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Global Insight Engines Market to reach USD 7151.68 million by the end of 2030

Global Insight Engines Market Size study & Forecast, by Component (Software and Services) by Deployment Type (On-premises and Cloud), by Size of the Enterprise (Small and Medium-Sized Enterprises and Large Enterprises), by End-user Industry (BFSI, Retail, IT and Telecom) and Regional Analysis, 2023-2030

Product Code: ICTICTI-21179860
Publish Date: 27-06-2023
Page: 200

Global Insight Engines Market is valued approximately USD 1162.14 million in 2022 and is anticipated to grow with a healthy growth rate of more than 25.5% over the forecast period 2023-2030. The insight engines market refers to the industry focused on providing advanced search and data analysis solutions that enable organizations to extract meaningful insights from their vast amounts of data. Insight engines combine artificial intelligence (AI), natural language processing (NLP), and machine learning techniques to deliver powerful search capabilities and data analysis functionalities. The major driving factors for the Global Insight Engines Market are rising amount of data and growing IT investment in cognitive search. Moreover, rising initiatives by key market players and technological advancement in the market is creating lucrative growth opportunity for the market over the forecast period 2023-2030.

Accenture estimates that there are 44 zettabytes of data available, which is expanding quickly. Eighty percent of this data is unstructured (text documents, audio, video, emails, social media posts, etc.), and twenty percent is stored in some sort of structured system. The capacity to extract facts from documents and store those data somewhere for easy access is required in order to acquire insights from this enormous resource and pinpoint what a user or organisation requires. Search engine goliaths like Google and Bing accomplish this by storing such details in a ‘knowledge graph,’ which is appropriate for the search engines they have been using for many years. Along with this, an IT and services startup called KDNuggets predicts that businesses will spend 15% of their IT budgets on cloud-based solutions for cognitive search, analytics, and other services. By 2021, it was expected that this investment would increase to 35%. However, the high cost of Insight Engines stifles market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Insight Engines Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America is considered a prominent market for insight engines. The region is home to several major technology companies and has a mature technology infrastructure. The United States, in particular, has a strong presence of insight engine vendors and a high adoption rate of advanced search and analytics solutions. The Asia Pacific region is witnessing rapid growth in the adoption of insight engines. Countries like China, Japan, India, and Australia are investing in digital transformation initiatives and leveraging AI technologies to improve business operations. The region presents significant growth opportunities for insight engine vendors.

Major market player included in this report are:
Elastic NV
Coveo Solutions Inc.
IBM Corporation
Dassault Systèmes
Mindbreeze GmbH
Smartlogic Semantic AI

Recent Developments in the Market:
Ø In July 2020, Microsoft introduced a preview feature of text analytics for healthcare. This feature empowers developers to analyze and derive valuable insights from unstructured medical data.

Global Insight Engines Market Report Scope:
ü Historical Data – 2020 – 2021
ü Base Year for Estimation – 2022
ü Forecast period – 2023-2030
ü Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
ü Segments Covered – Component, Deployment Type, Size of the Enterprise, End-user Industry, Region
ü Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
ü Customization Scope – Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and Component offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Component:
By Deployment Type:
By Size of the Enterprise:
Small and Medium-Sized Enterprises
Large Enterprises
By End-user Industry:
IT and Telecom

By Region:

North America


Asia Pacific
South Korea

Latin America

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Million)
1.2.1. Insight Engines Market, by Region, 2020-2030 (USD Million)
1.2.2. Insight Engines Market, by Component, 2020-2030 (USD Million)
1.2.3. Insight Engines Market, by Deployment Type, 2020-2030 (USD Million)
1.2.4. Insight Engines Market, by Size of the Enterprise, 2020-2030 (USD Million)
1.2.5. Insight Engines Market, by End-user Industry, 2020-2030 (USD Million)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Insight Engines Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Insight Engines Market Dynamics
3.1. Insight Engines Market Impact Analysis (2020-2030)
3.1.1. Market Drivers Increasing amount of data Growing IT investment in cognitive search
3.1.2. Market Challenges High Cost of Insight Engines
3.1.3. Market Opportunities Advancements in Formulation
Chapter 4. Global Insight Engines Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global Insight Engines Market, by Component
5.1. Market Snapshot
5.2. Global Insight Engines Market by Component, Performance – Potential Analysis
5.3. Global Insight Engines Market Estimates & Forecasts by Component 2020-2030 (USD Million)
5.4. Insight Engines Market, Sub Segment Analysis
5.4.1. Software
5.4.2. Services
Chapter 6. Global Insight Engines Market, by Deployment Type
6.1. Market Snapshot
6.2. Global Insight Engines Market by Deployment Type, Performance – Potential Analysis
6.3. Global Insight Engines Market Estimates & Forecasts by Deployment Type 2020-2030 (USD Million)
6.4. Insight Engines Market, Sub Segment Analysis
6.4.1. On-premises
6.4.2. Cloud
Chapter 7. Global Insight Engines Market, by Size of the Enterprise
7.1. Market Snapshot
7.2. Global Insight Engines Market by Size of the Enterprise, Performance – Potential Analysis
7.3. Global Insight Engines Market Estimates & Forecasts by Size of the Enterprise 2020-2030 (USD Million)
7.4. Insight Engines Market, Sub Segment Analysis
7.4.1. Small and Medium-Sized Enterprises
7.4.2. Large Enterprises
Chapter 8. Global Insight Engines Market, by End-user Industry
8.1. Market Snapshot
8.2. Global Insight Engines Market by End-user Industry, Performance – Potential Analysis
8.3. Global Insight Engines Market Estimates & Forecasts by End-user Industry 2020-2030 (USD Million)
8.4. Insight Engines Market, Sub Segment Analysis
8.4.1. BFSI
8.4.2. Retail
8.4.3. IT and Telecom
Chapter 9. Global Insight Engines Market, Regional Analysis
9.1. Top Leading Countries
9.2. Top Emerging Countries
9.3. Insight Engines Market, Regional Market Snapshot
9.4. North America Insight Engines Market
9.4.1. U.S. Insight Engines Market Component breakdown estimates & forecasts, 2020-2030 Deployment Type breakdown estimates & forecasts, 2020-2030 Size of the Enterprise breakdown estimates & forecasts, 2020-2030 End-user Industry breakdown estimates & forecasts, 2020-2030
9.4.2. Canada Insight Engines Market
9.5. Europe Insight Engines Market Snapshot
9.5.1. U.K. Insight Engines Market
9.5.2. Germany Insight Engines Market
9.5.3. France Insight Engines Market
9.5.4. Spain Insight Engines Market
9.5.5. Italy Insight Engines Market
9.5.6. Rest of Europe Insight Engines Market
9.6. Asia-Pacific Insight Engines Market Snapshot
9.6.1. China Insight Engines Market
9.6.2. India Insight Engines Market
9.6.3. Japan Insight Engines Market
9.6.4. Australia Insight Engines Market
9.6.5. South Korea Insight Engines Market
9.6.6. Rest of Asia Pacific Insight Engines Market
9.7. Latin America Insight Engines Market Snapshot
9.7.1. Brazil Insight Engines Market
9.7.2. Mexico Insight Engines Market
9.8. Middle East & Africa Insight Engines Market
9.8.1. Saudi Arabia Insight Engines Market
9.8.2. South Africa Insight Engines Market
9.8.3. Rest of Middle East & Africa Insight Engines Market

Chapter 10. Competitive Intelligence
10.1. Key Company SWOT Analysis
10.1.1. Company 1
10.1.2. Company 2
10.1.3. Company 3
10.2. Top Market Strategies
10.3. Company Profiles
10.3.1. Elastic NV Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
10.3.2. Attivio
10.3.3. Coveo Solutions Inc.
10.3.4. Sinequa
10.3.5. IBM Corporation
10.3.6. Lucidworks
10.3.7. Dassault Systèmes
10.3.8. Mindbreeze GmbH
10.3.9. Squirro
10.3.10. Smartlogic Semantic AI
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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