The Intelligent Process Automation Market is expected to register a CAGR of 13.6% from 2025 to 2031, with a market size expanding from US$ XX million in 2024 to US$ XX Million by 2031.
The report is segmented by Component (Solution, Services); Enterprise Size (Large Enterprises, SMEs); Deployment (Cloud, On Premises); End User (BFSI, Healthcare, Retail, IT and Telecom, Manufacturing, Others); Geography (North America, Europe, Asia-Pacific, Middle East & Africa, South and Central America).
The global analysis is further broken-down at regional level and major countries. The report offers the value in USD for the above analysis and segments
The report Intelligent Process Automation Market by The Insight Partners aims to describe the present landscape and future growth, top driving factors, challenges, and opportunities. This will provide insights to various business stakeholders, such as:
- Technology Providers/Manufacturers: To understand the evolving market dynamics and know the potential growth opportunities, enabling them to make informed strategic decisions.
- Investors: To conduct a comprehensive trend analysis regarding the market growth rate, market financial projections, and opportunities that exist across the value chain.
- Regulatory bodies: To regulate policies and police activities in the market with the aim of minimizing abuse, preserving investor trust and confidence, and upholding the integrity and stability of the market.
Intelligent Process Automation Market Segmentation
Component- Solution
- Services
- Large Enterprises
- SMEs
- Cloud
- On Premises
- BFSI
- Healthcare
- Retail
- IT and Telecom
- Manufacturing
Strategic Insights
Intelligent Process Automation Market Growth Drivers- Need for Operational Efficiency and Cost Reduction: There is growing interest from organizations in looking for ways to optimize their operations and reduce their cost, thus increasing demand for intelligent process automation (IPA) solutions. With repetitive and time-consuming tasks being automated, businesses can streamline operations, minimize human error, and resource allocation. Intelligent process automation is the integration of RPA with AI and ML that aims at making a decision and optimizing the workflows. The overall push for efficiency and cost savings is the key driving force behind the expansion of the IPA market.
- Increasing Complexity of Business Processes: Business processes are becoming increasingly complex because business organizations are expansionist and diversified. This results in increased occurrences of workflow management issues and compliance matters. Intelligent process automation aids organizations in dealing with this complexity by automating complex processes and integrating disparate systems. With IPA, companies can have more agile and adaptive workflows that respond to changing business needs while ensuring accuracy and compliance with regulations. Thus, the increasing complexity of business operations is a significant driver for the adoption of intelligent process automation solutions.
- Adoption of Hyperautomation Strategies: Hyperautomation strategies that incorporate advanced technologies to automate as many business processes as possible have emerged as one of the most followed trends in the intelligent process automation market. Hyperautomation is the consolidation of RPA, AI, machine learning, and other tools that help create a comprehensive automation ecosystem. The trend reflects the growing recognition of organizations that they can achieve better efficiency and agility by automating end-to-end processes rather than isolated tasks. As businesses increasingly adopt hyperautomation, the need for intelligent process automation solutions supporting this approach will grow.
- Emphasis on Data-Driven Decision Making: The growing importance of data analytics in business operations is influencing the intelligent process automation market. Organizations are leveraging data insights to inform their automation strategies and optimize processes. As businesses seek to harness the power of data, IPA solutions that incorporate advanced analytics capabilities will become more sought after. This trend will lead to the development of tools that not only automate processes but also provide actionable insights for continuous improvement.
- Integration with Advanced Technologies: The integration of smart process automation with the modern technologies that include AI, machine learning, and natural language processing promises to unlock vast improvements in automated capabilities. Therefore, an IPA solution embedding AI-powered insights and analytics will not only help organizations function more accurately and efficiently but can also ensure the automation of more intricate tasks requiring higher cognitive capacity. Such vendors can, therefore exploit the trend by developing advanced, fully integrated IPA solutions.
- Focus on Customer Experience Enhancement: As organizations focus on customer experience as an important differentiator, so is the increasing opportunity in intelligent process automation to leverage the enhancement of customer interaction and services. IPA can streamline customer support processes, communicate more personally, and bring down response times, thereby improving customer satisfaction. Organizations can thus make processes more seamless and efficient for customers by using IPA to enable streamlined customer-facing processes. It brings out a massive opportunity for the intelligent process automation provider to develop solutions across this demand.
Market Report Scope
Key Selling Points
- Comprehensive Coverage: The report comprehensively covers the analysis of products, services, types, and end users of the Intelligent Process Automation Market, providing a holistic landscape.
- Expert Analysis: The report is compiled based on the in-depth understanding of industry experts and analysts.
- Up-to-date Information: The report assures business relevance due to its coverage of recent information and data trends.
- Customization Options: This report can be customized to cater to specific client requirements and suit the business strategies aptly.
The research report on the Intelligent Process Automation Market can, therefore, help spearhead the trail of decoding and understanding the industry scenario and growth prospects. Although there can be a few valid concerns, the overall benefits of this report tend to outweigh the disadvantages.
REGIONAL FRAMEWORK
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- Sample PDF showcases the content structure and the nature of the information with qualitative and quantitative analysis.
- Request discounts available for Start-Ups & Universities
Report Coverage
Revenue forecast, Company Analysis, Industry landscape, Growth factors, and Trends
Segment Covered
This text is related
to segments covered.
Regional Scope
North America, Europe, Asia Pacific, Middle East & Africa, South & Central America
Country Scope
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to country scope.
Frequently Asked Questions
Some of the customization options available based on the request are an additional 3–5 company profiles and country-specific analysis of 3–5 countries of your choice. Customizations are to be requested/discussed before making final order confirmation# as our team would review the same and check the feasibility
The report can be delivered in PDF/PPT format; we can also share excel dataset based on the request
Adoption of Hyperautomation Strategies is anticipated to play a significant role in the global Intelligent Process Automation Market in the coming years
Need for Operational Efficiency and Cost Reduction and Increasing Complexity of Business Processes are the major factors driving the Intelligent Process Automation Market
The global Intelligent Process Automation Market is expected to grow at a CAGR of 13.6% during the forecast period 2024 - 2031
1.INTRODUCTION
1.1.SCOPE OF THE STUDY
1.2.THE INSIGHT PARTNERS RESEARCH REPORT GUIDANCE
1.3.MARKET SEGMENTATION
1.3.1Intelligent Process Automation - By Component
1.3.2Intelligent Process Automation - By Technology
1.3.3Intelligent Process Automation - By Application
1.3.4Intelligent Process Automation - By Vertical
1.3.5Intelligent Process Automation - By Region
1.3.5.1By Country
2.KEY TAKEWAYS
3.RESEARCH METHODOLOGY
4.INTELLIGENT PROCESS AUTOMATION LANDSCAPE
4.1.OVERVIEW
4.2.PEST ANALYSIS
4.2.1North America - Pest Analysis
4.2.2Europe - Pest Analysis
4.2.3Asia-Pacific - Pest Analysis
4.2.4Middle East and Africa - Pest Analysis
4.2.5South and Central America - Pest Analysis
4.3.ECOSYSTEM ANALYSIS
4.4.EXPERT OPINIONS
5.INTELLIGENT PROCESS AUTOMATION - KEY MARKET DYNAMICS
5.1.KEY MARKET DRIVERS
5.2.KEY MARKET RESTRAINTS
5.3.KEY MARKET OPPORTUNITIES
5.4.FUTURE TRENDS
5.5.IMPACT ANALYSIS OF DRIVERS, RESTRAINTS & EXPECTED INFLUENCE OF COVID-19 PANDEMIC
6.INTELLIGENT PROCESS AUTOMATION - GLOBAL MARKET ANALYSIS
6.1.INTELLIGENT PROCESS AUTOMATION - GLOBAL MARKET OVERVIEW
6.2.INTELLIGENT PROCESS AUTOMATION - GLOBAL MARKET AND FORECAST TO 2028
6.3.MARKET POSITIONING/MARKET SHARE
7.INTELLIGENT PROCESS AUTOMATION - REVENUE AND FORECASTS TO 2028 - COMPONENT
7.1.OVERVIEW
7.2.COMPONENT MARKET FORECASTS AND ANALYSIS
7.3.SOLUTION
7.3.1.Overview
7.3.2.Solution Market Forecast and Analysis
7.4.SERVICES
7.4.1.Overview
7.4.2.Services Market Forecast and Analysis
8.INTELLIGENT PROCESS AUTOMATION - REVENUE AND FORECASTS TO 2028 - TECHNOLOGY
8.1.OVERVIEW
8.2.TECHNOLOGY MARKET FORECASTS AND ANALYSIS
8.3.NATURAL LANGUAGE PROCESSING
8.3.1.Overview
8.3.2.Natural Language Processing Market Forecast and Analysis
8.4.MACHINE AND DEEP LEARNING
8.4.1.Overview
8.4.2.Machine and Deep Learning Market Forecast and Analysis
8.5.NEURAL NETWORKS
8.5.1.Overview
8.5.2.Neural Networks Market Forecast and Analysis
8.6.VIRTUAL AGENTS
8.6.1.Overview
8.6.2.Virtual Agents Market Forecast and Analysis
8.7.MINI BOTS
8.7.1.Overview
8.7.2.Mini Bots Market Forecast and Analysis
8.8.COMPUTER VISION
8.8.1.Overview
8.8.2.Computer Vision Market Forecast and Analysis
8.9.
8.9.1.Overview
8.9.2. Market Forecast and Analysis
9.INTELLIGENT PROCESS AUTOMATION - REVENUE AND FORECASTS TO 2028 - APPLICATION
9.1.OVERVIEW
9.2.APPLICATION MARKET FORECASTS AND ANALYSIS
9.3.IT OPERATIONS
9.3.1.Overview
9.3.2.IT Operations Market Forecast and Analysis
9.4.BUSINESS PROCESS AUTOMATION
9.4.1.Overview
9.4.2.Business Process Automation Market Forecast and Analysis
9.5.APPLICATION MANAGEMENT
9.5.1.Overview
9.5.2.Application Management Market Forecast and Analysis
9.6.CONTENT MANAGEMENT
9.6.1.Overview
9.6.2.Content Management Market Forecast and Analysis
9.7.SECURITY
9.7.1.Overview
9.7.2.Security Market Forecast and Analysis
10.INTELLIGENT PROCESS AUTOMATION - REVENUE AND FORECASTS TO 2028 - VERTICAL
10.1.OVERVIEW
10.2.VERTICAL MARKET FORECASTS AND ANALYSIS
10.3.BFSI
10.3.1.Overview
10.3.2.BFSI Market Forecast and Analysis
10.4.TELECOMMUNICATIONS AND IT
10.4.1.Overview
10.4.2.Telecommunications and IT Market Forecast and Analysis
10.5.TRANSPORT AND LOGISTICS
10.5.1.Overview
10.5.2.Transport and Logistics Market Forecast and Analysis
10.6.MEDIA AND ENTERTAINMENT
10.6.1.Overview
10.6.2.Media and Entertainment Market Forecast and Analysis
10.7.RETAIL AND ECOMMERCE
10.7.1.Overview
10.7.2.Retail and Ecommerce Market Forecast and Analysis
10.8.MANUFACTURING
10.8.1.Overview
10.8.2.Manufacturing Market Forecast and Analysis
10.9.HEALTHCARE AND LIFE SCIENCES
10.9.1.Overview
10.9.2.Healthcare and Life Sciences Market Forecast and Analysis
11.INTELLIGENT PROCESS AUTOMATION REVENUE AND FORECASTS TO 2028 - GEOGRAPHICAL ANALYSIS
11.1.NORTH AMERICA
11.1.1North America Intelligent Process Automation Overview
11.1.2North America Intelligent Process Automation Forecasts and Analysis
11.1.3North America Intelligent Process Automation Forecasts and Analysis - By Component
11.1.4North America Intelligent Process Automation Forecasts and Analysis - By Technology
11.1.5North America Intelligent Process Automation Forecasts and Analysis - By Application
11.1.6North America Intelligent Process Automation Forecasts and Analysis - By Vertical
11.1.7North America Intelligent Process Automation Forecasts and Analysis - By Countries
11.1.7.1United States Intelligent Process Automation
11.1.7.1.1United States Intelligent Process Automation by Component
11.1.7.1.2United States Intelligent Process Automation by Technology
11.1.7.1.3United States Intelligent Process Automation by Application
11.1.7.1.4United States Intelligent Process Automation by Vertical
11.1.7.2Canada Intelligent Process Automation
11.1.7.2.1Canada Intelligent Process Automation by Component
11.1.7.2.2Canada Intelligent Process Automation by Technology
11.1.7.2.3Canada Intelligent Process Automation by Application
11.1.7.2.4Canada Intelligent Process Automation by Vertical
11.1.7.3Mexico Intelligent Process Automation
11.1.7.3.1Mexico Intelligent Process Automation by Component
11.1.7.3.2Mexico Intelligent Process Automation by Technology
11.1.7.3.3Mexico Intelligent Process Automation by Application
11.1.7.3.4Mexico Intelligent Process Automation by Vertical
11.2.EUROPE
11.2.1Europe Intelligent Process Automation Overview
11.2.2Europe Intelligent Process Automation Forecasts and Analysis
11.2.3Europe Intelligent Process Automation Forecasts and Analysis - By Component
11.2.4Europe Intelligent Process Automation Forecasts and Analysis - By Technology
11.2.5Europe Intelligent Process Automation Forecasts and Analysis - By Application
11.2.6Europe Intelligent Process Automation Forecasts and Analysis - By Vertical
11.2.7Europe Intelligent Process Automation Forecasts and Analysis - By Countries
11.2.7.1Germany Intelligent Process Automation
11.2.7.1.1Germany Intelligent Process Automation by Component
11.2.7.1.2Germany Intelligent Process Automation by Technology
11.2.7.1.3Germany Intelligent Process Automation by Application
11.2.7.1.4Germany Intelligent Process Automation by Vertical
11.2.7.2France Intelligent Process Automation
11.2.7.2.1France Intelligent Process Automation by Component
11.2.7.2.2France Intelligent Process Automation by Technology
11.2.7.2.3France Intelligent Process Automation by Application
11.2.7.2.4France Intelligent Process Automation by Vertical
11.2.7.3Italy Intelligent Process Automation
11.2.7.3.1Italy Intelligent Process Automation by Component
11.2.7.3.2Italy Intelligent Process Automation by Technology
11.2.7.3.3Italy Intelligent Process Automation by Application
11.2.7.3.4Italy Intelligent Process Automation by Vertical
11.2.7.4United Kingdom Intelligent Process Automation
11.2.7.4.1United Kingdom Intelligent Process Automation by Component
11.2.7.4.2United Kingdom Intelligent Process Automation by Technology
11.2.7.4.3United Kingdom Intelligent Process Automation by Application
11.2.7.4.4United Kingdom Intelligent Process Automation by Vertical
11.2.7.5Russia Intelligent Process Automation
11.2.7.5.1Russia Intelligent Process Automation by Component
11.2.7.5.2Russia Intelligent Process Automation by Technology
11.2.7.5.3Russia Intelligent Process Automation by Application
11.2.7.5.4Russia Intelligent Process Automation by Vertical
11.2.7.6Rest of Europe Intelligent Process Automation
11.2.7.6.1Rest of Europe Intelligent Process Automation by Component
11.2.7.6.2Rest of Europe Intelligent Process Automation by Technology
11.2.7.6.3Rest of Europe Intelligent Process Automation by Application
11.2.7.6.4Rest of Europe Intelligent Process Automation by Vertical
11.3.ASIA-PACIFIC
11.3.1Asia-Pacific Intelligent Process Automation Overview
11.3.2Asia-Pacific Intelligent Process Automation Forecasts and Analysis
11.3.3Asia-Pacific Intelligent Process Automation Forecasts and Analysis - By Component
11.3.4Asia-Pacific Intelligent Process Automation Forecasts and Analysis - By Technology
11.3.5Asia-Pacific Intelligent Process Automation Forecasts and Analysis - By Application
11.3.6Asia-Pacific Intelligent Process Automation Forecasts and Analysis - By Vertical
11.3.7Asia-Pacific Intelligent Process Automation Forecasts and Analysis - By Countries
11.3.7.1Australia Intelligent Process Automation
11.3.7.1.1Australia Intelligent Process Automation by Component
11.3.7.1.2Australia Intelligent Process Automation by Technology
11.3.7.1.3Australia Intelligent Process Automation by Application
11.3.7.1.4Australia Intelligent Process Automation by Vertical
11.3.7.2China Intelligent Process Automation
11.3.7.2.1China Intelligent Process Automation by Component
11.3.7.2.2China Intelligent Process Automation by Technology
11.3.7.2.3China Intelligent Process Automation by Application
11.3.7.2.4China Intelligent Process Automation by Vertical
11.3.7.3India Intelligent Process Automation
11.3.7.3.1India Intelligent Process Automation by Component
11.3.7.3.2India Intelligent Process Automation by Technology
11.3.7.3.3India Intelligent Process Automation by Application
11.3.7.3.4India Intelligent Process Automation by Vertical
11.3.7.4Japan Intelligent Process Automation
11.3.7.4.1Japan Intelligent Process Automation by Component
11.3.7.4.2Japan Intelligent Process Automation by Technology
11.3.7.4.3Japan Intelligent Process Automation by Application
11.3.7.4.4Japan Intelligent Process Automation by Vertical
11.3.7.5South Korea Intelligent Process Automation
11.3.7.5.1South Korea Intelligent Process Automation by Component
11.3.7.5.2South Korea Intelligent Process Automation by Technology
11.3.7.5.3South Korea Intelligent Process Automation by Application
11.3.7.5.4South Korea Intelligent Process Automation by Vertical
11.3.7.6Rest of Asia-Pacific Intelligent Process Automation
11.3.7.6.1Rest of Asia-Pacific Intelligent Process Automation by Component
11.3.7.6.2Rest of Asia-Pacific Intelligent Process Automation by Technology
11.3.7.6.3Rest of Asia-Pacific Intelligent Process Automation by Application
11.3.7.6.4Rest of Asia-Pacific Intelligent Process Automation by Vertical
11.4.MIDDLE EAST AND AFRICA
11.4.1Middle East and Africa Intelligent Process Automation Overview
11.4.2Middle East and Africa Intelligent Process Automation Forecasts and Analysis
11.4.3Middle East and Africa Intelligent Process Automation Forecasts and Analysis - By Component
11.4.4Middle East and Africa Intelligent Process Automation Forecasts and Analysis - By Technology
11.4.5Middle East and Africa Intelligent Process Automation Forecasts and Analysis - By Application
11.4.6Middle East and Africa Intelligent Process Automation Forecasts and Analysis - By Vertical
11.4.7Middle East and Africa Intelligent Process Automation Forecasts and Analysis - By Countries
11.4.7.1South Africa Intelligent Process Automation
11.4.7.1.1South Africa Intelligent Process Automation by Component
11.4.7.1.2South Africa Intelligent Process Automation by Technology
11.4.7.1.3South Africa Intelligent Process Automation by Application
11.4.7.1.4South Africa Intelligent Process Automation by Vertical
11.4.7.2Saudi Arabia Intelligent Process Automation
11.4.7.2.1Saudi Arabia Intelligent Process Automation by Component
11.4.7.2.2Saudi Arabia Intelligent Process Automation by Technology
11.4.7.2.3Saudi Arabia Intelligent Process Automation by Application
11.4.7.2.4Saudi Arabia Intelligent Process Automation by Vertical
11.4.7.3U.A.E Intelligent Process Automation
11.4.7.3.1U.A.E Intelligent Process Automation by Component
11.4.7.3.2U.A.E Intelligent Process Automation by Technology
11.4.7.3.3U.A.E Intelligent Process Automation by Application
11.4.7.3.4U.A.E Intelligent Process Automation by Vertical
11.4.7.4Rest of Middle East and Africa Intelligent Process Automation
11.4.7.4.1Rest of Middle East and Africa Intelligent Process Automation by Component
11.4.7.4.2Rest of Middle East and Africa Intelligent Process Automation by Technology
11.4.7.4.3Rest of Middle East and Africa Intelligent Process Automation by Application
11.4.7.4.4Rest of Middle East and Africa Intelligent Process Automation by Vertical
11.5.SOUTH AND CENTRAL AMERICA
11.5.1South and Central America Intelligent Process Automation Overview
11.5.2South and Central America Intelligent Process Automation Forecasts and Analysis
11.5.3South and Central America Intelligent Process Automation Forecasts and Analysis - By Component
11.5.4South and Central America Intelligent Process Automation Forecasts and Analysis - By Technology
11.5.5South and Central America Intelligent Process Automation Forecasts and Analysis - By Application
11.5.6South and Central America Intelligent Process Automation Forecasts and Analysis - By Vertical
11.5.7South and Central America Intelligent Process Automation Forecasts and Analysis - By Countries
11.5.7.1Brazil Intelligent Process Automation
11.5.7.1.1Brazil Intelligent Process Automation by Component
11.5.7.1.2Brazil Intelligent Process Automation by Technology
11.5.7.1.3Brazil Intelligent Process Automation by Application
11.5.7.1.4Brazil Intelligent Process Automation by Vertical
11.5.7.2Argentina Intelligent Process Automation
11.5.7.2.1Argentina Intelligent Process Automation by Component
11.5.7.2.2Argentina Intelligent Process Automation by Technology
11.5.7.2.3Argentina Intelligent Process Automation by Application
11.5.7.2.4Argentina Intelligent Process Automation by Vertical
11.5.7.3Rest of South and Central America Intelligent Process Automation
11.5.7.3.1Rest of South and Central America Intelligent Process Automation by Component
11.5.7.3.2Rest of South and Central America Intelligent Process Automation by Technology
11.5.7.3.3Rest of South and Central America Intelligent Process Automation by Application
11.5.7.3.4Rest of South and Central America Intelligent Process Automation by Vertical
12.INDUSTRY LANDSCAPE
12.1.MERGERS AND ACQUISITIONS
12.2.AGREEMENTS, COLLABORATIONS AND JOIN VENTURES
12.3.NEW PRODUCT LAUNCHES
12.4.EXPANSIONS AND OTHER STRATEGIC DEVELOPMENTS
13.INTELLIGENT PROCESS AUTOMATION, KEY COMPANY PROFILES
13.1.ACCENTURE
13.1.1.Key Facts
13.1.2.Business Description
13.1.3.Products and Services
13.1.4.Financial Overview
13.1.5.SWOT Analysis
13.1.6.Key Developments
13.2.BLUE PRISM
13.2.1.Key Facts
13.2.2.Business Description
13.2.3.Products and Services
13.2.4.Financial Overview
13.2.5.SWOT Analysis
13.2.6.Key Developments
13.3.CAPGEMINI
13.3.1.Key Facts
13.3.2.Business Description
13.3.3.Products and Services
13.3.4.Financial Overview
13.3.5.SWOT Analysis
13.3.6.Key Developments
13.4.COGNIZANT
13.4.1.Key Facts
13.4.2.Business Description
13.4.3.Products and Services
13.4.4.Financial Overview
13.4.5.SWOT Analysis
13.4.6.Key Developments
13.5.CGI INC.
13.5.1.Key Facts
13.5.2.Business Description
13.5.3.Products and Services
13.5.4.Financial Overview
13.5.5.SWOT Analysis
13.5.6.Key Developments
13.6.GENPACT
13.6.1.Key Facts
13.6.2.Business Description
13.6.3.Products and Services
13.6.4.Financial Overview
13.6.5.SWOT Analysis
13.6.6.Key Developments
13.7.HCL TECHNOLOGIES LIMITED
13.7.1.Key Facts
13.7.2.Business Description
13.7.3.Products and Services
13.7.4.Financial Overview
13.7.5.SWOT Analysis
13.7.6.Key Developments
13.8.IBM
13.8.1.Key Facts
13.8.2.Business Description
13.8.3.Products and Services
13.8.4.Financial Overview
13.8.5.SWOT Analysis
13.8.6.Key Developments
13.9.KPMG
13.9.1.Key Facts
13.9.2.Business Description
13.9.3.Products and Services
13.9.4.Financial Overview
13.9.5.SWOT Analysis
13.9.6.Key Developments
13.10.TATA CONSULTANCY SERVICE
13.10.1.Key Facts
13.10.2.Business Description
13.10.3.Products and Services
13.10.4.Financial Overview
13.10.5.SWOT Analysis
13.10.6.Key Developments
14.APPENDIX
14.1.ABOUT THE INSIGHT PARTNERS
14.2.GLOSSARY OF TERMS
1. Accenture
2. Blue Prism
3. Capgemini
4. Cognizant
5. CGI Inc.
6. Genpact
7. HCL Technologies Limited
8. IBM
9. KPMG
10. TATA CONSULTANCY SERVICE
The Insight Partners performs research in 4 major stages: Data Collection & Secondary Research, Primary Research, Data Analysis and Data Triangulation & Final Review.
- Data Collection and Secondary Research:
As a market research and consulting firm operating from a decade, we have published many reports and advised several clients across the globe. First step for any study will start with an assessment of currently available data and insights from existing reports. Further, historical and current market information is collected from Investor Presentations, Annual Reports, SEC Filings, etc., and other information related to company’s performance and market positioning are gathered from Paid Databases (Factiva, Hoovers, and Reuters) and various other publications available in public domain.
Several associations trade associates, technical forums, institutes, societies and organizations are accessed to gain technical as well as market related insights through their publications such as research papers, blogs and press releases related to the studies are referred to get cues about the market. Further, white papers, journals, magazines, and other news articles published in the last 3 years are scrutinized and analyzed to understand the current market trends.
- Primary Research:
The primarily interview analysis comprise of data obtained from industry participants interview and answers to survey questions gathered by in-house primary team.
For primary research, interviews are conducted with industry experts/CEOs/Marketing Managers/Sales Managers/VPs/Subject Matter Experts from both demand and supply side to get a 360-degree view of the market. The primary team conducts several interviews based on the complexity of the markets to understand the various market trends and dynamics which makes research more credible and precise.
A typical research interview fulfils the following functions:
- Provides first-hand information on the market size, market trends, growth trends, competitive landscape, and outlook
- Validates and strengthens in-house secondary research findings
- Develops the analysis team’s expertise and market understanding
Primary research involves email interactions and telephone interviews for each market, category, segment, and sub-segment across geographies. The participants who typically take part in such a process include, but are not limited to:
- Industry participants: VPs, business development managers, market intelligence managers and national sales managers
- Outside experts: Valuation experts, research analysts and key opinion leaders specializing in the electronics and semiconductor industry.
Below is the breakup of our primary respondents by company, designation, and region:
Once we receive the confirmation from primary research sources or primary respondents, we finalize the base year market estimation and forecast the data as per the macroeconomic and microeconomic factors assessed during data collection.
- Data Analysis:
Once data is validated through both secondary as well as primary respondents, we finalize the market estimations by hypothesis formulation and factor analysis at regional and country level.
- 3.1 Macro-Economic Factor Analysis:
We analyse macroeconomic indicators such the gross domestic product (GDP), increase in the demand for goods and services across industries, technological advancement, regional economic growth, governmental policies, the influence of COVID-19, PEST analysis, and other aspects. This analysis aids in setting benchmarks for various nations/regions and approximating market splits. Additionally, the general trend of the aforementioned components aid in determining the market's development possibilities.
- 3.2 Country Level Data:
Various factors that are especially aligned to the country are taken into account to determine the market size for a certain area and country, including the presence of vendors, such as headquarters and offices, the country's GDP, demand patterns, and industry growth. To comprehend the market dynamics for the nation, a number of growth variables, inhibitors, application areas, and current market trends are researched. The aforementioned elements aid in determining the country's overall market's growth potential.
- 3.3 Company Profile:
The “Table of Contents” is formulated by listing and analyzing more than 25 - 30 companies operating in the market ecosystem across geographies. However, we profile only 10 companies as a standard practice in our syndicate reports. These 10 companies comprise leading, emerging, and regional players. Nonetheless, our analysis is not restricted to the 10 listed companies, we also analyze other companies present in the market to develop a holistic view and understand the prevailing trends. The “Company Profiles” section in the report covers key facts, business description, products & services, financial information, SWOT analysis, and key developments. The financial information presented is extracted from the annual reports and official documents of the publicly listed companies. Upon collecting the information for the sections of respective companies, we verify them via various primary sources and then compile the data in respective company profiles. The company level information helps us in deriving the base number as well as in forecasting the market size.
- 3.4 Developing Base Number:
Aggregation of sales statistics (2020-2022) and macro-economic factor, and other secondary and primary research insights are utilized to arrive at base number and related market shares for 2022. The data gaps are identified in this step and relevant market data is analyzed, collected from paid primary interviews or databases. On finalizing the base year market size, forecasts are developed on the basis of macro-economic, industry and market growth factors and company level analysis.
- Data Triangulation and Final Review:
The market findings and base year market size calculations are validated from supply as well as demand side. Demand side validations are based on macro-economic factor analysis and benchmarks for respective regions and countries. In case of supply side validations, revenues of major companies are estimated (in case not available) based on industry benchmark, approximate number of employees, product portfolio, and primary interviews revenues are gathered. Further revenue from target product/service segment is assessed to avoid overshooting of market statistics. In case of heavy deviations between supply and demand side values, all thes steps are repeated to achieve synchronization.
We follow an iterative model, wherein we share our research findings with Subject Matter Experts (SME’s) and Key Opinion Leaders (KOLs) until consensus view of the market is not formulated – this model negates any drastic deviation in the opinions of experts. Only validated and universally acceptable research findings are quoted in our reports.
We have important check points that we use to validate our research findings – which we call – data triangulation, where we validate the information, we generate from secondary sources with primary interviews and then we re-validate with our internal data bases and Subject matter experts. This comprehensive model enables us to deliver high quality, reliable data in shortest possible time.
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