The global insight engines market size was estimated at around USD 1.49 billion in 2022 and it is projected to hit around USD 15.67 billion by 2032, growing at a CAGR of 26.53% from 2023 to 2032. The insight engines market in the United States was accounted for USD 291 million in 2022.
Key Pointers
Report Scope of the Insight Engines Market
Report Coverage | Details |
Revenue Share of North America in 2022 | 46% |
Revenue Forecast by 2032 | USD 15.67 billion |
Growth Rate from 2023 to 2032 | CAGR of 26.53% |
Base Year | 2022 |
Forecast Period | 2023 to 2032 |
Market Analysis (Terms Used) | Value (US$ Million/Billion) or (Volume/Units) |
Companies Covered | Attivio; Coveo; Elasticsearch B.V.; Expert.AI; Google; International Business Machines Incorporation; Mindbreeze GmbH; Open Text Corporation; Sinequa; Squirro AG |
An insight engine, also known as enterprise cognitive search or knowledge discovery, is an enterprise platform that makes critical enterprise insights accessible to users when required. It integrates search with machine learning capabilities to deliver data for machines and information for users. An insight engine aims to deliver timely data that offers actionable insights. The rapid adoption of the consumer goods and retail industry and the growing adoption of digital technologies drive the growth of the insight engines market. For instance, in August 2022, Renewable Energy Systems Ltd., a renewable energy company, adopted Aiimi’s AI-powered platform, “Aiimi insight engines.” The platform will generate 5.7 terabytes of historical data that is efficiently discoverable and migrate the information to an Azure-hosted archive. Adopting the platform would let Renewable Energy Systems Ltd. a digital transformation and undergo a large-scale cloud migration to Azure.
Insights engines allow organizations to generate insights automatically from the available databases using advanced data analytics such as machine learning and artificial intelligence. Data-driven decision-making is increasingly popular among businesses and managers, and insights engines allow them to base their decisions on insights extracted from data. Insight engines apply methods to discover, describe, analyze, and organize data. This allows synthesized or existing information to be delivered interactively or proactively to customers, digital workers, or constituents, in context and at timely business moments.
Insight engines accelerate business growth by delivering ultimate value through customer-tailored personalization. Big data, artificial intelligence, and machine learning-enabled insight engines serve as strategic business resources that assist organizations in providing customers with one-of-a-kind digital experiences. By integrating such technologies, insight engines become the next big thing since they offer customized experiences that perform better than traditional digital asset management systems. Through intelligent relationship building, insight engines assist businesses in improving their relationships with customers. It combines high-quality technologies such as Natural Language Processing (NLP) and Natural Language Question Answering (NLQA) to provide clients with a sense of comfortable human connection that produces satisfying results. Additionally, insight engines can create business predictions and scenario developments with machine learning and deep learning to address various business issues.
The technology learns the relevance of the individual pieces of data by continuously analyzing various work methods, such as how frequently or in what context certain information is pulled up. It then prepares the data for the particular application case, the department, and the user and differentiates the facts accordingly to provide information in a personalized and proactive way. For instance, insight engines solutions allow the user to get a 360-degree view of all business-relevant data within the organization in response to a query. This comprehensive overview of suppliers, customers, expertise, and responsibilities is pivotal for success in the face of increasingly harsh competition.
Component Insights
The software segment led the market in 2022, accounting for over 74% share of the global revenue. The high share can be attributed to the increasing investments of companies in insight engines software. Further, the increasing volume and complexity of data, the need for faster and more accurate insights, and advancements in artificial intelligence and machine learning technologies drive software growth in the insight engines market. For instance, in October 2021, Aiimi, an insight engines provider, announced its partnership with Metia, a marketing agency with a strong focus on digital transformation, data-driven insights, and customer engagement. The partnership aims to leverage Metia’s expertise in data analytics and developing and scaling digital marketplaces, which will help grow their insight engines marketplace.
The services segment is predicted to foresee significant growth in the forecast years. Insight engine services comprise training, support, deployment, and integration of the insight engines. These vendor-provided services are offered as standalone offerings and product add-ons. Usually, vendors charge a fee for any services they offer besides the software subscription. Insight engine suppliers are collaborating with companies that provide these services to customers on their behalf. Various partnerships are also growing in the market, so it is anticipated that the rising demand for consulting, supporting, and other services will fuel the growth of the services segment, which is expected to rise.
Deployment Insights
The on-premises segment held the largest revenue share of over 59% in 2022. During on-premises deployment, the solution is set up on business servers protected by a firewall, the software is licensed, and the entire instance is housed on-site at an organization; as a business uses on-premises software, it has purchased a license or copy of the program. Hence, there is better protection than with a cloud computing infrastructure. Moreover, on-premises solutions offer more flexibility in terms of customization and integration with existing systems. Organizations can tailor the solution to their specific needs and integrate it with their existing infrastructure, which can be complex with cloud-based solutions.
The cloud segment will witness significant growth in the coming years. With the rise in popularity of cloud computing comes a new form of flexibility for businesses, from time and money savings to increased agility and scalability. When it comes to business technology, several software programs have migrated to the cloud for the most advanced features. Moving to the cloud also provided providers with cost and elasticity benefits to grow their operations. The rush for cloud computing ignores essential information, including that not all businesses are ready for cloud installations and willing to move to a cloud-only strategy. Implementations of the public and private clouds are numerous, and each is customized to a particular organization's needs and operating environment.
Enterprise Size Insights
The large enterprises' segment dominated the market in 2022 and accounted for a revenue share of over 73%. The growth is attributed to improved data access and discovery, enhanced data analysis and visualization, improved customer engagement and satisfaction, reduced operational costs, and improved efficiency. Many large enterprises are investing in insight engines as they have increased their demand for advanced solutions and information intelligence. Companies also develop new products and launch new solutions to meet this demand. Moreover, these enterprises generate massive amounts of data daily, which needs to be analyzed quickly and efficiently. Insight engines thus help enterprises to quickly search, analyze, and process data from various sources, reducing the time it takes to make decisions and take action.
The small and medium enterprises segment is anticipated to witness significant growth in the coming years. There are numerous small and medium-sized businesses in nearly every country. SMEs prefer the more affordable option due to their limited financial resources. Some firms might require assistance to buy these solutions due to limited IT investments. Despite SMEs' limited financial resources, the market is expected to expand due to the solutions' rising scalability, widespread accessibility, and cloud-based deployments.
Vertical Insights
The IT and telecom segment led the market in 2022, accounting for over 18% of global revenue. The high share can be attributed to the large volumes of structured and unstructured data from various sources such as customer interactions, social media, and enterprise applications they deal with.For instance, insight engines can be used to analyze customer support tickets and provide faster and more accurate resolutions, or to monitor IT systems and detect anomalies and performance issues before they become critical. Moreover, IT and ITes companies are also using insight engines to improve their internal search capabilities, allowing employees to quickly find the information they need within large and complex enterprise systems. This can help increase productivity, reduce errors, and improve collaboration among teams.
The retail and e-commerce segment is expected to show significant growth over the forecast period. The segment's rise can be attributable to the increasing adoption of digital technologies in the retail and e-commerce sectors that is expected to drive the insight engines market. Due to the growing usage of artificial intelligence to gather information, capture and collect existing knowledge, and find relationships between the data, the insight engines industry in the retail sector offers attractive potential. Moreover, by using insight engines, retailers can gain a deeper understanding of their customers and their needs, which can help them make more informed decisions about product offerings, marketing strategies, and operational improvements.
Application Insights
The customer experience management segment led the market in 2022, accounting for over 29% of the global revenue. The high share can be attributed to the significant role played by insight engines in improving customer experience management by helping organizations better understand their customers' needs and preferences. Insight engines implement artificial intelligence techniques such as machine and deep learning. These methods can find and search correlations between unstructured and structured data within corporations, regardless of size or type of organization. In addition, insight engines can help organizations to identify trends and patterns in customer behavior that may not be immediately apparent, allowing them to address potential issues before they escalate proactively. By providing real-time insights, insight engines can help organizations to be more agile and responsive to customer needs.
The risk and compliance management segment is expected to show significant growth over the forecast period. The segment's rise can be attributable to businesses facing increasingly complex regulatory requirements and cybersecurity threats. Many businesses are turning to insight engines to help them better understand and manage their risks and ensure compliance with applicable regulations. Moreover, insight engines assist organizations in identifying potential risks and compliance issues by analyzing large volumes of data from various sources, including structured and unstructured data, social media, and even video and audio content. These insights can be used to proactively identify and mitigate risks and respond quickly to any compliance issues that arise.
Regional Insights
North America dominated the market in 2022, accounting for over 46% share of the global revenue. Developed countries such as Canada and the U.S. drive the market's growth. The North American region has widely adopted insight engines technology and generates the highest revenue there. Due to its massive adoption of cutting-edge technology, such as chatbots, speech recognition, and natural language processing, North America has the largest share. The market for insight engines in the region is expanding due to several factors, such as the development of the internet of things (IoT), which is expanding rapidly, and the lower cost of ownership of cloud-based platforms. Additionally, many business sectors, including IT, telecom, healthcare, media, and entertainment, are taking advantage of insights engine capabilities to respond quickly to consumer inquiries due to the widespread adoption of these platforms across the region.
Asia Pacific is likely to possess lucrative market opportunities in the coming years. The leading players in the APAC insight engines market focus on growing their investments, product portfolios, analytic solutions, and strategic partnerships to create robust and easy functionality. China is a powerful country in the Asia Pacific region with rising technological usage. This country has one of the world's fastest Internet speeds and is home to major businesses such as Alibaba. The restrictive regulatory framework in China, which prohibits international companies such as FAANG (Facebook, Amazon, Apple, Netflix, and Google) from functioning there, strengthens the tripartite domination (iQiyi, Tencent, and Youku). These multinational players primarily leverage insight engines for general recommendations and advertising that promotes their businesses. The region has grown moderately due to the number of domestic opportunities. Additionally, as many new local companies strive to enter emerging markets in countries like India, they are projected to offer significant opportunities for the market during the forecast period.
Insight Engines Market Segmentations:
By Component
By Deployment
By Enterprise Size
By Application
By Vertical
By Regional
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on Insight Engines Market
5.1. COVID-19 Landscape: Insight Engines Industry Impact
5.2. COVID 19 - Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global Insight Engines Market, By Component
8.1. Insight Engines Market, by Component, 2023-2032
8.1.1. Software
8.1.1.1. Market Revenue and Forecast (2020-2032)
8.1.2. Services
8.1.2.1. Market Revenue and Forecast (2020-2032)
Chapter 9. Global Insight Engines Market, By Deployment
9.1. Insight Engines Market, by Deployment, 2023-2032
9.1.1. Cloud
9.1.1.1. Market Revenue and Forecast (2020-2032)
9.1.2. On-premises
9.1.2.1. Market Revenue and Forecast (2020-2032)
Chapter 10. Global Insight Engines Market, By Enterprise Size
10.1. Insight Engines Market, by Enterprise Size, 2023-2032
10.1.1. Small & Medium Enterprises
10.1.1.1. Market Revenue and Forecast (2020-2032)
10.1.2. Large Enterprises
10.1.2.1. Market Revenue and Forecast (2020-2032)
Chapter 11. Global Insight Engines Market, By Application
11.1. Insight Engines Market, by Application, 2023-2032
11.1.1. Workforce Management
11.1.1.1. Market Revenue and Forecast (2020-2032)
11.1.2. Customer Experience Management
11.1.2.1. Market Revenue and Forecast (2020-2032)
11.1.3. Sales & Marketing Management
11.1.3.1. Market Revenue and Forecast (2020-2032)
11.1.4. Risk & Compliance Management
11.1.4.1. Market Revenue and Forecast (2020-2032)
11.1.5. Others
11.1.5.1. Market Revenue and Forecast (2020-2032)
Chapter 12. Global Insight Engines Market, By Vertical
12.1. Insight Engines Market, by Vertical, 2023-2032
12.1.1. BFSI
12.1.1.1. Market Revenue and Forecast (2020-2032)
12.1.2. IT & Telecom
12.1.2.1. Market Revenue and Forecast (2020-2032)
12.1.3. Retail & Ecommerce
12.1.3.1. Market Revenue and Forecast (2020-2032)
12.1.4. Healthcare
12.1.4.1. Market Revenue and Forecast (2020-2032)
12.1.5. Manufacturing
12.1.5.1. Market Revenue and Forecast (2020-2032)
12.1.6. Government
12.1.6.1. Market Revenue and Forecast (2020-2032)
12.1.7. Others
12.1.7.1. Market Revenue and Forecast (2020-2032)
Chapter 13. Global Insight Engines Market, Regional Estimates and Trend Forecast
13.1. North America
13.1.1. Market Revenue and Forecast, by Component (2020-2032)
13.1.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.1.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.1.4. Market Revenue and Forecast, by Application (2020-2032)
13.1.5. Market Revenue and Forecast, by Vertical (2020-2032)
13.1.6. U.S.
13.1.6.1. Market Revenue and Forecast, by Component (2020-2032)
13.1.6.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.1.6.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.1.6.4. Market Revenue and Forecast, by Application (2020-2032)
13.1.7. Market Revenue and Forecast, by Vertical (2020-2032)
13.1.8. Rest of North America
13.1.8.1. Market Revenue and Forecast, by Component (2020-2032)
13.1.8.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.1.8.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.1.8.4. Market Revenue and Forecast, by Application (2020-2032)
13.1.8.5. Market Revenue and Forecast, by Vertical (2020-2032)
13.2. Europe
13.2.1. Market Revenue and Forecast, by Component (2020-2032)
13.2.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.2.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.2.4. Market Revenue and Forecast, by Application (2020-2032)
13.2.5. Market Revenue and Forecast, by Vertical (2020-2032)
13.2.6. UK
13.2.6.1. Market Revenue and Forecast, by Component (2020-2032)
13.2.6.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.2.6.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.2.7. Market Revenue and Forecast, by Application (2020-2032)
13.2.8. Market Revenue and Forecast, by Vertical (2020-2032)
13.2.9. Germany
13.2.9.1. Market Revenue and Forecast, by Component (2020-2032)
13.2.9.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.2.9.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.2.10. Market Revenue and Forecast, by Application (2020-2032)
13.2.11. Market Revenue and Forecast, by Vertical (2020-2032)
13.2.12. France
13.2.12.1. Market Revenue and Forecast, by Component (2020-2032)
13.2.12.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.2.12.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.2.12.4. Market Revenue and Forecast, by Application (2020-2032)
13.2.13. Market Revenue and Forecast, by Vertical (2020-2032)
13.2.14. Rest of Europe
13.2.14.1. Market Revenue and Forecast, by Component (2020-2032)
13.2.14.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.2.14.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.2.14.4. Market Revenue and Forecast, by Application (2020-2032)
13.2.15. Market Revenue and Forecast, by Vertical (2020-2032)
13.3. APAC
13.3.1. Market Revenue and Forecast, by Component (2020-2032)
13.3.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.3.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.3.4. Market Revenue and Forecast, by Application (2020-2032)
13.3.5. Market Revenue and Forecast, by Vertical (2020-2032)
13.3.6. India
13.3.6.1. Market Revenue and Forecast, by Component (2020-2032)
13.3.6.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.3.6.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.3.6.4. Market Revenue and Forecast, by Application (2020-2032)
13.3.7. Market Revenue and Forecast, by Vertical (2020-2032)
13.3.8. China
13.3.8.1. Market Revenue and Forecast, by Component (2020-2032)
13.3.8.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.3.8.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.3.8.4. Market Revenue and Forecast, by Application (2020-2032)
13.3.9. Market Revenue and Forecast, by Vertical (2020-2032)
13.3.10. Japan
13.3.10.1. Market Revenue and Forecast, by Component (2020-2032)
13.3.10.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.3.10.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.3.10.4. Market Revenue and Forecast, by Application (2020-2032)
13.3.10.5. Market Revenue and Forecast, by Vertical (2020-2032)
13.3.11. Rest of APAC
13.3.11.1. Market Revenue and Forecast, by Component (2020-2032)
13.3.11.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.3.11.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.3.11.4. Market Revenue and Forecast, by Application (2020-2032)
13.3.11.5. Market Revenue and Forecast, by Vertical (2020-2032)
13.4. MEA
13.4.1. Market Revenue and Forecast, by Component (2020-2032)
13.4.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.4.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.4.4. Market Revenue and Forecast, by Application (2020-2032)
13.4.5. Market Revenue and Forecast, by Vertical (2020-2032)
13.4.6. GCC
13.4.6.1. Market Revenue and Forecast, by Component (2020-2032)
13.4.6.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.4.6.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.4.6.4. Market Revenue and Forecast, by Application (2020-2032)
13.4.7. Market Revenue and Forecast, by Vertical (2020-2032)
13.4.8. North Africa
13.4.8.1. Market Revenue and Forecast, by Component (2020-2032)
13.4.8.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.4.8.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.4.8.4. Market Revenue and Forecast, by Application (2020-2032)
13.4.9. Market Revenue and Forecast, by Vertical (2020-2032)
13.4.10. South Africa
13.4.10.1. Market Revenue and Forecast, by Component (2020-2032)
13.4.10.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.4.10.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.4.10.4. Market Revenue and Forecast, by Application (2020-2032)
13.4.10.5. Market Revenue and Forecast, by Vertical (2020-2032)
13.4.11. Rest of MEA
13.4.11.1. Market Revenue and Forecast, by Component (2020-2032)
13.4.11.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.4.11.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.4.11.4. Market Revenue and Forecast, by Application (2020-2032)
13.4.11.5. Market Revenue and Forecast, by Vertical (2020-2032)
13.5. Latin America
13.5.1. Market Revenue and Forecast, by Component (2020-2032)
13.5.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.5.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.5.4. Market Revenue and Forecast, by Application (2020-2032)
13.5.5. Market Revenue and Forecast, by Vertical (2020-2032)
13.5.6. Brazil
13.5.6.1. Market Revenue and Forecast, by Component (2020-2032)
13.5.6.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.5.6.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.5.6.4. Market Revenue and Forecast, by Application (2020-2032)
13.5.7. Market Revenue and Forecast, by Vertical (2020-2032)
13.5.8. Rest of LATAM
13.5.8.1. Market Revenue and Forecast, by Component (2020-2032)
13.5.8.2. Market Revenue and Forecast, by Deployment (2020-2032)
13.5.8.3. Market Revenue and Forecast, by Enterprise Size (2020-2032)
13.5.8.4. Market Revenue and Forecast, by Application (2020-2032)
13.5.8.5. Market Revenue and Forecast, by Vertical (2020-2032)
Chapter 14. Company Profiles
14.1. Attivio
14.1.1. Company Overview
14.1.2. Product Offerings
14.1.3. Financial Performance
14.1.4. Recent Initiatives
14.2. Coveo
14.2.1. Company Overview
14.2.2. Product Offerings
14.2.3. Financial Performance
14.2.4. Recent Initiatives
14.3. Elasticsearch B.V
14.3.1. Company Overview
14.3.2. Product Offerings
14.3.3. Financial Performance
14.3.4. Recent Initiatives
14.4. Expert.AI
14.4.1. Company Overview
14.4.2. Product Offerings
14.4.3. Financial Performance
14.4.4. Recent Initiatives
14.5. Google
14.5.1. Company Overview
14.5.2. Product Offerings
14.5.3. Financial Performance
14.5.4. Recent Initiatives
14.6. International Business Machines Incorporation
14.6.1. Company Overview
14.6.2. Product Offerings
14.6.3. Financial Performance
14.6.4. Recent Initiatives
14.7. Mindbreeze GmbH
14.7.1. Company Overview
14.7.2. Product Offerings
14.7.3. Financial Performance
14.7.4. Recent Initiatives
14.8. Open Text Corporation
14.8.1. Company Overview
14.8.2. Product Offerings
14.8.3. Financial Performance
14.8.4. Recent Initiatives
14.9. Sinequa
14.9.1. Company Overview
14.9.2. Product Offerings
14.9.3. Financial Performance
14.9.4. Recent Initiatives
14.10. Squirro AG
14.10.1. Company Overview
14.10.2. Product Offerings
14.10.3. Financial Performance
14.10.4. Recent Initiatives
Chapter 15. Research Methodology
15.1. Primary Research
15.2. Secondary Research
15.3. Assumptions
Chapter 16. Appendix
16.1. About Us
16.2. Glossary of Terms