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Global Internet of Behaviors (IoB) Market to reach USD XX billion by the end of 2029

Global Internet of Behaviors (IoB) Market Size study & Forecast, by Application (Advertising Campaign, Digital Marketing, Content Delivery, Brand Promotion), By Enterprise Size (Small & Medium Enterprises (SMEs), Large Enterprises), By End-Use Industry (BFSI, Telecom and IT, Media and Entertainment, Tourism & Travel, Other) and Regional Analysis, 2022-2029

Product Code: ICTICTI-69185740
Publish Date: 29-01-2023
Page: 200

Global Internet of Behaviors (IoB) Market is valued at approximately USD XX billion in 2021 and is anticipated to grow with a healthy growth rate of more than 22% over the forecast period 2022-2029. Internet of Behaviors (IoB) refers to the collection and use of data to access consumer behaviors. Data collected from different devices including Wearable technologies, individual online activities, and household electrical devices, is utilized to gather information about user behavior and interests. Moreover, IoB combines three fields including behavioral science, edge analytics and the Internet of Things (IoT). This data is further used by marketers to develop and promote new products based on human psychology. The increasing penetration of IoT devices worldwide and growing cloud spending across industries as well as rising utilization of psychological targeting in advertising are key factors accelerating the market growth.

The increasing penetration of IoT-enabled devices owing to the growth of high-speed internet services is contributing to the growth of the market over the forecast period. For instance, according to Statista –the total number of Internet of Things (IoT) devices worldwide was estimated at 9.7 billion in 2020 and the total number of IoT devices is projected to grow to 29 billion IoT devices by 2030. Also, growing emergence of AI and ML technologies and increasing adoption of digital marketing tools would create a lucrative growth prospectus for the market over the forecast period. However, rising concern over data privacy & security stifles market growth throughout the forecast period of 2022-2029.

The key regions considered for the Global Internet of Behaviors (IoB) Market study include Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America dominated the market in terms of revenue, owing to the presence of leading market players as well as rising spending on digital advertising across different industries in the region. Whereas Asia Pacific is expected to grow with the highest CAGR during the forecast period, owing to factors such as rising spending from government authorities towards smart cities as well as growing emergence of high-speed internet services in the region.

Major market players included in this report are:
Aware Inc.
Traceable
Guardian Analytics
Vertica Systems
Trifacta
NuData Security
Mazu Networks Inc.
Qubit Digital
Cognitive Scale
Capillary Technologies

Recent Developments in the Market:
 In May 2022, San Francisco, USA based Traceable AI, raised USD 60 million in Series B funding. This funding round was led by Institutional Venture Partners (IVP) and saw participation from other prominent investors including Tiger Global Management and existing investors Unusual Ventures and BIG Labs. This funding would be used for new product development and accelerating research activities, and in the expansion of sales and marketing teams.

Global Internet of Behaviors (IoB) Market Report Scope:
Historical Data 2019-2020-2021
Base Year for Estimation 2021
Forecast period 2022-2029
Report Coverage Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Segments Covered Application, Enterprise Size, End-Use Industry, Region
Regional Scope North America; Europe; Asia Pacific; Latin America; Rest of the World
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 Application
Advertising Campaign
Digital Marketing
Content Delivery
Brand Promotion

By Enterprise Size
Small & Medium Enterprises (SMEs)
Large Enterprises

By End Use Industry
BFSI
Telecom and IT
Media and Entertainment
Tourism & Travel
Other

By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
RoLA
Rest of the World

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2029 (USD Billion)
1.2.1. Internet of Behaviors (IoB) Market, by Region, 2019-2029 (USD Billion)
1.2.2. Internet of Behaviors (IoB) Market, by Application, 2019-2029 (USD Billion)
1.2.3. Internet of Behaviors (IoB) Market, by Enterprise Size, 2019-2029 (USD Billion)
1.2.4. Internet of Behaviors (IoB) Market, by End-Use Industry, 2019-2029 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Internet of Behaviors (IoB) 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 Internet of Behaviors (IoB) Market Dynamics
3.1. Internet of Behaviors (IoB) Market Impact Analysis (2019-2029)
3.1.1. Market Drivers
3.1.1.1. Increasing penetration of IoT devices worldwide
3.1.1.2. Growing cloud spending across the industries
3.1.1.3. Rising utilization of psychological targeting in advertising
3.1.2. Market Challenges
3.1.2.1. Rising concern over data privacy & security
3.1.3. Market Opportunities
3.1.3.1. Growing emergence of AI and ML technologies
3.1.3.2. Increasing adoption of digital marketing tools
Chapter 4. Global Internet of Behaviors (IoB) 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. Futuristic Approach to Porter’s 5 Force Model (2019-2029)
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. Industry Experts Prospective
4.7. Analyst Recommendation & Conclusion
Chapter 5. Risk Assessment: COVID-19 Impact
5.1. Assessment of the overall impact of COVID-19 on the industry
5.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global Internet of Behaviors (IoB) Market, by Application
6.1. Market Snapshot
6.2. Global Internet of Behaviors (IoB) Market by Application, Performance – Potential Analysis
6.3. Global Internet of Behaviors (IoB) Market Estimates & Forecasts by Application 2019-2029 (USD Billion)
6.4. Internet of Behaviors (IoB) Market, Sub Segment Analysis
6.4.1. Advertising Campaign
6.4.2. Digital Marketing
6.4.3. Content Delivery
6.4.4. Brand Promotion
Chapter 7. Global Internet of Behaviors (IoB) Market, by Enterprise Size
7.1. Market Snapshot
7.2. Global Internet of Behaviors (IoB) Market by Enterprise Size, Performance – Potential Analysis
7.3. Global Internet of Behaviors (IoB) Market Estimates & Forecasts by Enterprise Size 2019-2029 (USD Billion)
7.4. Internet of Behaviors (IoB) Market, Sub Segment Analysis
7.4.1. Small & Medium Enterprises (SMEs)
7.4.2. Large Enterprises
Chapter 8. Global Internet of Behaviors (IoB) Market, by End-Use Industry
8.1. Market Snapshot
8.2. Global Internet of Behaviors (IoB) Market by End-Use Industry, Performance – Potential Analysis
8.3. Global Internet of Behaviors (IoB) Market Estimates & Forecasts by End-Use Industry 2019-2029 (USD Billion)
8.4. Internet of Behaviors (IoB) Market, Sub Segment Analysis
8.4.1. BFSI
8.4.2. Telecom and IT
8.4.3. Media and Entertainment
8.4.4. Tourism & Travel
Chapter 9. Global Internet of Behaviors (IoB) Market, Regional Analysis
9.1. Internet of Behaviors (IoB) Market, Regional Market Snapshot
9.2. North America Internet of Behaviors (IoB) Market
9.2.1. U.S. Internet of Behaviors (IoB) Market
9.2.1.1. Application breakdown estimates & forecasts, 2019-2029
9.2.1.2. Enterprise Size breakdown estimates & forecasts, 2019-2029
9.2.1.3. End-Use Industry breakdown estimates & forecasts, 2019-2029
9.2.2. Canada Internet of Behaviors (IoB) Market
9.3. Europe Internet of Behaviors (IoB) Market Snapshot
9.3.1. U.K. Internet of Behaviors (IoB) Market
9.3.2. Germany Internet of Behaviors (IoB) Market
9.3.3. France Internet of Behaviors (IoB) Market
9.3.4. Spain Internet of Behaviors (IoB) Market
9.3.5. Italy Internet of Behaviors (IoB) Market
9.3.6. Rest of Europe Internet of Behaviors (IoB) Market
9.4. Asia-Pacific Internet of Behaviors (IoB) Market Snapshot
9.4.1. China Internet of Behaviors (IoB) Market
9.4.2. India Internet of Behaviors (IoB) Market
9.4.3. Japan Internet of Behaviors (IoB) Market
9.4.4. Australia Internet of Behaviors (IoB) Market
9.4.5. South Korea Internet of Behaviors (IoB) Market
9.4.6. Rest of Asia Pacific Internet of Behaviors (IoB) Market
9.5. Latin America Internet of Behaviors (IoB) Market Snapshot
9.5.1. Brazil Internet of Behaviors (IoB) Market
9.5.2. Mexico Internet of Behaviors (IoB) Market
9.5.3. Rest of Latin America Internet of Behaviors (IoB) Market
9.6. Rest of The World Internet of Behaviors (IoB) Market

Chapter 10. Competitive Intelligence
10.1. Top Market Strategies
10.2. Company Profiles
10.2.1. Aware Inc.
10.2.1.1. Key Information
10.2.1.2. Overview
10.2.1.3. Financial (Subject to Data Availability)
10.2.1.4. Product Summary
10.2.1.5. Recent Developments
10.2.2. Traceable
10.2.3. Guardian Analytics
10.2.4. Vertica Systems
10.2.5. Trifacta
10.2.6. NuData Security
10.2.7. Mazu Networks Inc.
10.2.8. Qubit Digital
10.2.9. Cognitive Scale
10.2.10. Capillary Technologies
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

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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.
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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.
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