentation Analysis
 5.5 Financial Data & Supplier Data
  5.5.1 Introduction and Market Overview
  5.5.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  5.5.3 Key Market Trends, Growth Factors and Opportunities
  5.5.4 Financial Data & Supplier Data: Geographic Segmentation Analysis

Chapter 6: Data Monetization Market by Business Function
 6.1 Data Monetization Market Snapshot and Growth Engine
 6.2 Data Monetization Market Overview
 6.3 Supply Chain Management
  6.3.1 Introduction and Market Overview
  6.3.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  6.3.3 Key Market Trends, Growth Factors and Opportunities
  6.3.4 Supply Chain Management: Geographic Segmentation Analysis
 6.4 Sales & Marketing
  6.4.1 Introduction and Market Overview
  6.4.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  6.4.3 Key Market Trends, Growth Factors and Opportunities
  6.4.4 Sales & Marketing: Geographic Segmentation Analysis
 6.5 Operations
  6.5.1 Introduction and Market Overview
  6.5.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  6.5.3 Key Market Trends, Growth Factors and Opportunities
  6.5.4 Operations: Geographic Segmentation Analysis
 6.6 Finance
  6.6.1 Introduction and Market Overview
  6.6.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  6.6.3 Key Market Trends, Growth Factors and Opportunities
  6.6.4 Finance: Geographic Segmentation Analysis
 6.7 Others (Legal
  6.7.1 Introduction and Market Overview
  6.7.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  6.7.3 Key Market Trends, Growth Factors and Opportunities
  6.7.4 Others (Legal: Geographic Segmentation Analysis
 6.8 R&D
  6.8.1 Introduction and Market Overview
  6.8.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  6.8.3 Key Market Trends, Growth Factors and Opportunities
  6.8.4 R&D: Geographic Segmentation Analysis
 6.9 & HR)
  6.9.1 Introduction and Market Overview
  6.9.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  6.9.3 Key Market Trends, Growth Factors and Opportunities
  6.9.4 & HR): Geographic Segmentation Analysis

Chapter 7: Data Monetization Market by Deployment Type
 7.1 Data Monetization Market Snapshot and Growth Engine
 7.2 Data Monetization Market Overview
 7.3 On-premises & Cloud
  7.3.1 Introduction and Market Overview
  7.3.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  7.3.3 Key Market Trends, Growth Factors and Opportunities
  7.3.4 On-premises & Cloud: Geographic Segmentation Analysis

Chapter 8: Data Monetization Market by Organization Size
 8.1 Data Monetization Market Snapshot and Growth Engine
 8.2 Data Monetization Market Overview
 8.3 Small & Medium-Sized Enterprises(SMEs) & Large Enterprises
  8.3.1 Introduction and Market Overview
  8.3.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  8.3.3 Key Market Trends, Growth Factors and Opportunities
  8.3.4 Small & Medium-Sized Enterprises(SMEs) & Large Enterprises: Geographic Segmentation Analysis

Chapter 9: Data Monetization Market by Vertical
 9.1 Data Monetization Market Snapshot and Growth Engine
 9.2 Data Monetization Market Overview
 9.3 BFSI
  9.3.1 Introduction and Market Overview
  9.3.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  9.3.3 Key Market Trends, Growth Factors and Opportunities
  9.3.4 BFSI: Geographic Segmentation Analysis
 9.4 Telecom
  9.4.1 Introduction and Market Overview
  9.4.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  9.4.3 Key Market Trends, Growth Factors and Opportunities
  9.4.4 Telecom: Geographic Segmentation Analysis
 9.5 Consumer Goods & Retail
  9.5.1 Introduction and Market Overview
  9.5.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  9.5.3 Key Market Trends, Growth Factors and Opportunities
  9.5.4 Consumer Goods & Retail: Geographic Segmentation Analysis
 9.6 Media & Entertainment
  9.6.1 Introduction and Market Overview
  9.6.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  9.6.3 Key Market Trends, Growth Factors and Opportunities
  9.6.4 Media & Entertainment: Geographic Segmentation Analysis
 9.7 Manufacturing
  9.7.1 Introduction and Market Overview
  9.7.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  9.7.3 Key Market Trends, Growth Factors and Opportunities
  9.7.4 Manufacturing: Geographic Segmentation Analysis
 9.8 IT
  9.8.1 Introduction and Market Overview
  9.8.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  9.8.3 Key Market Trends, Growth Factors and Opportunities
  9.8.4 IT: Geographic Segmentation Analysis
 9.9 Transportation & Logistics
  9.9.1 Introduction and Market Overview
  9.9.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  9.9.3 Key Market Trends, Growth Factors and Opportunities
  9.9.4 Transportation & Logistics: Geographic Segmentation Analysis
 9.10 Energy & Utilities
  9.10.1 Introduction and Market Overview
  9.10.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  9.10.3 Key Market Trends, Growth Factors and Opportunities
  9.10.4 Energy & Utilities: Geographic Segmentation Analysis
 9.11 Healthcare
  9.11.1 Introduction and Market Overview
  9.11.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  9.11.3 Key Market Trends, Growth Factors and Opportunities
  9.11.4 Healthcare: Geographic Segmentation Analysis
 9.12 Others
  9.12.1 Introduction and Market Overview
  9.12.2 Historic and Forecasted Market Size in Value USD and Volume Units (2017-2032F)
  9.12.3 Key Market Trends, Growth Factors and Opportunities
  9.12.4 Others: Geographic Segmentation Analysis

Chapter 10: Company Profiles and Competitive Analysis
 10.1 Competitive Landscape
  10.1.1 Competitive Benchmarking
  10.1.2 Data Monetization Market Share by Manufacturer (2023)
  10.1.3 Industry BCG Matrix
  10.1.4 Heat Map Analysis
  10.1.5 Mergers and Acquisitions
  
 10.2 MICROSOFT CORPORATION
  10.2.1 Company Overview
  10.2.2 Key Executives
  10.2.3 Company Snapshot
  10.2.4 Role of the Company in the Market
  10.2.5 Sustainability and Social Responsibility
  10.2.6 Operating Business Segments
  10.2.7 Product Portfolio
  10.2.8 Business Performance
  10.2.9 Key Strategic Moves and Recent Developments
  10.2.10 SWOT Analysis
 10.3 SALESFORCE COM INC
 10.4 ORACLE CORPORATION
 10.5 SAP SE
 10.6 SAS INSTITUTE INC
 10.7 SISENSE INC
 10.8 TIBCO SOFTWARE INC
 10.9 IBM CORPORATION
 10.10 QLIKTECH INTERNATIONAL AB
 10.11 DOMO INC
 10.12 ACCENTURE PLC
 10.13 VIRTUSA CORPORATION
 10.14 INFOSYS LIMITED
 10.15 OTHER KEY PLAYERS

Chapter 11: Global Data Monetization Market By Region
 11.1 Overview
 11.2. North America Data Monetization Market
  11.2.1 Key Market Trends, Growth Factors and Opportunities
  11.2.2 Top Key Companies
  11.2.3 Historic and Forecasted Market Size by Segments
  11.2.4 Historic and Forecasted Market Size By Component
   11.2.4.1 Tools
   11.2.4.2 Services
   11.2.4.3 Consulting
   11.2.4.4 Support & Maintenance & Implementation & Integration
  11.2.5 Historic and Forecasted Market Size By DataType
   11.2.5.1 Customer Data
   11.2.5.2 Product Data
   11.2.5.3 Financial Data & Supplier Data
  11.2.6 Historic and Forecasted Market Size By Business Function
   11.2.6.1 Supply Chain Management
   11.2.6.2 Sales & Marketing
   11.2.6.3 Operations
   11.2.6.4 Finance
   11.2.6.5 Others (Legal
   11.2.6.6 R&D
   11.2.6.7 & HR)
  11.2.7 Historic and Forecasted Market Size By Deployment Type
   11.2.7.1 On-premises & Cloud
  11.2.8 Historic and Forecasted Market Size By Organization Size
   11.2.8.1 Small & Medium-Sized Enterprises(SMEs) & Large Enterprises
  11.2.9 Historic and Forecasted Market Size By Vertical
   11.2.9.1 BFSI
   11.2.9.2 Telecom
   11.2.9.3 Consumer Goods & Retail
   11.2.9.4 Media & Entertainment
   11.2.9.5 Manufacturing
   11.2.9.6 IT
   11.2.9.7 Transportation & Logistics
   11.2.9.8 Energy & Utilities
   11.2.9.9 Healthcare
   11.2.9.10 Others
  11.2.10 Historic and Forecast Market Size by Country
   11.2.10.1 US
   11.2.10.2 Canada
   11.2.10.3 Mexico
 11.3. Eastern Europe Data Monetization Market
  11.3.1 Key Market Trends, Growth Factors and Opportunities
  11.3.2 Top Key Companies
  11.3.3 Historic and Forecasted Market Size by Segments
  11.3.4 Historic and Forecasted Market Size By Component
   11.3.4.1 Tools
   11.3.4.2 Services
   11.3.4.3 Consulting
   11.3.4.4 Support & Maintenance & Implementation & Integration
  11.3.5 Historic and Forecasted Market Size By DataType
   11.3.5.1 Customer Data
   11.3.5.2 Product Data
   11.3.5.3 Financial Data & Supplier Data
  11.3.6 Historic and Forecasted Market Size By Business Function
   11.3.6.1 Supply Chain Management
   11.3.6.2 Sales & Marketing
   11.3.6.3 Operations
   11.3.6.4 Finance
   11.3.6.5 Others (Legal
   11.3.6.6 R&D
   11.3.6.7 & HR)
  11.3.7 Historic and Forecasted Market Size By Deployment Type
   11.3.7.1 On-premises & Cloud
  11.3.8 Historic and Forecasted Market Size By Organization Size
   11.3.8.1 Small & Medium-Sized Enterprises(SMEs) & Large Enterprises
  11.3.9 Historic and Forecasted Market Size By Vertical
   11.3.9.1 BFSI
   11.3.9.2 Telecom
   11.3.9.3 Consumer Goods & Retail
   11.3.9.4 Media & Entertainment
   11.3.9.5 Manufacturing
   11.3.9.6 IT
   11.3.9.7 Transportation & Logistics
   11.3.9.8 Energy & Utilities
   11.3.9.9 Healthcare
   11.3.9.10 Others
  11.3.10 Historic and Forecast Market Size by Country
   11.3.10.1 Bulgaria
   11.3.10.2 The Czech Republic
   11.3.10.3 Hungary
   11.3.10.4 Poland
   11.3.10.5 Romania
   11.3.10.6 Rest of Eastern Europe
 11.4. Western Europe Data Monetization Market
  11.4.1 Key Market Trends, Growth Factors and Opportunities
  11.4.2 Top Key Companies
  11.4.3 Historic and Forecasted Market Size by Segments
  11.4.4 Historic and Forecasted Market Size By Component
   11.4.4.1 Tools
   11.4.4.2 Services
   11.4.4.3 Consulting
   11.4.4.4 Support & Maintenance & Implementation & Integration
  11.4.5 Historic and Forecasted Market Size By DataType
   11.4.5.1 Customer Data
   11.4.5.2 Product Data
   11.4.5.3 Financial Data & Supplier Data
  11.4.6 Historic and Forecasted Market Size By Business Function
   11.4.6.1 Supply Chain Management
   11.4.6.2 Sales & Marketing
   11.4.6.3 Operations
   11.4.6.4 Finance
   11.4.6.5 Others (Legal
   11.4.6.6 R&D
   11.4.6.7 & HR)
  11.4.7 Historic and Forecasted Market Size By Deployment Type
   11.4.7.1 On-premises & Cloud
  11.4.8 Historic and Forecasted Market Size By Organization Size
   11.4.8.1 Small & Medium-Sized Enterprises(SMEs) & Large Enterprises
  11.4.9 Historic and Forecasted Market Size By Vertical
   11.4.9.1 BFSI
   11.4.9.2 Telecom
   11.4.9.3 Consumer Goods & Retail
   11.4.9.4 Media & Entertainment
   11.4.9.5 Manufacturing
   11.4.9.6 IT
   11.4.9.7 Transportation & Logistics
   11.4.9.8 Energy & Utilities
   11.4.9.9 Healthcare
   11.4.9.10 Others
  11.4.10 Historic and Forecast Market Size by Country
   11.4.10.1 Germany
   11.4.10.2 UK
   11.4.10.3 France
   11.4.10.4 Netherlands
   11.4.10.5 Italy
   11.4.10.6 Russia
   11.4.10.7 Spain
   11.4.10.8 Rest of Western Europe
 11.5. Asia Pacific Data Monetization Market
  11.5.1 Key Market Trends, Growth Factors and Opportunities
  11.5.2 Top Key Companies
  11.5.3 Historic and Forecasted Market Size by Segments
  11.5.4 Historic and Forecasted Market Size By Component
   11.5.4.1 Tools
   11.5.4.2 Services
   11.5.4.3 Consulting
   11.5.4.4 Support & Maintenance & Implementation & Integration
  11.5.5 Historic and Forecasted Market Size By DataType
   11.5.5.1 Customer Data
   11.5.5.2 Product Data
   11.5.5.3 Financial Data & Supplier Data
  11.5.6 Historic and Forecasted Market Size By Business Function
   11.5.6.1 Supply Chain Management
   11.5.6.2 Sales & Marketing
   11.5.6.3 Operations
   11.5.6.4 Finance
   11.5.6.5 Others (Legal
   11.5.6.6 R&D
   11.5.6.7 & HR)
  11.5.7 Historic and Forecasted Market Size By Deployment Type
   11.5.7.1 On-premises & Cloud
  11.5.8 Historic and Forecasted Market Size By Organization Size
   11.5.8.1 Small & Medium-Sized Enterprises(SMEs) & Large Enterprises
  11.5.9 Historic and Forecasted Market Size By Vertical
   11.5.9.1 BFSI
   11.5.9.2 Telecom
   11.5.9.3 Consumer Goods & Retail
   11.5.9.4 Media & Entertainment
   11.5.9.5 Manufacturing
   11.5.9.6 IT
   11.5.9.7 Transportation & Logistics
   11.5.9.8 Energy & Utilities
   11.5.9.9 Healthcare
   11.5.9.10 Others
  11.5.10 Historic and Forecast Market Size by Country
   11.5.10.1 China
   11.5.10.2 India
   11.5.10.3 Japan
   11.5.10.4 South Korea
   11.5.10.5 Malaysia
   11.5.10.6 Thailand
   11.5.10.7 Vietnam
   11.5.10.8 The Philippines
   11.5.10.9 Australia
   11.5.10.10 New Zealand
   11.5.10.11 Rest of APAC
 11.6. Middle East & Africa Data Monetization Market
  11.6.1 Key Market Trends, Growth Factors and Opportunities
  11.6.2 Top Key Companies
  11.6.3 Historic and Forecasted Market Size by Segments
  11.6.4 Historic and Forecasted Market Size By Component
   11.6.4.1 Tools
   11.6.4.2 Services
   11.6.4.3 Consulting
   11.6.4.4 Support & Maintenance & Implementation & Integration
  11.6.5 Historic and Forecasted Market Size By DataType
   11.6.5.1 Customer Data
   11.6.5.2 Product Data
   11.6.5.3 Financial Data & Supplier Data
  11.6.6 Historic and Forecasted Market Size By Business Function
   11.6.6.1 Supply Chain Management
   11.6.6.2 Sales & Marketing
   11.6.6.3 Operations
   11.6.6.4 Finance
   11.6.6.5 Others (Legal
   11.6.6.6 R&D
   11.6.6.7 & HR)
  11.6.7 Historic and Forecasted Market Size By Deployment Type
   11.6.7.1 On-premises & Cloud
  11.6.8 Historic and Forecasted Market Size By Organization Size
   11.6.8.1 Small & Medium-Sized Enterprises(SMEs) & Large Enterprises
  11.6.9 Historic and Forecasted Market Size By Vertical
   11.6.9.1 BFSI
   11.6.9.2 Telecom
   11.6.9.3 Consumer Goods & Retail
   11.6.9.4 Media & Entertainment
   11.6.9.5 Manufacturing
   11.6.9.6 IT
   11.6.9.7 Transportation & Logistics
   11.6.9.8 Energy & Utilities
   11.6.9.9 Healthcare
   11.6.9.10 Others
  11.6.10 Historic and Forecast Market Size by Country
   11.6.10.1 Turkey
   11.6.10.2 Bahrain
   11.6.10.3 Kuwait
   11.6.10.4 Saudi Arabia
   11.6.10.5 Qatar
   11.6.10.6 UAE
   11.6.10.7 Israel
   11.6.10.8 South Africa
 11.7. South America Data Monetization Market
  11.7.1 Key Market Trends, Growth Factors and Opportunities
  11.7.2 Top Key Companies
  11.7.3 Historic and Forecasted Market Size by Segments
  11.7.4 Historic and Forecasted Market Size By Component
   11.7.4.1 Tools
   11.7.4.2 Services
   11.7.4.3 Consulting
   11.7.4.4 Support & Maintenance & Implementation & Integration
  11.7.5 Historic and Forecasted Market Size By DataType
   11.7.5.1 Customer Data
   11.7.5.2 Product Data
   11.7.5.3 Financial Data & Supplier Data
  11.7.6 Historic and Forecasted Market Size By Business Function
   11.7.6.1 Supply Chain Management
   11.7.6.2 Sales & Marketing
   11.7.6.3 Operations
   11.7.6.4 Finance
   11.7.6.5 Others (Legal
   11.7.6.6 R&D
   11.7.6.7 & HR)
  11.7.7 Historic and Forecasted Market Size By Deployment Type
   11.7.7.1 On-premises & Cloud
  11.7.8 Historic and Forecasted Market Size By Organization Size
   11.7.8.1 Small & Medium-Sized Enterprises(SMEs) & Large Enterprises
  11.7.9 Historic and Forecasted Market Size By Vertical
   11.7.9.1 BFSI
   11.7.9.2 Telecom
   11.7.9.3 Consumer Goods & Retail
   11.7.9.4 Media & Entertainment
   11.7.9.5 Manufacturing
   11.7.9.6 IT
   11.7.9.7 Transportation & Logistics
   11.7.9.8 Energy & Utilities
   11.7.9.9 Healthcare
   11.7.9.10 Others
  11.7.10 Historic and Forecast Market Size by Country
   11.7.10.1 Brazil
   11.7.10.2 Argentina
   11.7.10.3 Rest of SA

Chapter 12 Analyst Viewpoint and Conclusion
12.1 Recommendations and Concluding Analysis
12.2 Potential Market Strategies

Chapter 13 Research Methodology
13.1 Research Process
13.2 Primary Research
13.3 Secondary Research