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Global Digital Asset Management Market to reach USD 15.84 billion by the end of 2030.

Global Digital Asset Management Market Size Study & Forecast, by Offering (Solution, Services), by Deployment Mode (On Premises, Cloud), by Business Function (Human Resources (HR), Sales and Marketing, Information Technology (IT), Others), and Regional Analysis, 2023-2030

Product Code: ICTICTI-89722744
Publish Date: 20-10-2023
Page: 200

Global Digital Asset Management Market is valued at approximately USD 4.9 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 15.8% over the forecast period 2023-2030. Digital Asset Management (DAM) is a system or process used by organizations to store, organize, manage, and distribute digital assets effectively. Digital assets refer to any digital content that holds value to the organization, such as images, videos, documents, audio files, graphics, and other multimedia files. DAM solutions help streamline the entire lifecycle of digital assets, from creation and ingestion to storage, retrieval, and distribution. Factors such as rising focus on enhancing the digital experience of customers among enterprises, increase in organizational focus on digital marketing, and growth in the need for controlled access and better security of digital assets to avoid copyright issues are the key factors that are contributing to the global market growth.

In addition, the increasing adoption of cloud-based solutions is directly associated with market demand across the globe. Cloud-based DAM solutions offer scalability and flexibility, making it easier for organizations to expand their digital asset management capabilities as their needs grow. According to a report by DHS, a substantial 86% of critical infrastructure owners and operators within the high-tech sectors have adopted cloud-based solutions. The report has provided insights into the expenditure of various sectors on essential infrastructure through cloud services, projecting a notable rise from USD 152 billion in 2020 to a projected USD 223 billion by the year 2025. Thus, these aforementioned factors are propelling the growth of the Digital Asset Management Market during the estimated period. Moreover, the emergence of AI to automate processes, as well as the integration of advanced encryption technologies to streamline digital trading present various lucrative opportunities over the forecast years. However, the high upfront costs associated with implementation and integration, along with the rising data security and privacy concerns are challenging the market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Digital Asset Management Market study include Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the increasing volume of digital content, the presence of strict compliance and security regulations for managing sensitive content, and rising integration with marketing technologies. Whereas, Asia Pacific is expected to grow at the highest CAGR over the forecast years. The rise in adoption of cloud-based DAM solutions, the rapid expansion of AI and machine learning capabilities in DAM, as well as a surge in demand for video content are significantly propelling the market demand across the region.

Major market players included in this report are:
Open Text Corporation
North Plains Systems (Ignite Enterprise Software Solutions, Inc.)
Oracle Corporation
Widen Enterprises Inc
Cognizant Technology Solutions Corporation
Hewlett Packard Enterprise (HPE) Development LP
International Business Machines Corporation
Dell Technologies Inc
Adobe Inc.

Recent Developments in the Market:
Ø In November 2021, Adobe introduced AEM Assets. The best DAM installation strategies would be covered in Part 2 of AEM Assets. Adobe’s professional services teams assisted clients with the architecture, development, and implementation of digital marketing solutions. Additionally, it offers advice on how to maximize consumers’ investments in digital assets and safeguard brands.
Ø In March 2023, OpenText and Bayer has collaborated to streamline their online business processes. Bayer chose OpenText Business Network Cloud Enterprise as a strategic solution to promote agility and boost operational effectiveness for specific B2B integration tasks across the Consumer Health and Pharmaceuticals businesses.

Global Digital Asset Management Market Report Scope:
ü Historical Data – 2020 – 2021
ü Base Year for Estimation – 2022
ü Forecast period – 2023-2030
ü Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
ü Segments Covered – Offering, Deployment Mode, Business Function, Region
ü Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
ü Customization Scope – Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

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 years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential 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 Offering:

By Deployment Mode:
On Premises

By Business Function:
Human Resources (HR)
Sales and Marketing
Information Technology (IT)

By Region:

North America


Asia Pacific
South Korea

Latin America

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. Digital Asset Management Market, by Region, 2020-2030 (USD Billion)
1.2.2. Digital Asset Management Market, by Offering, 2020-2030 (USD Billion)
1.2.3. Digital Asset Management Market, by Deployment Mode, 2020-2030 (USD Billion)
1.2.4. Digital Asset Management Market, by Business Function, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Digital Asset Management Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Digital Asset Management Market Dynamics
3.1. Digital Asset Management Market Impact Analysis (2020-2030)
3.1.1. Market Drivers Increasing adoption of cloud-based solutions Rising focus on enhancing the digital experience of customers among enterprises
3.1.2. Market Challenges High upfront costs associated with implementation and integration Rising data security and privacy concerns
3.1.3. Market Opportunities Emergence of AI to automate processes Integration of advanced encryption technologies to streamline digital trading
Chapter 4. Global Digital Asset Management 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
4.2. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global Digital Asset Management Market, by Offering
5.1. Market Snapshot
5.2. Global Digital Asset Management Market by Offering, Performance – Potential Analysis
5.3. Global Digital Asset Management Market Estimates & Forecasts by Offering 2020-2030 (USD Billion)
5.4. Digital Asset Management Market, Sub Segment Analysis
5.4.1. Solution
5.4.2. Services
Chapter 6. Global Digital Asset Management Market, by Deployment Mode
6.1. Market Snapshot
6.2. Global Digital Asset Management Market by Deployment Mode, Performance – Potential Analysis
6.3. Global Digital Asset Management Market Estimates & Forecasts by Deployment Mode 2020-2030 (USD Billion)
6.4. Digital Asset Management Market, Sub Segment Analysis
6.4.1. On Premises
6.4.2. Cloud
Chapter 7. Global Digital Asset Management Market, by Business Function
7.1. Market Snapshot
7.2. Global Digital Asset Management Market by Business Function, Performance – Potential Analysis
7.3. Global Digital Asset Management Market Estimates & Forecasts by Business Function 2020-2030 (USD Billion)
7.4. Digital Asset Management Market, Sub Segment Analysis
7.4.1. Human Resources (HR)
7.4.2. Sales and Marketing
7.4.3. Information Technology (IT)
7.4.4. Others
Chapter 8. Global Digital Asset Management Market, Regional Analysis
8.1. Top Leading Countries
8.2. Top Emerging Countries
8.3. Digital Asset Management Market, Regional Market Snapshot
8.4. North America Digital Asset Management Market
8.4.1. U.S. Digital Asset Management Market Offering breakdown estimates & forecasts, 2020-2030 Deployment Mode breakdown estimates & forecasts, 2020-2030 Business Function breakdown estimates & forecasts, 2020-2030
8.4.2. Canada Digital Asset Management Market
8.5. Europe Digital Asset Management Market Snapshot
8.5.1. U.K. Digital Asset Management Market
8.5.2. Germany Digital Asset Management Market
8.5.3. France Digital Asset Management Market
8.5.4. Spain Digital Asset Management Market
8.5.5. Italy Digital Asset Management Market
8.5.6. Rest of Europe Digital Asset Management Market
8.6. Asia-Pacific Digital Asset Management Market Snapshot
8.6.1. China Digital Asset Management Market
8.6.2. India Digital Asset Management Market
8.6.3. Japan Digital Asset Management Market
8.6.4. Australia Digital Asset Management Market
8.6.5. South Korea Digital Asset Management Market
8.6.6. Rest of Asia Pacific Digital Asset Management Market
8.7. Latin America Digital Asset Management Market Snapshot
8.7.1. Brazil Digital Asset Management Market
8.7.2. Mexico Digital Asset Management Market
8.8. Middle East & Africa Digital Asset Management Market
8.8.1. Saudi Arabia Digital Asset Management Market
8.8.2. South Africa Digital Asset Management Market
8.8.3. Rest of Middle East & Africa Digital Asset Management Market

Chapter 9. Competitive Intelligence
9.1. Key Company SWOT Analysis
9.1.1. Company 1
9.1.2. Company 2
9.1.3. Company 3
9.2. Top Market Strategies
9.3. Company Profiles
9.3.1. Open Text Corporation Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
9.3.2. North Plains Systems (Ignite Enterprise Software Solutions, Inc.)
9.3.3. Oracle Corporation
9.3.4. Widen Enterprises Inc
9.3.5. Cognizant Technology Solutions Corporation
9.3.6. Hewlett Packard Enterprise (HPE) Development LP
9.3.7. Aprimo
9.3.8. International Business Machines Corporation
9.3.9. Dell Dell Technologies Inc
9.3.10. Adobe Inc.
Chapter 10. Research Process
10.1. Research Process
10.1.1. Data Mining
10.1.2. Analysis
10.1.3. Market Estimation
10.1.4. Validation
10.1.5. Publishing
10.2. Research Attributes
10.3. 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.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
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:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
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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