Global Machine Learning as a Service (MLaaS) Market Size, Industry Analysis By Segmentations, Top Key Players, Trends, Future Development & Forecast 2024-2035
- PUBLISHED ON
- 2/24/2023
- NO OF PAGES
- 235
- CATEGORY
- Electronics & Communication
Machine Learning as a Service (MLaaS) market report presents a global overview of market shares, size, statistics, trends, demand, revenue and growth opportunities by key players, regions and countries. This report offers a complete market overview during the past, present, and the forecast period till 2032 which helps to identify future opportunities, risk factors, growing areas. Report also highlight on recent developments, technological innovations, market affecting factors, demographics analysis, demand and supply chain which gives brief strategy of market growth during the forecast period. It also gives in-depth insights on SWOT and PESTLE analysis based on industry segmentations and regional developments.
Market Overview:
The report provides a basic overview of the industry including definitions, classifications, and industry chain structure. The Machine Learning as a Service (MLaaS) market analysis is provided for the international markets including development trends, competitive landscape analysis, and key regions development status. Development policies and plans are discussed as well as manufacturing processes and cost structures are also analyzed. This report also states import/export consumption, supply and demand, price, revenue and gross margins.
Report Scope:
The primary and secondary research is done in order to access up-to-date government regulations, market information and industry data. Data were collected from the Machine Learning as a Service (MLaaS) manufacturers, distributors, end users, industry associations, governments’ industry bureaus, industry publications, industry experts, third party database, and our in-house databases. The report combines extensive quantitative analysis and exhaustive qualitative analysis, ranges from a macro overview of the total market size, industry chain, and market dynamics to micro details of segment by type, application and region and as a result provides a holistic view of as well as a deep insight into the Machine Learning as a Service (MLaaS) market covering all its essential aspects.
Global Machine Learning as a Service (MLaaS) Market: Segmentations
Global Machine Learning as a Service (MLaaS) Market: Major Players
AWS
IBM
HPE
Google
BigML
SAS Institute Inc
Microsoft
MonkeyLearn
Global Machine Learning as a Service (MLaaS) Market: By Types
Marketing and Advertisement
Predictive Maintenance
Automated Network Management
Fraud Detection and Risk Analytics
Other Applications
Global Machine Learning as a Service (MLaaS) Market: By Applications
SMEs
Large Enterprises
Global Machine Learning as a Service (MLaaS) Market: Regional Analysis
The countries covered in the regional analysis of the Global Machine Learning as a Service (MLaaS) market report are U.S., Canada, and Mexico in North America, Germany, France, U.K., Russia, Italy, Spain, Turkey, Netherlands, Switzerland, Belgium, and Rest of Europe in Europe, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, China, Japan, India, South Korea, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, South Africa, Egypt, Israel, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), and Argentina, Brazil, and Rest of South America as part of South America.
Key Benefits:
• The analysis provides an overview of the factors driving and limiting the growth of the market including trends, structure and others.
• Market estimation for type and geographic segments is derived from the current market scenario and expected market trends.
• Porter’s Five Force Model and SWOT analysis are used to study the global Machine Learning as a Service (MLaaS) market and would help stakeholders make strategic decisions.
• The analysis assists in understanding the strategies adopted by the companies for the growth of this market.
• In-depth analysis of the types of Machine Learning as a Service (MLaaS) would help in identifying future applications in this market.
Reasons to Purchase this Report:
• Qualitative and quantitative analysis of the market based on segmentation involving both economic as well as non-economic factors
• Provision of market value (USD Billion) data for each segment and sub-segment
• Indicates the region and segment that is expected to witness the fastest growth as well as to dominate the market
• Analysis by geography highlighting the consumption of the product/service in the region as well as indicating the factors that are affecting the market within each region
• Competitive landscape which incorporates the market ranking of the major players, along with new service/product launches, partnerships, business expansions, and acquisitions in the past five years of companies profiled
• Extensive company profiles comprising of company overview, company insights, product benchmarking, and SWOT analysis for the major market players
• The current as well as the future market outlook of the industry with respect to recent developments which involve growth opportunities and drivers as well as challenges and restraints of both emerging as well as developed regions
• Includes in-depth analysis of the market of various perspectives through Porter’s five forces analysis
• Provides insight into the market through Value Chain
• Market dynamics scenario, along with growth opportunities of the market in the years to come
• 6-month post-sales analyst support
Objectives of the Study:
• To provide with an exhaustive analysis on the Machine Learning as a Service (MLaaS) Market by Product, By Application, By End User and by Region.
• To cater comprehensive information on factors impacting market growth (drivers, restraints, opportunities, and industry-specific restraints)
• To evaluate and forecast micro-markets and the overall market
• To predict the market size, in key regions— North America, Europe, Asia Pacific, Latin America and Middle East and Africa.
• To record and evaluate competitive landscape mapping- product launches, technological advancements, mergers and expansions
Base Year: 2023Market Overview:
The report provides a basic overview of the industry including definitions, classifications, and industry chain structure. The Machine Learning as a Service (MLaaS) market analysis is provided for the international markets including development trends, competitive landscape analysis, and key regions development status. Development policies and plans are discussed as well as manufacturing processes and cost structures are also analyzed. This report also states import/export consumption, supply and demand, price, revenue and gross margins.
Report Scope:
The primary and secondary research is done in order to access up-to-date government regulations, market information and industry data. Data were collected from the Machine Learning as a Service (MLaaS) manufacturers, distributors, end users, industry associations, governments’ industry bureaus, industry publications, industry experts, third party database, and our in-house databases. The report combines extensive quantitative analysis and exhaustive qualitative analysis, ranges from a macro overview of the total market size, industry chain, and market dynamics to micro details of segment by type, application and region and as a result provides a holistic view of as well as a deep insight into the Machine Learning as a Service (MLaaS) market covering all its essential aspects.
Global Machine Learning as a Service (MLaaS) Market: Segmentations
Global Machine Learning as a Service (MLaaS) Market: Major Players
AWS
IBM
HPE
BigML
SAS Institute Inc
Microsoft
MonkeyLearn
Global Machine Learning as a Service (MLaaS) Market: By Types
Marketing and Advertisement
Predictive Maintenance
Automated Network Management
Fraud Detection and Risk Analytics
Other Applications
Global Machine Learning as a Service (MLaaS) Market: By Applications
SMEs
Large Enterprises
Global Machine Learning as a Service (MLaaS) Market: Regional Analysis
The countries covered in the regional analysis of the Global Machine Learning as a Service (MLaaS) market report are U.S., Canada, and Mexico in North America, Germany, France, U.K., Russia, Italy, Spain, Turkey, Netherlands, Switzerland, Belgium, and Rest of Europe in Europe, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, China, Japan, India, South Korea, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, South Africa, Egypt, Israel, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), and Argentina, Brazil, and Rest of South America as part of South America.
Key Benefits:
• The analysis provides an overview of the factors driving and limiting the growth of the market including trends, structure and others.
• Market estimation for type and geographic segments is derived from the current market scenario and expected market trends.
• Porter’s Five Force Model and SWOT analysis are used to study the global Machine Learning as a Service (MLaaS) market and would help stakeholders make strategic decisions.
• The analysis assists in understanding the strategies adopted by the companies for the growth of this market.
• In-depth analysis of the types of Machine Learning as a Service (MLaaS) would help in identifying future applications in this market.
Reasons to Purchase this Report:
• Qualitative and quantitative analysis of the market based on segmentation involving both economic as well as non-economic factors
• Provision of market value (USD Billion) data for each segment and sub-segment
• Indicates the region and segment that is expected to witness the fastest growth as well as to dominate the market
• Analysis by geography highlighting the consumption of the product/service in the region as well as indicating the factors that are affecting the market within each region
• Competitive landscape which incorporates the market ranking of the major players, along with new service/product launches, partnerships, business expansions, and acquisitions in the past five years of companies profiled
• Extensive company profiles comprising of company overview, company insights, product benchmarking, and SWOT analysis for the major market players
• The current as well as the future market outlook of the industry with respect to recent developments which involve growth opportunities and drivers as well as challenges and restraints of both emerging as well as developed regions
• Includes in-depth analysis of the market of various perspectives through Porter’s five forces analysis
• Provides insight into the market through Value Chain
• Market dynamics scenario, along with growth opportunities of the market in the years to come
• 6-month post-sales analyst support
Objectives of the Study:
• To provide with an exhaustive analysis on the Machine Learning as a Service (MLaaS) Market by Product, By Application, By End User and by Region.
• To cater comprehensive information on factors impacting market growth (drivers, restraints, opportunities, and industry-specific restraints)
• To evaluate and forecast micro-markets and the overall market
• To predict the market size, in key regions— North America, Europe, Asia Pacific, Latin America and Middle East and Africa.
• To record and evaluate competitive landscape mapping- product launches, technological advancements, mergers and expansions
Historic Year: 2016-2022
Forecast: 2024-2035
1 Machine Learning as a Service (MLaaS) Introduction and Market Overview
1.1 Objectives of the Study
1.2 Overview of Machine Learning as a Service (MLaaS)
1.3 Machine Learning as a Service (MLaaS) Market Scope and Market Size Estimation
1.3.1 Market Concentration Ratio and Market Maturity Analysis
1.3.2 Global Machine Learning as a Service (MLaaS) Revenue and Growth Rate from 2016-2026
1.4 Market Segmentation
1.4.1 Types of Machine Learning as a Service (MLaaS)
1.4.2 Applications of Machine Learning as a Service (MLaaS)
1.4.3 Research Regions
1.5 Market Dynamics
1.5.1 Machine Learning as a Service (MLaaS) Industry Trends
1.5.2 Machine Learning as a Service (MLaaS) Drivers
1.5.3 Machine Learning as a Service (MLaaS) Market Challenges
1.5.4 Machine Learning as a Service (MLaaS) Market Restraints
1.6 Industry News and Policies by Regions
1.6.1 Industry News
1.6.2 Industry Policies
1.7 Mergers & Acquisitions, Expansion Plans
1.8 Machine Learning as a Service (MLaaS) Industry Development Trends under COVID-19 Outbreak
1.8.1 Global COVID-19 Status Overview
1.8.2 Influence of COVID-19 Outbreak on Machine Learning as a Service (MLaaS) Industry Development
2 Industry Chain Analysis
2.1 Upstream Raw Material Supply and Demand Analysis
2.1.1 Global Machine Learning as a Service (MLaaS) Major Upstream Raw Material and Suppliers
2.1.2 Raw Material Source Analysis
2.2 Major Players of Machine Learning as a Service (MLaaS)
2.2.1 Major Players Manufacturing Base of Machine Learning as a Service (MLaaS) in 2020
2.2.2 Major Players Market Distribution in 2020
2.3 Machine Learning as a Service (MLaaS) Manufacturing Cost Structure Analysis
2.3.1 Production Process Analysis
2.3.2 Manufacturing Cost Structure of Machine Learning as a Service (MLaaS)
2.3.3 Labor Cost of Machine Learning as a Service (MLaaS)
2.4 Market Channel Analysis of Machine Learning as a Service (MLaaS)
2.5 Major Down Stream Customers by Application
3 Global Machine Learning as a Service (MLaaS) Market, by Type
3.1 Global Machine Learning as a Service (MLaaS) Revenue and Market Share by Type (2016-2021)
3.2 Global Machine Learning as a Service (MLaaS) Production and Market Share by Type (2016-2021)
3.3 Global Machine Learning as a Service (MLaaS) Revenue and Growth Rate by Type (2016-2021)
3.3.1 Global Machine Learning as a Service (MLaaS) Revenue and Growth Rate of Marketing and Advertisement
3.3.2 Global Machine Learning as a Service (MLaaS) Revenue and Growth Rate of Predictive Maintenance
3.3.3 Global Machine Learning as a Service (MLaaS) Revenue and Growth Rate of Automated Network Management
3.3.4 Global Machine Learning as a Service (MLaaS) Revenue and Growth Rate of Fraud Detection and Risk Analytics
3.3.5 Global Machine Learning as a Service (MLaaS) Revenue and Growth Rate of Other Applications
3.4 Global Machine Learning as a Service (MLaaS) Price Analysis by Type (2016-2021)
3.4.1 Explanation of Different Type Product Price Trends
4 Machine Learning as a Service (MLaaS) Market, by Application
4.1 Downstream Market Overview
4.2 Global Machine Learning as a Service (MLaaS) Consumption and Market Share by Application (2016-2021)
4.3 Global Machine Learning as a Service (MLaaS) Consumption and Growth Rate by Application (2016-2021)
4.3.1 Global Machine Learning as a Service (MLaaS) Consumption and Growth Rate of SMEs (2016-2021)
4.3.2 Global Machine Learning as a Service (MLaaS) Consumption and Growth Rate of Large Enterprises (2016-2021)
5 Global Machine Learning as a Service (MLaaS) Consumption, Revenue ($) by Region (2016-2021)
5.1 Global Machine Learning as a Service (MLaaS) Revenue and Market Share by Region (2016-2021)
5.2 Global Machine Learning as a Service (MLaaS) Consumption and Market Share by Region (2016-2021)
5.3 Global Machine Learning as a Service (MLaaS) Consumption, Revenue, Price and Gross Margin (2016-2021)
5.4 North America Machine Learning as a Service (MLaaS) Consumption, Revenue, Price and Gross Margin (2016-2021)
5.4.1 North America Machine Learning as a Service (MLaaS) Market Under COVID-19
5.4.2 North America Machine Learning as a Service (MLaaS) SWOT Analysis
5.5 Europe Machine Learning as a Service (MLaaS) Consumption, Revenue, Price and Gross Margin (2016-2021)
5.5.1 Europe Machine Learning as a Service (MLaaS) Market Under COVID-19
5.5.2 Europe Machine Learning as a Service (MLaaS) SWOT Analysis
5.6 China Machine Learning as a Service (MLaaS) Consumption, Revenue, Price and Gross Margin (2016-2021)
5.6.1 China Machine Learning as a Service (MLaaS) Market Under COVID-19
5.6.2 China Machine Learning as a Service (MLaaS) SWOT Analysis
5.7 Japan Machine Learning as a Service (MLaaS) Consumption, Revenue, Price and Gross Margin (2016-2021)
5.7.1 Japan Machine Learning as a Service (MLaaS) Market Under COVID-19
5.7.2 Japan Machine Learning as a Service (MLaaS) SWOT Analysis
5.8 Middle East and Africa Machine Learning as a Service (MLaaS) Consumption, Revenue, Price and Gross Margin (2016-2021)
5.8.1 Middle East and Africa Machine Learning as a Service (MLaaS) Market Under COVID-19
5.8.2 Middle East and Africa Machine Learning as a Service (MLaaS) SWOT Analysis
5.9 India Machine Learning as a Service (MLaaS) Consumption, Revenue, Price and Gross Margin (2016-2021)
5.9.1 India Machine Learning as a Service (MLaaS) Market Under COVID-19
5.9.2 India Machine Learning as a Service (MLaaS) SWOT Analysis
5.10 South America Machine Learning as a Service (MLaaS) Consumption, Revenue, Price and Gross Margin (2016-2021)
5.10.1 South America Machine Learning as a Service (MLaaS) Market Under COVID-19
5.10.2 South America Machine Learning as a Service (MLaaS) SWOT Analysis
5.11 South Korea Machine Learning as a Service (MLaaS) Consumption, Revenue, Price and Gross Margin (2016-2021)
5.11.1 South Korea Machine Learning as a Service (MLaaS) Market Under COVID-19
5.11.2 South Korea Machine Learning as a Service (MLaaS) SWOT Analysis
5.12 Southeast Asia Machine Learning as a Service (MLaaS) Consumption, Revenue, Price and Gross Margin (2016-2021)
5.12.1 Southeast Asia Machine Learning as a Service (MLaaS) Market Under COVID-19
5.12.2 Southeast Asia Machine Learning as a Service (MLaaS) SWOT Analysis
6 Global Machine Learning as a Service (MLaaS) Production by Top Regions (2016-2021)
6.1 Global Machine Learning as a Service (MLaaS) Production by Top Regions (2016-2021)
6.2 North America Machine Learning as a Service (MLaaS) Production and Growth Rate
6.3 Europe Machine Learning as a Service (MLaaS) Production and Growth Rate
6.4 China Machine Learning as a Service (MLaaS) Production and Growth Rate
6.5 Japan Machine Learning as a Service (MLaaS) Production and Growth Rate
6.6 India Machine Learning as a Service (MLaaS) Production and Growth Rate
7 Global Machine Learning as a Service (MLaaS) Consumption by Regions (2016-2021)
7.1 Global Machine Learning as a Service (MLaaS) Consumption by Regions (2016-2021)
7.2 North America Machine Learning as a Service (MLaaS) Consumption and Growth Rate
7.3 Europe Machine Learning as a Service (MLaaS) Consumption and Growth Rate
7.4 China Machine Learning as a Service (MLaaS) Consumption and Growth Rate
7.5 Japan Machine Learning as a Service (MLaaS) Consumption and Growth Rate
7.6 Middle East & Africa Machine Learning as a Service (MLaaS) Consumption and Growth Rate
7.7 India Machine Learning as a Service (MLaaS) Consumption and Growth Rate
7.8 South America Machine Learning as a Service (MLaaS) Consumption and Growth Rate
7.9 South Korea Machine Learning as a Service (MLaaS) Consumption and Growth Rate
7.10 Southeast Asia Machine Learning as a Service (MLaaS) Consumption and Growth Rate
8 Competitive Landscape
8.1 Competitive Profile
8.2 AWS Market Performance Analysis
8.2.1 Company Profiles
8.2.2 Machine Learning as a Service (MLaaS) Product Profiles, Application and Specification
8.2.3 AWS Sales, Revenue, Price, Gross Margin 2016-2021
8.2.4 Company Recent Development
8.2.5 Strategies for Company to Deal with the Impact of COVID-19
8.3 IBM Market Performance Analysis
8.3.1 Company Profiles
8.3.2 Machine Learning as a Service (MLaaS) Product Profiles, Application and Specification
8.3.3 IBM Sales, Revenue, Price, Gross Margin 2016-2021
8.3.4 Company Recent Development
8.3.5 Strategies for Company to Deal with the Impact of COVID-19
8.4 HPE Market Performance Analysis
8.4.1 Company Profiles
8.4.2 Machine Learning as a Service (MLaaS) Product Profiles, Application and Specification
8.4.3 HPE Sales, Revenue, Price, Gross Margin 2016-2021
8.4.4 Company Recent Development
8.4.5 Strategies for Company to Deal with the Impact of COVID-19
8.5 Google Market Performance Analysis
8.5.1 Company Profiles
8.5.2 Machine Learning as a Service (MLaaS) Product Profiles, Application and Specification
8.5.3 Google Sales, Revenue, Price, Gross Margin 2016-2021
8.5.4 Company Recent Development
8.5.5 Strategies for Company to Deal with the Impact of COVID-19
8.6 BigML Market Performance Analysis
8.6.1 Company Profiles
8.6.2 Machine Learning as a Service (MLaaS) Product Profiles, Application and Specification
8.6.3 BigML Sales, Revenue, Price, Gross Margin 2016-2021
8.6.4 Company Recent Development
8.6.5 Strategies for Company to Deal with the Impact of COVID-19
8.7 SAS Institute Inc Market Performance Analysis
8.7.1 Company Profiles
8.7.2 Machine Learning as a Service (MLaaS) Product Profiles, Application and Specification
8.7.3 SAS Institute Inc Sales, Revenue, Price, Gross Margin 2016-2021
8.7.4 Company Recent Development
8.7.5 Strategies for Company to Deal with the Impact of COVID-19
8.8 Microsoft Market Performance Analysis
8.8.1 Company Profiles
8.8.2 Machine Learning as a Service (MLaaS) Product Profiles, Application and Specification
8.8.3 Microsoft Sales, Revenue, Price, Gross Margin 2016-2021
8.8.4 Company Recent Development
8.8.5 Strategies for Company to Deal with the Impact of COVID-19
8.9 MonkeyLearn Market Performance Analysis
8.9.1 Company Profiles
8.9.2 Machine Learning as a Service (MLaaS) Product Profiles, Application and Specification
8.9.3 MonkeyLearn Sales, Revenue, Price, Gross Margin 2016-2021
8.9.4 Company Recent Development
8.9.5 Strategies for Company to Deal with the Impact of COVID-19
9 Global Machine Learning as a Service (MLaaS) Market Analysis and Forecast by Type and Application
9.1 Global Machine Learning as a Service (MLaaS) Market Revenue & Volume Forecast, by Type (2021-2026)
9.1.1 Marketing and Advertisement Market Revenue and Volume Forecast (2021-2026)
9.1.2 Predictive Maintenance Market Revenue and Volume Forecast (2021-2026)
9.1.3 Automated Network Management Market Revenue and Volume Forecast (2021-2026)
9.1.4 Fraud Detection and Risk Analytics Market Revenue and Volume Forecast (2021-2026)
9.1.5 Other Applications Market Revenue and Volume Forecast (2021-2026)
9.2 Global Machine Learning as a Service (MLaaS) Market Revenue & Volume Forecast, by Application (2021-2026)
9.2.1 SMEs Market Revenue and Volume Forecast (2021-2026)
9.2.2 Large Enterprises Market Revenue and Volume Forecast (2021-2026)
10 Machine Learning as a Service (MLaaS) Market Supply and Demand Forecast by Region
10.1 North America Market Supply and Demand Forecast (2021-2026)
10.2 Europe Market Supply and Demand Forecast (2021-2026)
10.3 China Market Supply and Demand Forecast (2021-2026)
10.4 Japan Market Supply and Demand Forecast (2021-2026)
10.5 Middle East and Africa Market Supply and Demand Forecast (2021-2026)
10.6 India Market Supply and Demand Forecast (2021-2026)
10.7 South America Market Supply and Demand Forecast (2021-2026)
10.8 South Korea Market Supply and Demand Forecast (2021-2026)
10.9 Southeast Asia Market Supply and Demand Forecast (2021-2026)
10.10 Explanation of Market Size Trends by Region
10.11 Machine Learning as a Service (MLaaS) Market Trends Analysis
11 New Project Feasibility Analysis
11.1 Industry Barriers and New Entrants SWOT Analysis
11.2 Analysis and Suggestions on New Project Investment
12 Expert Interview Record
13 Research Finding and Conclusion
14 Appendix
14.1 Methodology
14.2 Research Data Source
Quality Assurance Process
- We Market Research’s Quality Assurance program strives to deliver superior value to our clients.
We Market Research senior executive is assigned to each consulting engagement and works closely with the project team to deliver as per the clients expectations.
Market Research Process
We Market Research monitors 3 important attributes during the QA process- Cost, Schedule & Quality. We believe them as a critical benchmark in achieving a project’s success.
To mitigate risks that can impact project success, we deploy the follow project delivery best practices:
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Case Study- Automotive Sector
One of the key manufacturers of automotive had plans to invest in electric utility vehicles. The electric cars and associated markets being a of evolving nature, the automotive client approached Straits Research for a detailed insight on the market forecasts. The client specifically asked for competitive analysis, regulatory framework, regional prospects studied under the influence of drivers, challenges, opportunities, and pricing in terms of revenue and sales (million units).
Solution
The overall study was executed in three stages, intending to help the client meet its objective of precisely understanding the entire market before deciding on an investment. At first, secondary research was conducted considering political, economic, social, and technological parameters to get a gist of the various aspects of the market. This stage of the study concluded with the derivation of drivers, opportunities, and challenges. It also laid substantial emphasis on understanding and collecting data not only on a global scale but also on the regional and country levels. Data Extraction through Primary Research
The second stage involved primary research in which several market players and automotive parts suppliers were contacted to study their viewpoint concerning the development of their market and production capacity, clientele, and product line. This stage concluded in a brief understanding of the competitive ecosystem and also glanced through the strategies and pricing of the companies profiled.
Market Estimates and Forecast
In the final stage of the study, market forecasts for the electric utility were derived using multiple market engineering approaches. This data helped the client to get an overview of the market and accelerate the process of investment.
Case Study- ICT Sector
Business process outsourcing, being one of the lucrative markets from both supply- and demand- side, has appealed to various companies. One of the prominent corporations based out of Japan approached us with their requirements regarding the scope of the procurement outsourcing market for around 50 countries. Additionally, the client also sought key players operating in the market and their revenue breakdown in terms of region and application.
Business Solution
An exhaustive market study was conducted based on primary and secondary research that involved factors such as labor costs in various countries, skilled and technical labors, manufacturing scenario, and their respective contributions in the global GDP. A comparative study of the market was conducted from both supply- and demand side, with the supply-side comprising of notable companies, such as GEP, Accenture, and others, that provide these services. On the other hand, large manufacturing companies from them demand-side were considered that opt for these services.
Conclusion
The report aided the client in understanding the market trends, including country-level business scenarios, consumer behavior, and trends in 50 countries. The report also provided financial insights of crucial players and detailed market estimations and forecasts till 2028.
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