Global Data Monetization Market (2022 to 2027) – Increasing Need to Create Insights from a Pool of Data Presents Opportunties

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DUBLIN, Nov. 8, 2022 /PRNewswire/ — The “Data Monetization Market by Component (Tools and Services), Data Type (Customer Data, Financial Data), Business Function, Deployment Type (On-Premises and Cloud), Organization Size, Industry Vertical, and Region – Global Forecast to 2027” report has been added to  ResearchAndMarkets.com’s offering.

The data monetization market size is expected to grow from USD 2.9 billion in 2022 to USD 7.3 billion by 2027, at a Compound Annual Growth Rate (CAGR) of 19.5% during the forecast period. The increase in volume of data generation and lower cost of data storage, rapid adoption of advanced analytics and visualization are a few factors driving the growth of the data monetization market.

The services can help organizations reduce costs by applying effective data maintenance strategies

Services form an integral part of the data monetization software life cycle. Services assist the software functionalities, ranging from its deployment to management, such as implementation and integration, training and consultation, product upgradation, and support and maintenance. The complex nature of data monetization tools and solutions is expected to boost the demand for data monetization services. The services covered in this section are consulting, support and maintenance, and implementation. These services assist organizations in easily deploying data monetization tools on their premises or cloud.

The capability to capture emerging opportunities to generate new revenue and profit streams using consulting services is the major factor driving the adoption of consulting data monetization services

Service providers offer consulting services to help their clients in implementing new methodologies for recognizing additional revenue streams from the existing data. Thus, clients can use massive data sets to build a foundation for new products that they can then sell at a profit to other companies, which would benefit from data intelligence

Data monetization tools enable companies to determine their revenue and profitability and analyze their business segments.

Financial data constitutes of historical and current data related to financial transactions of enterprises. These transactions include income, expenses, bank balance, contracts, and other financial data. The increasing amount of valuable financial data through internal and external sources and special online transactions is expected to boost the adoption of financial data monetization.

The increasing need to launch data-driven marketing campaigns to improve brand equity is the major factor driving the data monetization market growth

Data provides a way to evaluate the performance of marketing campaigns, content, programs, and employees, among others. Surface-level data such as sales figures is capable of providing product performance. Companies can utilize sales and marketing data to make decisions about exiting a product from a particular market and developing new products in the market. Data is the epicenter of every department in an organization. It facilitates immediate decision-making and paves the way for innovative products.

Cloud-based data monetization tools offer quick implementation, which is expected to drive the adoption of cloud-based data monetization tools.

In recent times, due to the increased adoption of data-driven decision-making and advanced analytics, organizations have started to adopt data monetization solutions. SMEs are majorly moving toward the adoption of the cloud deployment type, due to its major benefits such as lower costs, no requirement of manpower for hardware maintenance, faster and efficient results, and complete flexibility and scalability, which result in reduced Operational Expenditure (OPEX) and CAPEX.

The need for government compliance and regulatory requirements related to managing organizational data would increase the adoption of data monetization among SMEs.

The intense competitive market scenario has encouraged SMEs to invest in data monetization tools and services, and derive insights from a large pool of data for their business growth. As compared to large enterprises, the SMEs face resource crunch and require cost-effective methods to solve complexities for better cost optimization of their assets and requirements.

Data monetization in the media and entertainment industry has a specific importance in the overall business operations and is expected to deliver a higher RoI

The media and entertainment industry vertical is witnessing a dramatic shift from the traditional content-centric world to the customer-centric world. Thus, understanding customer preferences and anticipating customers’ demand have become important for efficient content management, financial performance, and profitability. 

North America to dominate the data monetization market in 2022

The presence of two major economies in North America: the US and Canada are expected to boost the adoption of data monetization tools in the region. Moreover, the end-use industries in the region such as BFSI and retail are focusing on improving customer experience and reducing sales cycle, which is expected to drive the market during the forecast period. The adoption of the data monetization solution is expected to be the highest in North America due to the rapid adoption of data monetization tools and services among insight-intensive enterprises in this region as compared to other regions.

Key Topics Covered:

1 Introduction



2 Research Methodology



3 Executive Summary



4 Premium Insights

4.1 Brief Overview of Data Monetization Market

4.2 Market, by Component, 2022 Vs. 2027

4.3 Market, by Services, 2022 Vs. 2027

4.4 Market, by Data Type, 2022 Vs. 2027

4.5 Market, by Deployment Type, 2022 Vs. 2027

4.6 Market, by Organization Size, 2022 Vs. 2027

4.7 Data Monetization Market, by Business Function, 2022 Vs. 2027

4.8 Market, by Industry Vertical, 2022 Vs. 2027

4.9 Market – Investment Scenario



5 Market Overview and Industry Trends


5.1 Introduction

5.2 Market Dynamics

5.2.1 Drivers

5.2.1.1 Increase in Volume of Data Generation and Lower Cost of Data Storage

5.2.1.2 Rapid Adoption of Advanced Analytics and Visualization

5.2.1.3 Increase in Use of External Data Sources

5.2.1.4 Growth in the Adoption of Data-Driven Decision-Making

5.2.1.5 Rise in Business Data Volume and Variety

5.2.2 Restraints

5.2.2.1 Varying Structure of Regulatory Policies

5.2.2.2 Lack of 0Rganizational Capabilities and Cultural Barriers

5.2.3 Opportunities

5.2.3.1 Increasing Need to Create Insights from a Pool of Data

5.2.3.2 Rising Adoption of AI for Data Processing

5.2.4 Challenges

5.2.4.1 Quality of Data Collected by Organizations for Monetization

5.2.4.2 Privacy and Security Concerns

5.2.4.3 Increase in Complexities in Data Structures

5.3 Ecosystem

5.4 Supply Chain Analysis

5.5 Types of Data Monetization

5.5.1 Direct Data Monetization

5.5.2 Indirect Data Monetization

5.6 Technological Analysis

5.6.1 Data as a Service

5.6.2 Insight as a Service

5.6.3 Analytics-Enabled Platform as a Service

5.6.4 Embedded Analytics

5.7 COVID-19 Driven Market Dynamics

5.7.1 Drivers and Opportunities

5.7.2 Restraints and Challenges

5.8 Patent Analysis

5.9 Case Study Analysis

5.9.1 Case Study 1: to Improve the Accuracy of Customer Churn Prediction Through New Models, and Also Improve the Data Monetization Initiative

5.9.2 Case Study 2: to Utilize the Available Data and Gain a Competitive Advantage in the Market

5.9.3 Case Study 3: to Enhance the Safety and Manage the Huge Amount of Data Generated by Key Performance Indicators (Kpis) Used for Constant Reporting on Safety

5.9.4 Case Study 4: to Provide a Complete View of Business Performance and Share the Information with Its Employees in Real-Time Across Finance, Hcm, Workforce Management, and Asset Management Departments.

5.9.5 Case Study 5: to Find Out Inefficiencies in the Healthcare Chain on a Per Patient Basis

5.10 Average Selling Price: Data Monetization Market

5.11 Tariff and Regulatory Landscape



6 Data Monetization Market, by Component


6.1 Introduction

6.1.1 Component: Market Drivers

6.1.2 Component: COVID-19 Impact

6.2 Tools

6.3 Services

6.3.1 Support and Maintenance

6.3.2 Consulting

6.3.3 Implementation and Integration



7 Data Monetization Market, by Data Type


7.1 Introduction

7.1.1 Data Type: Market Drivers

7.1.2 Data Type: COVID-19 Impact

7.2 Customer Data

7.3 Product Data

7.4 Financial Data

7.5 Supplier Data



8 Data Monetization Market, by Business Function


8.1 Introduction

8.1.1 Business Function: Market Drivers

8.1.2 Business Function: COVID-19 Impact

8.2 Sales and Marketing

8.3 Supply Chain Management

8.4 Operations

8.5 Finance

8.6 Others



9 Data Monetization Market, by Deployment Type


9.1 Introduction

9.1.1 Deployment Type: Market Drivers

9.1.2 Deployment Type: COVID-19 Impact

9.2 Cloud

9.3 On-Premises



10 Data Monetization Market, by Organization Size


10.1 Introduction

10.1.1 Organization Size: Market Drivers

10.1.2 Organization Size: COVID-19 Impact

10.2 Large Enterprises

10.3 Small and Medium-Sized Enterprises



11 Data Monetization Market, by Industry Vertical


11.1 Introduction

11.1.1 Industry Vertical: Market Drivers

11.1.2 Industry Vertical: COVID-19 Impact

11.2 Banking, Financial Services, and Insurance

11.3 Telecommunication

11.4 Consumer Goods and Retail

11.5 Information Technology

11.6 Healthcare

11.7 Manufacturing

11.8 Media and Entertainment

11.9 Transportation and Logistics

11.10 Energy and Utilities

11.11 Others



12 Data Monetization Market, by Region



13 Competitive Landscape

13.1 Introduction

13.2 Market Share Analysis

13.3 Market Ranking

13.4 Historical Revenue Analysis of Leading Players

13.5 Key Market Developments

13.5.1 New Launches

13.6 Company Evaluation Quadrant

13.6.1 Stars

13.6.2 Emerging Leaders

13.6.3 Pervasive Players

13.6.4 Participants



14 Company Profiles


14.1 Introduction

14.2 Key Companies

14.2.1 Microsoft

14.2.2 Oracle

14.2.3 Salesforce

14.2.4 Sas

14.2.5 Tibco Software

14.2.6 IBM

14.2.7 Qlik

14.2.8 Sap

14.2.9 Looker

14.2.10 Thoughtspot

14.2.11 Sisense

14.2.12 Domo

14.2.13 Accenture

14.2.14 Virtusa

14.2.15 Infosys

14.2.16 1010Data

14.2.17 Infor

14.2.18 Reltio

14.2.19 Datarobot

14.2.20 Openwave Mobility

14.2.21 Netscout

14.2.22 Adastra

14.2.23 Optiva

14.2.24 Ness

14.2.25 Comviva

14.3 Startup/SME Profiles

14.3.1 Monetize

14.3.2 Elevondata

14.3.3 Emu Analytics

14.3.4 Narrative



15 Adjacent Market



16 Appendix

For more information about this report visit https://www.researchandmarkets.com/r/3qe3ju

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