AI Training Dataset Market

AI Training Dataset Market Size by Type (Image/Video, Text, Audio), Vertical (Automotive, Healthcare, Retail & E-commerce, IT, BFSI, Government, Others), Regions, Global Industry Analysis, Share, Growth, Trends, and Forecast 2024 to 2033

Base Year: 2022 Historical Data: 2019-21
  • Report ID: TBI-13562
  • Published Date: Jul, 2024
  • Pages: 239
  • Category: Information Technology & Semiconductors
  • Format: PDF
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The global AI training dataset market was valued at USD 1.64 billion in 2023, which is anticipated to grow at a CAGR of 24.25% from 2024 to 2033. Manufacturing, IT, BFSI, retail & e-commerce, and healthcare are just a few industries where AI is becoming increasingly important. New entrants have more opportunities due to the rising demand for application-specific training data. Artificial intelligence (AI) is becoming increasingly important for big data since the technology enables the extraction of highly complex representations through a hierarchical learning process, necessitating the mining and extraction of meaningful patterns from vast amounts of data. The rising adoption of cloud computing will also drive the market because it offers scalable storage solutions, making it easy to store and manage large datasets.

Market Introduction:

AI enables machines to carry out activities similar to those performed by humans, learn from their mistakes, and adjust to new inputs. To do a specific task, these machines are trained to scan large amounts of data and look for patterns. For these machines to learn, specific datasets are required. The demand for AI training datasets is increasing to address this need. The production of massive volumes of data and technical improvements essentially fuel the growth of the AI training dataset market. In addition, variables like machine learning and intelligence are developing significantly. The lack of technological knowledge in emerging nations partially hampers market expansion. Additionally, during the forecast period, there will likely be numerous chances for market expansion due to the growing functionality of training data sets across various industry verticals. Artificial intelligence includes machine learning as a subset. It allows AI to use data to learn and make decisions. Without any specific system programming, this process takes place. Since big data involves capturing, storing, and analyzing a sizable amount of data, its introduction is projected to fuel the growth of the AI market. The demand for AI datasets is increasing significantly due to the fast adoption of AI technology. Different end-use sectors seek to establish processes that make working remotely as beneficial and efficient as working from an office. They are also concentrating on the necessity of monitoring systems and improving computational models. With the support of artificial intelligence (AI), machines can carry out human-like functions and adapt to new inputs. To do a specific task, these machines are programmed to process vast amounts of data and identify patterns. Specific datasets are needed to get these devices ready. To meet this need, the market for AI training datasets is growing. Machine learning is an artificial intelligence (AI) application that enables systems to learn from experience and develop without being explicitly programmed. The main goal of machine learning is to create software that can acquire and use data to learn on its own. The information used to train a machine learning model is known as AI training data. The training set, training dataset, learning group, and ground truth data are also considered sources of AI training data in data science. These training datasets contain both the expected output and the related input data. Considerable effort goes into curating and standardizing dataset formats to make them easier for machine learning research because datasets exist in various formats and can occasionally be challenging. A web platform called OpenML comes with R, Python, Java, and other APIs for downloading hundreds of machine learning datasets, analyzing algorithms on datasets, and comparing the performance of algorithms with those of many other algorithms. For testing supervised machine learning algorithms, PMLB has a sizable, carefully curated archive of benchmark datasets. It provides classification and regression datasets in a consistent format that may be accessed via a Python API.

AI Training Dataset Market Size

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Recent Development
  • In June 2022, Amazon Web Services Inc. added new tools to its cloud platform to make it simpler for programmers to develop code and create training datasets for their artificial intelligence-based projects.
  • In July 2021, Amazon and Hugging Face, a provider of open-source natural language processing (NLP) technologies, have collaborated. The objective of this partnership was to accelerate the deployment of sophisticated NLP capabilities while making it easier for businesses to use cutting-edge machine-learning models. Following this partnership, Hugging Face will suggest Amazon Web Services as a cloud service provider for its clients.
  • In June 2021, Scale AI and MIT Media Lab, a Massachusetts Institute of Technology research centre, began working together. To help doctors treat patients more effectively, this cooperation attempted to utilize ML in healthcare.
  • Darktrace, a leading supplier of autonomous AI for cyber security, and Microsoft collaborated in May 2021. This partnership seeks to offer unparalleled defence against advanced threats as businesses move to the cloud.

Market Dynamics:

Drivers

Machine learning and AI are expanding quickly- The introduction of big data, which includes the recording, storing, and processing of a substantial amount of data, is projected to promote the growth of the artificial intelligence sector. As the use of artificial intelligence grows, a sharp increase in demand for training datasets is anticipated. This is because annotated data encourages the creation of artificial intelligence (AI) models and machine learning systems in essential fields like speech recognition and image identification. Many public and private organizations employ a variety of applications to gather domain-specific data, including those for national intelligence, fraud detection, marketing, medical informatics, and cybersecurity. Due to datasets, which progressively increase the precision of each piece of knowledge, unstructured and unsupervised data can be classified.

Opportunities:

Expanding uses of training datasets in several industry verticals- The collecting and distribution of a vast amount of visual and digital data have been made possible by an increase in applications, websites, social networks, and other digital channels. Many companies have used this data-annotated, freely accessible web content to provide their clients with superior products. Unstructured text data gathered due to the increased usage of electronic health record (EHR) systems is one of the most crucial resources for clinical research. Throughout the projection period, it is anticipated that increasing applications in numerous sectors will generate enormous potential for market growth.

Regional segmentation analysis:

The regions analyzed for the market include North America, Europe, South America, Asia Pacific, the Middle East, and Africa. North America emerged as the most significant global AI training dataset market, with a 31.63% market revenue share in 2023. To speed up the adoption of artificial intelligence technology in North America's growing sectors, companies in that business are concentrating on releasing new datasets.

North America Region AI Training Dataset Market Share in 2023 - 31.63%

 

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  • For instance, a new dataset for driverless vehicles was provided in September 2020 by Waymo LLC, a subsidiary of Google LLC. This dataset contains sensor data gathered using video sensors and LiDAR in various driving scenarios, including pedestrians, cyclists, and other road users, as well as signs and other obstructions. These new advancements are influencing dataset adoption in the market, serving a sizable portion of the market.
Type Segment Analysis

The type segment is divided into image/video, text, and audio. The text segment dominated, with a market share of around 35.02% in 2023. The reason for this is the extensive use of text datasets in the IT industry for various automation processes, including speech recognition, text classification, and caption generation.

However, because so many different audio datasets are available, the audio segment is predicted to serve a moderate market share. These consist of audio datasets for the environment, voice datasets, speech commands, the Multimodal Emotion Lines Dataset (MELD), and music datasets.

Vertical Segment Analysis

The vertical segment is divided into automotive, healthcare, retail & e-commerce, IT, BFSI, government, and others. The IT segment dominated the market, with a market share of around 16.53% in 2023. Various technology companies are adopting machine learning technologies to improve user experience and create cutting-edge products. Machine learning technology needs high-quality training data to ensure that ML algorithms are continuously optimized. Additionally, high-quality datasets support IT businesses in improving a range of solutions, including computer vision, crowdsourcing, data analytics, virtual assistants, and others. The industry's heavy reliance on training datasets results from such circumstances.

  • For instance, to support the development of more effective AI models for image-based buying, Amazon released the Amazon Berkeley Objects, a sizable dataset, in June 2021.
Some of the Key Market Players:
  • Appen Limited
  • Lionbridge Technologies, Inc.
  • Microsoft Corporation
  • Samasource Inc.
  • Deep Vision Data
  • Google, LLC (Kaggle)
  • Amazon Web Services, Inc.
  • Alegion
  • Cogito Tech LLC
  • Scale AI Inc.

Report Description:

Attribute Description
Market Size Revenue (USD Billion)
Market size value in 2023 USD 1.64 Billion
Market size value in 2033 USD 14.42 Billion
CAGR (2024 to 2033) 24.25%
Historical data 2020-2022
Base Year 2023
Forecast 2024-2033
Region The regions analyzed for the market are Asia Pacific, Europe, South America, North America, and Middle East & Africa. Furthermore, the regions are further analyzed at the country level.
Segments Type, Vertical

Frequesntly Asked Questions

As per The Brainy Insights, the size of the AI training dataset market was valued at USD 1.64 Billion in 2023 & USD 14.42 Billion by 2033.

Global AI training dataset market is growing at a CAGR of 24.25% during the forecast period 2024-2033.

North America region emerged as the largest market for the AI training dataset.

Machine learning and AI are expanding quickly is a significant driving factor for the growth of the AI training dataset market.

Expanding uses of training datasets in several industry verticals is a significant opportunity for the growth of the AI training dataset market.

Key players are Appen Limited, Lionbridge Technologies, Inc., Microsoft Corporation, Samasource Inc., Deep Vision Data, Google, LLC (Kaggle), Amazon Web Services, Inc., Alegion, Cogito Tech LLC, Scale AI Inc., among others.

1. Introduction
    1.1. Objective of the Study
    1.2. Market Definition
    1.3. Research Scope
    1.4. Currency
    1.5. Key Target Audience

2. Research Methodology and Assumptions

3. Executive Summary

4. Premium Insights
    4.1. Porter’s Five Forces Analysis
    4.2. Value Chain Analysis
    4.3. Top Investment Pockets
          4.3.1. Market Attractiveness Analysis By Type
          4.3.2. Market Attractiveness Analysis By Vertical
          4.3.3. Market Attractiveness Analysis By Region
    4.4. Industry Trends

5. Market Dynamics
    5.1. Market Evaluation
    5.2. Drivers
          5.2.1. Machine learning and AI are expanding quickly
    5.3. Opportunities
          5.3.1. Expanding uses of training datasets in several industry verticals

6. Global AI Training Dataset Market Analysis and Forecast, By Type
    6.1. Segment Overview
    6.2. Image/Video
    6.3. Text
    6.4. Audio

7. Global AI Training Dataset Market Analysis and Forecast, By Vertical
    7.1. Segment Overview
    7.2. Automotive
    7.3. Healthcare
    7.4. Retail & E-commerce
    7.5. IT
    7.6. BFSI
    7.7. Government
    7.8. Others

8. Global AI Training Dataset Market Analysis and Forecast, By Regional Analysis
    8.1. Segment Overview
    8.2. North America
          8.2.1. U.S.
          8.2.2. Canada
          8.2.3. Mexico
    8.3. Europe
          8.3.1. Germany
          8.3.2. France
          8.3.3. U.K.
          8.3.4. Italy
          8.3.5. Spain
    8.4. Asia-Pacific
          8.4.1. Japan
          8.4.2. China
          8.4.3. India
    8.5. South America
          8.5.1. Brazil
    8.6. Middle East and Africa
          8.6.1. UAE
          8.6.2. South Africa

9. Global AI Training Dataset Market-Competitive Landscape
    9.1. Overview
    9.2. Market Share of Key Players in the AI Training Dataset Market
          9.2.1. Global Company Market Share
          9.2.2. North America Company Market Share
          9.2.3. Europe Company Market Share
          9.2.4. APAC Company Market Share
    9.3. Competitive Situations and Trends
          9.3.1. Product Launches and Developments
          9.3.2. Partnerships, Collaborations, and Agreements
          9.3.3. Mergers & Acquisitions
          9.3.4. Expansions

10. Company Profiles
    10.1. Appen Limited
          10.1.1. Business Overview
          10.1.2. Company Snapshot
          10.1.3. Company Market Share Analysis
          10.1.4. Company Product Portfolio
          10.1.5. Recent Developments
          10.1.6. SWOT Analysis
    10.2. Lionbridge Technologies, Inc.
          10.2.1. Business Overview
          10.2.2. Company Snapshot
          10.2.3. Company Market Share Analysis
          10.2.4. Company Product Portfolio
          10.2.5. Recent Developments
          10.2.6. SWOT Analysis
    10.3. Microsoft Corporation
          10.3.1. Business Overview
          10.3.2. Company Snapshot
          10.3.3. Company Market Share Analysis
          10.3.4. Company Product Portfolio
          10.3.5. Recent Developments
          10.3.6. SWOT Analysis
    10.4. Samasource Inc.
          10.4.1. Business Overview
          10.4.2. Company Snapshot
          10.4.3. Company Market Share Analysis
          10.4.4. Company Product Portfolio
          10.4.5. Recent Developments
          10.4.6. SWOT Analysis
    10.5. Deep Vision Data
          10.5.1. Business Overview
          10.5.2. Company Snapshot
          10.5.3. Company Market Share Analysis
          10.5.4. Company Product Portfolio
          10.5.5. Recent Developments
          10.5.6. SWOT Analysis
    10.6. Google, LLC (Kaggle)
          10.6.1. Business Overview
          10.6.2. Company Snapshot
          10.6.3. Company Market Share Analysis
          10.6.4. Company Product Portfolio
          10.6.5. Recent Developments
          10.6.6. SWOT Analysis
    10.7. Amazon Web Services, Inc.
          10.7.1. Business Overview
          10.7.2. Company Snapshot
          10.7.3. Company Market Share Analysis
          10.7.4. Company Product Portfolio
          10.7.5. Recent Developments
          10.7.6. SWOT Analysis
    10.8. Alegion
          10.8.1. Business Overview
          10.8.2. Company Snapshot
          10.8.3. Company Market Share Analysis
          10.8.4. Company Product Portfolio
          10.8.5. Recent Developments
          10.8.6. SWOT Analysis
    10.9. Cogito Tech LLC
          10.9.1. Business Overview
          10.9.2. Company Snapshot
          10.9.3. Company Market Share Analysis
          10.9.4. Company Product Portfolio
          10.9.5. Recent Developments
          10.9.6. SWOT Analysis
    10.10. Scale AI Inc.
          10.10.1. Business Overview
          10.10.2. Company Snapshot
          10.10.3. Company Market Share Analysis
          10.10.4. Company Product Portfolio
          10.10.5. Recent Developments
          10.10.6. SWOT Analysis

List of Table

1. Global AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

2. Global Image/Video, AI Training Dataset Market, By Region, 2020-2033 (USD Billion) 

3. Global Text, AI Training Dataset Market, By Region, 2020-2033 (USD Billion)

4. Global Audio, AI Training Dataset Market, By Region, 2020-2033 (USD Billion)

5. Global AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion) 

6. Global Automotive, AI Training Dataset Market, By Region, 2020-2033 (USD Billion) 

7. Global Healthcare, AI Training Dataset Market, By Region, 2020-2033 (USD Billion)

8. Global Retail & E-commerce, AI Training Dataset Market, By Region, 2020-2033 (USD Billion) 

9. Global IT, AI Training Dataset Market, By Region, 2020-2033 (USD Billion)

10. Global BFSI, AI Training Dataset Market, By Region, 2020-2033 (USD Billion)

11. Global Government, AI Training Dataset Market, By Region, 2020-2033 (USD Billion)

12. Global Others, AI Training Dataset Market, By Region, 2020-2033 (USD Billion)

13. Global AI Training Dataset Market, By Region, 2020-2033 (USD Billion) 

14. North America AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

15. North America AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion) 

16. U.S. AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

17. U.S. AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion)

18. Canada AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

19. Canada AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion)

20. Mexico AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

21. Mexico AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion)

22. Europe AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

23. Europe AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion)

24. Germany AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

25. Germany AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion)

26. France AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

27. France AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion)

28. U.K. AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

29. U.K. AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion)

30. Italy AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

31. Italy AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion)

32. Spain AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

33. Spain AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion)

34. Asia Pacific AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

35. Asia Pacific AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion)

36. Japan AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

37. Japan AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion)

38. China AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

39. China AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion)

40. India AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

41. India AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion)

42. South America AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

43. South America AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion)

44. Brazil AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

45. Brazil AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion)

46. Middle East and Africa AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

47. Middle East and Africa AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion)

48. UAE AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

49. UAE AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion)

50. South Africa AI Training Dataset Market, By Type, 2020-2033 (USD Billion) 

51. South Africa AI Training Dataset Market, By Vertical, 2020-2033 (USD Billion)

List of Figures 

1. Global AI Training Dataset Market Segmentation

2. AI Training Dataset Market: Research Methodology

3. Market Size Estimation Methodology: Bottom-Up Approach

4. Market Size Estimation Methodology: Top-Down Approach

5. Data Triangulation

6. Porter’s Five Forces Analysis 

7. Value Chain Analysis 

8. Global AI Training Dataset Market Attractiveness Analysis By Type

9. Global AI Training Dataset Market Attractiveness Analysis By Vertical

10. Global AI Training Dataset Market Attractiveness Analysis By Region

11. Global AI Training Dataset Market: Dynamics

12. Global AI Training Dataset Market Share by Type (2023 & 2033)

13. Global AI Training Dataset Market Share by Vertical (2023 & 2033)

14. Global AI Training Dataset Market Share by Regions (2023 & 2033)

15. Global AI Training Dataset Market Share by Company (2023)

This study forecasts revenue at global, regional, and country levels from 2019 to 2032. The Brainy Insights has segmented the global AI training dataset market based on below mentioned segments:

Global AI Training Dataset by Type:

  • Image/Video
  • Text
  • Audio

Global AI Training Dataset by Vertical:

  • Automotive
  • Healthcare
  • Retail & E-commerce
  • IT
  • BFSI
  • Government
  • Others

Global AI Training Dataset by Region:

  • North America
    • U.S.
    • Canada
    • Mexico
  • Europe
    • Germany
    • France
    • U.K.
    • Italy
    • Spain
  • Asia-Pacific
    • Japan
    • China
    • India
  • South America
    • Brazil
  • Middle East and Africa  
    • UAE
    • South Africa

Methodology

Research has its special purpose to undertake marketing efficiently. In this competitive scenario, businesses need information across all industry verticals; the information about customer wants, market demand, competition, industry trends, distribution channels etc. This information needs to be updated regularly because businesses operate in a dynamic environment. Our organization, The Brainy Insights incorporates scientific and systematic research procedures in order to get proper market insights and industry analysis for overall business success. The analysis consists of studying the market from a miniscule level wherein we implement statistical tools which helps us in examining the data with accuracy and precision. 

Our research reports feature both; quantitative and qualitative aspects for any market. Qualitative information for any market research process are fundamental because they reveal the customer needs and wants, usage and consumption for any product/service related to a specific industry. This in turn aids the marketers/investors in knowing certain perceptions of the customers. Qualitative research can enlighten about the different product concepts and designs along with unique service offering that in turn, helps define marketing problems and generate opportunities. On the other hand, quantitative research engages with the data collection process through interviews, e-mail interactions, surveys and pilot studies. Quantitative aspects for the market research are useful to validate the hypotheses generated during qualitative research method, explore empirical patterns in the data with the help of statistical tools, and finally make the market estimations.

The Brainy Insights offers comprehensive research and analysis, based on a wide assortment of factual insights gained through interviews with CXOs and global experts and secondary data from reliable sources. Our analysts and industry specialist assume vital roles in building up statistical tools and analysis models, which are used to analyse the data and arrive at accurate insights with exceedingly informative research discoveries. The data provided by our organization have proven precious to a diverse range of companies, facilitating them to address issues such as determining which products/services are the most appealing, whether or not customers use the product in the manner anticipated, the purchasing intentions of the market and many others.

Our research methodology encompasses an idyllic combination of primary and secondary initiatives. Key phases involved in this process are listed below:

MARKET RESEARCH PROCESS

Data Procurement:

The phase involves the gathering and collecting of market data and its related information with the help of different sources & research procedures.

The data procurement stage involves in data gathering and collecting through various data sources.

This stage involves in extensive research. These data sources includes:

Purchased Database: Purchased databases play a crucial role in estimating the market sizes irrespective of the domain. Our purchased database includes:

  • The organizational databases such as D&B Hoovers, and Bloomberg that helps us to identify the competitive scenario of the key market players/organizations along with the financial information.
  • Industry/Market databases such as Statista, and Factiva provides market/industry insights and deduce certain formulations. 
  • We also have contractual agreements with various reputed data providers and third party vendors who provide information which are not limited to:
    • Import & Export Data
    • Business Trade Information
    • Usage rates of a particular product/service on certain demographics mainly focusing on the unmet prerequisites

Primary Research: The Brainy Insights interacts with leading companies and experts of the concerned domain to develop the analyst team’s market understanding and expertise. It improves and substantiates every single data presented in the market reports. Primary research mainly involves in telephonic interviews, E-mail interactions and face-to-face interviews with the raw material providers, manufacturers/producers, distributors, & independent consultants. The interviews that we conduct provides valuable data on market size and industry growth trends prevailing in the market. Our organization also conducts surveys with the various industry experts in order to gain overall insights of the industry/market. For instance, in healthcare industry we conduct surveys with the pharmacists, doctors, surgeons and nurses in order to gain insights and key information of a medical product/device/equipment which the customers are going to usage. Surveys are conducted in the form of questionnaire designed by our own analyst team. Surveys plays an important role in primary research because surveys helps us to identify the key target audiences of the market. Additionally, surveys helps to identify the key target audience engaged with the market. Our survey team conducts the survey by targeting the key audience, thus gaining insights from them. Based on the perspectives of the customers, this information is utilized to formulate market strategies. Moreover, market surveys helps us to understand the current competitive situation of the industry. To be precise, our survey process typically involve with the 360 analysis of the market. This analytical process begins by identifying the prospective customers for a product or service related to the market/industry to obtain data on how a product/service could fit into customers’ lives.

Secondary Research: The secondary data sources includes information published by the on-profit organizations such as World bank, WHO, company fillings, investor presentations, annual reports, national government documents, statistical databases, blogs, articles, white papers and others. From the annual report, we analyse a company’s revenue to understand the key segment and market share of that organization in a particular region. We analyse the company websites and adopt the product mapping technique which is important for deriving the segment revenue. In the product mapping method, we select and categorize the products offered by the companies catering to domain specific market, deduce the product revenue for each of the companies so as to get overall estimation of the market size. We also source data and analyses trends based on information received from supply side and demand side intermediaries in the value chain. The supply side denotes the data gathered from supplier, distributor, wholesaler and the demand side illustrates the data gathered from the end customers for respective market domain.

The supply side for a domain specific market is analysed by:

  • Estimating and projecting penetration rates through analysing product attributes, availability of internal and external substitutes, followed by pricing analysis of the product.
  • Experiential assessment of year-on-year sales of the product by conducting interviews.

The demand side for the market is estimated through:

  • Evaluating the penetration level and usage rates of the product.
  • Referring to the historical data to determine the growth rate and evaluate the industry trends

In-house Library: Apart from these third-party sources, we have our in-house library of qualitative and quantitative information. Our in-house database includes market data for various industry and domains. These data are updated on regular basis as per the changing market scenario. Our library includes, historic databases, internal audit reports and archives.

Sometimes there are instances where there is no metadata or raw data available for any domain specific market. For those cases, we use our expertise to forecast and estimate the market size in order to generate comprehensive data sets. Our analyst team adopt a robust research technique in order to produce the estimates:

  • Applying demographic along with psychographic segmentation for market evaluation
  • Determining the Micro and Macro-economic indicators for each region 
  • Examining the industry indicators prevailing in the market. 

Data Synthesis: This stage involves the analysis & mapping of all the information obtained from the previous step. It also involves in scrutinizing the data for any discrepancy observed while data gathering related to the market. The data is collected with consideration to the heterogeneity of sources. Robust scientific techniques are in place for synthesizing disparate data sets and provide the essential contextual information that can orient market strategies. The Brainy Insights has extensive experience in data synthesis where the data passes through various stages:

  • Data Screening: Data screening is the process of scrutinising data/information collected from primary research for errors and amending those collected data before data integration method. The screening involves in examining raw data, identifying errors and dealing with missing data. The purpose of the data screening is to ensure data is correctly entered or not. The Brainy Insights employs objective and systematic data screening grades involving repeated cycles of quality checks, screening and suspect analysis.
  • Data Integration: Integrating multiple data streams is necessary to produce research studies that provide in-depth picture to the clients. These data streams come from multiple research studies and our in house database. After screening of the data, our analysts conduct creative integration of data sets, optimizing connections between integrated surveys and syndicated data sources. There are mainly 2 research approaches that we follow in order to integrate our data; top down approach and bottom up approach.

Market Deduction & Formulation: The final stage comprises of assigning data points at appropriate market spaces so as to deduce feasible conclusions. Analyst perspective & subject matter expert based holistic form of market sizing coupled with industry analysis also plays a crucial role in this stage.

This stage involves in finalization of the market size and numbers that we have collected from data integration step. With data interpolation, it is made sure that there is no gap in the market data. Successful trend analysis is done by our analysts using extrapolation techniques, which provide the best possible forecasts for the market.

Data Validation & Market Feedback: Validation is the most important step in the process. Validation & re-validation via an intricately designed process helps us finalize data-points to be used for final calculations.

The Brainy Insights interacts with leading companies and experts of the concerned domain to develop the analyst team’s market understanding and expertise. It improves and substantiates every single data presented in the market reports. The data validation interview and discussion panels are typically composed of the most experienced industry members. The participants include, however, are not limited to:

  • CXOs and VPs of leading companies’ specific to sector
  • Purchasing managers, technical personnel, end-users
  • Key opinion leaders such as investment bankers, and industry consultants

Moreover, we always validate our data and findings through primary respondents from all the major regions we are working on.

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