AI in Retail and E-Commerce Market Growth, Trends & Forecast by 2034
Coverage: AI in Retail and E-Commerce Market covers analysis By Component (Software, Hardware, and Services), Deployment (Cloud and On Premises), Organization Size (Large Enterprises and SMEs), and Geography (North America, Europe, Asia Pacific, Middle East and Africa, and South America)
- Report Date : Apr 2026
- Report Code : TIPRE00042232
- Category : Technology, Media and Telecommunications
- Status : Upcoming
- Available Report Formats :
- No. of Pages : 290
The AI in retail and e-commerce market size is projected to reach US$ 19.98 billion in 2025 and is expected to reach US$ 398.65 billion by 2034. The AI in retail and e-commerce market is estimated to register a CAGR of 40.3% during 2026–2034.
AI in Retail and E-Commerce Market AnalysisThe AI in retail and e-commerce market is witnessing rapid growth due to increasing adoption of digital platforms, advanced analytics, and AI-driven customer engagement solutions. Retailers are leveraging AI to optimize inventory management, personalize marketing campaigns, enhance customer experiences, and automate supply chain operations. Growing e-commerce penetration, rising consumer expectations, and competitive pressures are driving investments in AI technologies. Predictive analytics, natural language processing, and computer vision are used for demand forecasting, chatbots, recommendation engines, and fraud detection. Continuous innovations and the expansion of cloud-based AI platforms are expected to sustain long-term growth in the AI-driven retail and e-commerce landscape.
AI in Retail and E-Commerce Market OverviewThe AI in retail and e-commerce market is expanding rapidly as businesses seek to improve customer personalization, operational efficiency, and decision-making accuracy. AI technologies such as machine learning, natural language processing, and computer vision are deployed in product recommendations, dynamic pricing, inventory optimization, and customer support automation. The rise of omnichannel retail, mobile commerce, and social commerce is fueling AI adoption for real-time analytics and personalized engagement. Growing investments in AI infrastructure, increasing consumer data availability, and the push for smart, automated retail operations are accelerating market growth, making AI a critical component of retail and e-commerce strategies.
Strategic InsightsAI in Retail and E-Commerce Market Drivers and OpportunitiesMarket Drivers:
- Rising Demand for Personalized Shopping Experiences: AI enables tailored recommendations, targeted promotions, and dynamic pricing, improving customer engagement and sales conversion.
- Operational Efficiency and Supply Chain Optimization: AI helps retailers forecast demand, optimize inventory, automate warehousing, and enhance logistics efficiency.
- Growth of Omnichannel and E-Commerce Platforms:
AI-driven analytics improve product discovery, real-time inventory management, and seamless customer experiences across online and offline channels.
Market Opportunities:
- Collaboration with AI Technology Providers: Retailers partner with AI firms to develop recommendation engines, chatbots, visual search tools, and predictive analytics solutions.
- Integration of AI-Driven Software and Platforms: AI-powered platforms for customer analytics, pricing optimization, demand forecasting, and fraud detection provide measurable business value.
- Modular and Scalable AI Systems: AI solutions are increasingly designed for gradual integration, allowing adoption alongside existing retail IT systems without full infrastructure replacement.
The AI in retail and e-commerce market is divided into different segments to give a clearer view of how it works, its growth potential, and the latest trends. Below is the standard segmentation approach used in industry reports:
By Component:
- Software: AI software in retail and e-commerce includes recommendation engines, predictive analytics tools, demand forecasting systems, dynamic pricing solutions, and virtual assistants, improving decision-making and customer experience.
- Hardware: Hardware includes servers, GPUs, IoT-enabled devices, and sensors used for data collection, in-store analytics, and automation in warehouses and fulfillment centers.
- Services: AI services cover system integration, consulting, model training, and ongoing maintenance, ensuring smooth deployment, scalability, and optimization of AI solutions.
By Deployment:
- Cloud
- On Premises
By Organization Size:
- Large Enterprises
- SMEs
By Geography:
- North America
- Europe
- Asia Pacific
- South America
- Middle East & Africa
Market Report Scope
AI in Retail and E-Commerce Market Share Analysis by GeographyThe AI in retail and e-commerce market in Asia Pacific is expanding owing to increasing digitalization, growing e-commerce penetration, and rising demand for personalized shopping experiences. Retailers and online platforms are leveraging AI for personalized product recommendations, dynamic pricing, customer behavior analytics, inventory optimization, and automated logistics. Supportive government initiatives, investments in AI infrastructure, and advancements in machine learning, computer vision, natural language processing, and predictive analytics are accelerating market growth. Additionally, rising awareness of AI's potential to improve operational efficiency, enhance customer engagement, and enable data-driven decision-making is driving widespread adoption, making Asia Pacific one of the fastest-growing markets for AI-enabled retail and e-commerce solutions.
Below is a summary of market share and trends by region:
1. North America
- Market Share: A mature market with high AI adoption among major retailers, e-commerce giants, and omnichannel platforms.
- Key Drivers:
- Investments in AI-powered customer analytics, personalized recommendations, predictive inventory management, and government support for digital commerce initiatives.
- Trends: AI-driven chatbots, visual search, dynamic pricing, demand forecasting, and integration with CRM and ERP systems for seamless customer experiences.
2. Europe
- Market Share: Strong position due to advanced retail infrastructure, regulatory support for digital commerce, and growing consumer acceptance of AI.
- Key Drivers:
- Government incentives for digital retail innovation, adoption of AI in supply chain and marketing automation, and demand for personalized shopping.
- Trends: AI-powered product recommendations, predictive analytics for inventory and logistics, and virtual shopping assistants.
3. MEA
- Market Share: Emerging market with increasing AI adoption in e-commerce and retail, particularly in Gulf countries.
- Key Drivers:
- Growing e-commerce penetration, retail modernization, and investments in AI-based logistics and customer engagement solutions.
- Trends: AI-driven inventory management, chatbots, and personalization of online shopping experiences.
4. Asia Pacific
- Market Share: Fastest-growing region, led by China, India, Japan, and Southeast Asia, driven by rapid e-commerce growth and smartphone penetration.
- Key Drivers:
- Government initiatives supporting AI adoption, rising digital retail penetration, and demand for personalized and frictionless shopping experiences.
- Trends: AI in mobile commerce, predictive analytics, recommendation engines, automated warehouses, and smart supply chains.
5. South America
- Market Share: Gradually expanding market, with growing AI adoption in Brazil, Argentina, and Chile.
- Key Drivers:
- Rising online retail penetration, investments in AI-driven logistics and payment systems, and the digital transformation of traditional retail.
- Trends: AI-based fraud detection, customer analytics, chatbots, and demand forecasting for e-commerce platforms.
High Market Density and Competition
Competition is strong due to the presence of established players such as Microsoft Corp, Accenture Plc, International Business Machines Corp, NVIDIA Corp, and Google LLC. Regional and niche providers, such as Advanced Micro Devices Inc, SAP SE, and SAS Institute Inc, add to the competitive landscape across different regions.
This high level of competition urges companies to stand out by offering:
- Advanced AI-powered retail solutions: Personalized recommendation engines, dynamic pricing systems, predictive inventory management, fraud detection, visual search, and virtual shopping assistants.
- Customized AI applications: Solutions tailored for e-commerce platforms, brick-and-mortar stores, omnichannel retail, logistics, and customer support.
- Cost-effective operations: AI-driven automation for supply chain optimization, warehouse management, marketing personalization, and operational efficiency improvements.
- Comprehensive analytics and support services: AI-enabled chatbots, real-time customer analytics, automated order fulfillment, and predictive maintenance of retail IT infrastructure.
Opportunities and Strategic Moves
- Collaborations with AI technology providers: Retailers are partnering with AI firms to enhance personalization, optimize inventory, improve customer engagement, and enable real-time decision-making.
- Integration of AI-driven platforms: Companies are deploying AI-enabled software for predictive analytics, demand forecasting, pricing optimization, and automated customer service.
- Modular and scalable AI systems: Retailers increasingly adopt AI solutions that integrate with existing IT infrastructure, enabling gradual implementation without full replacement of legacy systems.
- Expansion into omnichannel and mobile commerce: AI supports seamless customer experiences across online, offline, and mobile channels, creating growth opportunities in emerging markets.
- Accenture Plc
- Advanced Micro Devices Inc
- Google LLC
- International Business Machines Corp
- Intel Corp
- Microsoft Corp
- NVIDIA Corp
- Amazon Web Services Inc
- SAP SE
- SAS Institute Inc
Disclaimer: The companies listed above are not ranked in any particular order.
Other companies analyzed during the course of research:- Persistent Systems
- Qualcomm Technologies, Inc.
- Salesforce
- Palantir Technologies
- Infosys Limited
- Capgemini SE
- Others
- Flipkart Acquires AI Innovator Minivet AI to Revolutionize Online Shopping: Flipkart, India's e-commerce titan, has bolstered its technological arsenal by acquiring a majority stake in Minivet AI. This strategic move, announced on December 19, 2025, marks a substantial investment in generative artificial intelligence, aiming to transform how products are presented and discovered online. The acquisition is poised to enhance Flipkart's visual commerce capabilities and create more immersive shopping experiences for its vast customer base.
- Google's AI Announcement: In January 2026, Google announced the launch of Universal Commerce Protocol. This infrastructure will enable seamless AI-powered shopping, Native Checkout across AI surfaces, Business Agent in Search, and a Direct Offers pilot. Google has established a standard protocol for how brands are positioning themselves with AI as the protocol layer between consumers, retailers, and payment systems.
The "AI in Retail and E-Commerce Market Size and Forecast (2021–2031)" report provides a detailed analysis of the market covering below areas:
- AI in retail and e-commerce market size and forecast at global, regional, and country levels for all the segments covered under the scope
- AI in retail and e-commerce market trends, as well as dynamics such as drivers, restraints, and key opportunities
- Detailed PEST and SWOT analysis
- AI in retail and e-commerce market analysis covering key trends, global and regional framework, major players, regulations, and recent developments
- Industry landscape and competition analysis covering market concentration, heat map analysis, prominent players, and recent developments for the AI in retail and e-commerce market
- Detailed company profiles
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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
NVIDIA Corp, Microsoft Corp, Google LLC, IBM Corp, and Accenture Plc are among the major players operating in the market.
Challenges include:
High Development and Operational Costs: High development and operational costs pose a significant restraint on the growth of the AI in Retail and E-Commerce market.
As of 2025:
1. North America: Leads the market with share of 41.25%.
2. Europe: Holds a significants share of 26.83%.
3. Asia-Pacific: The fastest-growing region, with a projected CAGR of 42.4% during 2026–2034.
The software segment held the largest share of the market in 2025, serving as the foundation for high-throughput, precision-driven AI operations.
The market growth is primarily driven by:
1. Rising Adoption of AI for Personalized Shopping and Recommendation Engines
2. Increasing Use of AI in Inventory Management and Demand Forecasting
3. Growing Demand for Automated Customer Support and Chatbots
The global AI in Retail and E-Commerce market is valued at ~ US$19.98 billion in 2025 and is expected to reach US$398.65 billion by 2034; it is expected to register a CAGR of 40.3% during 2026–2034.
1. Executive Summary
1.1 Analyst Market Outlook
1.2 Market Attractiveness
2. AI in Retail and E-Commerce Market Landscape
2.1 Overview
2.2 Value Chain Analysis
2.2.1 Raw Materials/Components
2.2.2 Retail and E-Commerce Process/Technology
2.2.3 Distribution Landscape
2.2.4 End–User
2.2.5 Level of Integration
2.3 Supply Chain Analysis
2.3.1 List of Manufacturers/Suppliers
2.3.2 List of Potential Customers (Upto 50)
2.4 Porter`s Five Force Analysis
2.5 PEST Analysis
2.6 Impact of Artificial Intelligence (AI)
2.7 Regulatory Framework
3. Competitive Landscape
3.1 Company Benchmarking by Key Players
3.2 Market Share Analysis, 2025 – By Key Players
3.3 Market Concentration
4. AI in Retail and E-Commerce Market – Key Industry Dynamics
4.1 Market Drivers
4.2 Market Restraints
4.3 Market Opportunities
4.4 Future Trends
4.5 Impact of Drivers and Restraints
5. AI in Retail and E-Commerce Market – Global Market Analysis
5.1 AI in Retail and E-Commerce Market Revenue (US$ Million), 2021–2034
5.2 AI in Retail and E-Commerce Market Forecast and Analysis
6. AI in Retail and E-Commerce Market Revenue Analysis – Component
6.1 AI in Retail and E-Commerce Market Forecasts and Analysis by Component
6.2 Hardware
6.2.1 Overview
6.2.2 Hardware Market Revenue, 2021–2034 (US$ Million)
6.3 Software
6.3.1 Overview
6.3.2 Software Market Revenue, 2021–2034 (US$ Million)
6.4 Services
6.4.1 Overview
6.4.2 Services Market Revenue, 2021–2034 (US$ Million)
7. AI in Retail and E-Commerce Market Revenue Analysis – Deployment
7.1 AI in Retail and E-Commerce Market Forecasts and Analysis by Deployment
7.2 Cloud
7.2.1 Overview
7.2.2 Cloud Market Revenue, 2021–2034 (US$ Million)
7.3 On-Premises
7.3.1 Overview
7.3.2 On-Premises Market Revenue, 2021–2034 (US$ Million)
8. AI in Retail and E-Commerce Market Revenue Analysis – Organization Size
8.1 AI in Retail and E-Commerce Market Forecasts and Analysis by Organization Size
8.2 Large Enterprises
8.2.1 Overview
8.2.2 Large Enterprises Market Revenue, 2021–2034 (US$ Million)
8.3 SMEs
8.3.1 Overview
8.3.2 SMEs Market Revenue, 2021–2034 (US$ Million)
9. AI in Retail and E-Commerce Market – Geographical Analysis
9.1 North America
9.1.1 North America AI in Retail and E-Commerce Market Overview
9.1.2 North America: AI in Retail and E-Commerce Market Revenue and Forecasts, 2021–2034 (US$ Million)
9.1.3 North America: AI in Retail and E-Commerce Market – By Segmentation
9.1.3.1 Component
9.1.3.2 Deployment
9.1.3.3 Organization Size
9.1.4 North America: AI in Retail and E-Commerce Market Breakdown by Countries
9.1.4.1 United States Market
9.1.4.1.1 United States: AI in Retail and E-Commerce Market Revenue and Forecasts, 2021–2034 (US$ Million)
9.1.4.1.2 United States: AI in Retail and E-Commerce Market – By Segmentation
9.1.4.1.2.1 Component
9.1.4.1.2.2 Deployment
9.1.4.1.2.3 Organization Size
9.1.4.2 Canada Market
9.1.4.3 Mexico Market
9.2 Europe
9.2.1 Germany
9.2.2 France
9.2.3 Italy
9.2.4 United Kingdom
9.2.5 Russia
9.2.6 Rest of Europe
9.3 Asia-Pacific
9.3.1 Australia
9.3.2 China
9.3.3 India
9.3.4 Japan
9.3.5 South Korea
9.3.6 Rest of Asia-Pacific
9.4 Middle East and Africa
9.4.1 South Africa
9.4.2 Saudi Arabia
9.4.3 U.A.E
9.4.4 Rest of Middle East and Africa
9.5 South and Central America
9.5.1 Brazil
9.5.2 Argentina
9.5.3 Rest of South and Central America
10. AI in Retail and E-Commerce Market Industry Landscape
11. AI in Retail and E-Commerce Market – Key Company Profiles
11.1 Accenture Plc
11.1.1 Key Facts
11.1.2 Business Description
11.1.3 Products and Services
11.1.4 Financial Overview
11.1.5 SWOT Analysis
11.1.6 Key Developments
11.2 Advanced Micro Devices Inc
11.3 Google LLC
11.4 International Business Machines Corp
11.5 Intel Corp
11.6 Microsoft Corp
11.7 NVIDIA Corp
11.8 Amazon Web Services Inc
11.9 SAP SE
11.10 SAS Institute Inc
12. List of Additional Companies Analyzed
13. Appendix
13.1 Glossary
13.2 List of Tables
13.3 List of Figures
13.2 Research Methodology and Approach
13.2.1 Secondary Research
13.2.2 Primary Research
13.2.3 Market Estimation Approach
13.2.3.1 Supply Side Analysis
13.2.3.2 Demand Side Analysis
13.2.4 Research Assumptions and Limitations
13.3 Meet Our Analysts
13.4 About The Insight Partners
13.5 Market Intelligence Cloud
List of TablesTable 1. List of Regulatory Bodies and Organizations
Table 2. AI in Retail and E-Commerce Market Revenue, 2021–2025 (US$ Million)
Table 3. AI in Retail and E-Commerce Market Revenue, 2026–2034 (US$ Million)
Table 4. North America AI in Retail and E-Commerce Market Revenue, 2021–2025 (US$ Million) – Component
Table 5. North America AI in Retail and E-Commerce Market Revenue and Forecasts, 2026–2034 (US$ Million) – Component
Table 6. North America AI in Retail and E-Commerce Market Revenue, 2021–2025 (US$ Million) – Deployment
Table 7. North America AI in Retail and E-Commerce Market Revenue and Forecasts, 2026–2034 (US$ Million) – Deployment
Table 8. North America AI in Retail and E-Commerce Market Revenue, 2021–2025 (US$ Million) – Organization Size
Table 9. North America AI in Retail and E-Commerce Market Revenue and Forecasts, 2026–2034 (US$ Million) – Organization Size
Table 10. United States: AI in Retail and E-Commerce Market Revenue, 2021–2025 (US$ Million) – Component
Table 11. United States: AI in Retail and E-Commerce Market Revenue and Forecasts, 2026–2034 (US$ Million) – Component
Table 12. United States: AI in Retail and E-Commerce Market Revenue, 2021–2025 (US$ Million) – Deployment
Table 13. United States: AI in Retail and E-Commerce Market Revenue and Forecasts, 2026–2034 (US$ Million) – Deployment
Table 14. United States: AI in Retail and E-Commerce Market Revenue, 2021–2025 (US$ Million) – Organization Size
Table 15. United States: AI in Retail and E-Commerce Market Revenue and Forecasts, 2026–2034 (US$ Million) – Organization Size
Table 16. List of Additional Companies Analyzed
Table 17. Glossary – AI in Retail and E-Commerce Market
???????List of FiguresFigure 1. AI in Retail and E-Commerce Market – Value Chain Analysis. 9
Figure 2. Porter’s Five Forces Analysis
Figure 3. Pest Analysis
Figure 4. AI in Retail and E-Commerce Market – Key Industry Dynamics
Figure 5. Impact Analysis of Drivers and Restraints
Figure 6. AI in Retail and E-Commerce Market Revenue (US$ Million), 2021–2034
Figure 7. AI in Retail and E-Commerce Market Share (%) – Component, 2025 and 2034
Figure 8. Hardware Market Revenue and Forecasts, 2021–2034 (US$ Million)
Figure 9. Software Market Revenue and Forecasts, 2021–2034 (US$ Million)
Figure 10. Services Market Revenue and Forecasts, 2021–2034 (US$ Million)
Figure 11. AI in Retail and E-Commerce Market Share (%) – Deployment, 2025 and 2034
Figure 12. Cloud Market Revenue and Forecasts, 2021–2034 (US$ Million)
Figure 13. On-Premises Market Revenue and Forecasts, 2021–2034 (US$ Million)
Figure 14. AI in Retail and E-Commerce Market Share (%) – Organization Size, 2025 and 2034
Figure 15. Large Enterprises Market Revenue and Forecasts, 2021–2034 (US$ Million)
Figure 16. SMEs Market Revenue and Forecasts, 2021–2034 (US$ Million)
Figure 17. AI in Retail and E-Commerce Market Breakdown by Geography, 2025 and 2034
Figure 18. North America: AI in Retail and E-Commerce Market Revenue and Forecasts, 2021–2034 (US$ Million)
Figure 19. North America: AI in Retail and E-Commerce Market Breakdown by Key Countries, 2025 and 2034 (%)
Figure 20. United States: AI in Retail and E-Commerce Market Revenue and Forecasts, 2021–2034 (US$ Million)
Figure 21. Bottom–Up Approach and Top–Down Approach
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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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