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Global AI in Social Media Market to reach USD 9619.65 million by the end of 2030.

Global AI in Social Media Market Size study & Forecast, by Technology (Machine Learning, Deep Learning, NLP), by Application (Customer Experience Management, Sales and Marketing, Predictive Risk Assessment) and Regional Analysis, 2023-2030

Product Code: ICTICTS-44447940
Publish Date: 10-06-2023
Page: 200

Global AI in Social Media Market is valued at approximately USD 1278 million in 2022 and is anticipated to grow with a healthy growth rate of more than 28.70% over the forecast period 2023-2030. AI in Social Media means the utilization and integration of AI technology in different types of social media platforms. The factor that drives the growth of the market is an increase in the number of users on social media as it propels companies to employ their AI services in social media. As per Statista, the number of users on social media was around 4.26 billion in 2021 and an increase in the number of users on social media is expected to drive the growth of AI in the Social Media Market. The other factor that drives the growth of the market is an increase in the integration of AI in social media for effective advertising as there are a lot of users on these platforms and these platforms act as the effective way for advertising as they are integrated with AI which propels the growth of AI in social media. However, the limited number of experts in Artificial Intelligence stifles the growth of the AI in Social Media Market.

The growth opportunity factor for the market is the analysis of real-time sentiments as AI can be used to understand the sentiments of social media posts. There is a good opportunity for several companies to monitor the sentiments of social media posts towards the public. The other opportunity for the market is an analysis of social media influencers as influencer marketing is on the rise and AI tools can help businesses to find suitable influencers for their business. As per Statista, the global market for influencer marketing in 2022 was around USD 16.4 billion and it is expected to increase on a YoY basis which can act as a growth opportunity for the market.

The key regions considered for the Global AI in Social Media Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to reasons such as a rise in government support for consent with regulations and there is an expansion of the presence of social media solution providers in AI. Asia Pacific is expected to grow significantly during the forecast period, owing to factors such as the rapid growth of the e-commerce industry in the region which enabled the increase in demand of AI-powered tolls which are there for social media.

Major market player included in this report are:
Microsoft Corporation
Google LLC
Amazon Web Services Inc.
Adobe Inc.
Meta Platforms Inc.
International Business Machines Corporation
Snap Inc.
Salesforce Inc.
Hootsuite Inc.
Twitter Inc.

Recent Developments in the Market:
Ø In October 2022, Meta declared a partnership with Microsoft to offer customers distinctive services in a range of industries, such as gaming and the future of work. As part of this partnership, Microsoft is expected to release Microsoft 365 apps for Meta Quest devices, which can enable its users to engage with material from workplace applications such as Excel, Word, Outlook, PowerPoint, and SharePoint in virtual reality (VR).
Ø In Aug 2022, Veritone, Inc., the maker of the hyper-extensive corporate artificial intelligence (AI) platform aiWARE, announced an extension of its partnership with Amazon Web Services (AWS) to improve the service of its Media & Entertainment (M&E) clients.

Global AI in Social Media Battery 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 – Technology, Application, 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 Technology:
Machine Learning
Deep Learning
NLP

By Application:
Customer Experience Management
Sales and Marketing
Predictive Risk Assessment

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

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 Million)
1.2.1. AI in Social Media Market, by Region, 2020-2030 (USD Million)
1.2.2. AI in Social Media Market, by Technology, 2020-2030 (USD Million)
1.2.3. AI in Social Media Market, by Application, 2020-2030 (USD Million)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global AI in Social Media Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Application Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global AI in Social Media Market Dynamics
3.1. AI in Social Media Market Impact Analysis (2020-2030)
3.1.1. Market Drivers
3.1.1.1. Increase in number of users on social media
3.1.1.2. Increase in integration of AI in social media for effective advertising
3.1.2. Market Challenges
3.1.2.1. Limited number of experts in AI
3.1.3. Market Opportunities
3.1.3.1. Analysis of real-time sentiments
3.1.3.2. Analysis of social media influencers for influencer marketing
Chapter 4. Global AI in Social Media Market Application 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. Application Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global AI in Social Media Market, by Technology
5.1. Market Snapshot
5.2. Global AI in Social Media Market by Technology, Performance – Potential Analysis
5.3. Global AI in Social Media Market Estimates & Forecasts by Technology 2020-2030 (USD Million)
5.4. AI in Social Media Market, Sub Segment Analysis
5.4.1. Machine Learning
5.4.2. Deep Learning
5.4.3. NLP
Chapter 6. Global AI in Social Media Market, by Application
6.1. Market Snapshot
6.2. Global AI in Social Media Market by Application, Performance – Potential Analysis
6.3. Global AI in Social Media Market Estimates & Forecasts by Application 2020-2030 (USD Million)
6.4. AI in Social Media Market, Sub Segment Analysis
6.4.1. Customer Experience Management
6.4.2. Sales and Marketing
6.4.3. Predictive Risk Assessment
Chapter 7. Global AI in Social Media Market, Regional Analysis
7.1. Top Leading Countries
7.2. Top Emerging Countries
7.3. AI in Social Media Market, Regional Market Snapshot
7.4. North America AI in Social Media Market
7.4.1. U.S. AI in Social Media Market
7.4.1.1. Technology breakdown estimates & forecasts, 2020-2030
7.4.1.2. Application breakdown estimates & forecasts, 2020-2030
7.4.2. Canada AI in Social Media Market
7.5. Europe AI in Social Media Market Snapshot
7.5.1. U.K. AI in Social Media Market
7.5.2. Germany AI in Social Media Market
7.5.3. France AI in Social Media Market
7.5.4. Spain AI in Social Media Market
7.5.5. Italy AI in Social Media Market
7.5.6. Rest of Europe AI in Social Media Market
7.6. Asia-Pacific AI in Social Media Market Snapshot
7.6.1. China AI in Social Media Market
7.6.2. India AI in Social Media Market
7.6.3. Japan AI in Social Media Market
7.6.4. Australia AI in Social Media Market
7.6.5. South Korea AI in Social Media Market
7.6.6. Rest of Asia Pacific AI in Social Media Market
7.7. Latin America AI in Social Media Market Snapshot
7.7.1. Brazil AI in Social Media Market
7.7.2. Mexico AI in Social Media Market
7.8. Middle East & Africa AI in Social Media Market
7.8.1. Saudi Arabia AI in Social Media Market
7.8.2. South Africa AI in Social Media Market
7.8.3. Rest of Middle East & Africa AI in Social Media Market

Chapter 8. Competitive Intelligence
8.1. Key Company SWOT Analysis
8.1.1. Company 1
8.1.2. Company 2
8.1.3. Company 3
8.2. Top Market Strategies
8.3. Company Profiles
8.3.1. Microsoft Corporation
8.3.1.1. Key Information
8.3.1.2. Overview
8.3.1.3. Financial (Subject to Data Availability)
8.3.1.4. Product Summary
8.3.1.5. Recent Developments
8.3.2. Google LLC
8.3.3. Amazon Web Services Inc.
8.3.4. Adobe Inc.
8.3.5. Meta Platforms Inc.
8.3.6. International Business Machines Corporation
8.3.7. Snap Inc.
8.3.8. Salesforce Inc.
8.3.9. Hootsuite Inc.
8.3.10. Twitter Inc.
Chapter 9. Research Process
9.1. Research Process
9.1.1. Data Mining
9.1.2. Analysis
9.1.3. Market Estimation
9.1.4. Validation
9.1.5. Publishing
9.2. Research Attributes
9.3. 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.
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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.
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:
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