Growth Factors of Competitive Intelligence Tools Market
The global competitive intelligence tools market size was valued at USD 37.6 million in 2019 and is projected tgrow from USD 82.0 million in 2027 tUSD 121.37 million by 2031, exhibiting a CAGR of 10.3% during the forecast period of 2020-2027.
The pandemic significantly impacted the Competitive Intelligence Tools Market via using an elevated reliance on virtual tools as organizations tailored tfaraway paintings and unexpectedly changing market conditions. Organizations prioritized competitive evaluation tnavigate uncertainties, fostering demand for these tools tdisplay competitor strategies, marketplace trends, and customer behavior in real-time, impeding the competitive intelligence tools market growth.
The Competitive Intelligence Tools Market is driven by the desire for groups tstay ahead in dynamic markets, improvements in AI and records analytics, and the growing adoption of digital equipment for real-time insights intcompetitor techniques, purchaser behavior, and marketplace traits.
The Competitive Intelligence (CI) Tools market is experiencing a huge boom, driven by the growing need for companies tbenefit from the more profound expertise of their aggressive panorama, leading tthe expansion of the competitive intelligence tools market share globally. Key trends include the integration of Artificial Intelligence (AI) and Machine Learning (ML) for information evaluation and insights technology, the upward thrust of cloud-based total CI platforms for greater accessibility and collaboration, and a developing focus on statistics protection and privacy inside CI gear.
Comprehensive Analysis of Competitive Intelligence Tools Market
The Competitive Intelligence Tools Market is segmented by kind and alertness. By type, the market includes on-premises and cloud-based tools, with cloud-based answers gaining traction because of their price effectiveness and scalability—providers like Cipher Systems LLC and Crayon, Inc. We are using adoption through subscription-primarily based and SaaS offerings, while on-premises gear remains popular for steady facts management. By application, the marketplace spans industries such as BFSI, IT & telecom, automobile, retail, healthcare, strength, commercial, schooling, and others. The commercial area leads leveraging CI gear tenhance production intelligence while the education segment is growing unexpectedly due tthe expanded adoption of online studying platforms and company eLearning answers.
The North America region led the competitive intelligence tools market by benefitting a size of USD 16.4 million in 2019 due tthe increasing demand for records analytics gear and answers; adopting those intelligence gear is expected tincrease the thrust throughout areas.
The leading players in the competitive intelligence tools market significantly shape its growth trajectory and set industry standards. These key companies, including Alphabet Inc. (Google LLC) (California, United States), Crunchbase (California, United States), SEMrush (Massachusetts, United States), Owler (California, United States), Alexa Internet, Inc. (California, United States), Comintelli (Stockholm, Sweden), Talkwalker (Luxembourg), SpyFu (Arizona, United States), Crayon (Massachusetts, United States), NetBase Quid (California, United States), Slintel Inc. (California, United States), Consensus Point (Tennessee, United States), Evalueserve (Schaffhausen, Switzerland), SimilarWeb (New York, United States), Digimind (New York, United States), Klue Labs (Vancouver, Canada), CI Radar (Georgia, United States), Brandwatch (Brighton, United Kingdom), Contify, Inc. (New Delhi, India), and ArchIntel (Virginia, United States), contribute ta competitive landscape that drives innovation and advances the market.
In May 2022, SimilarWeb enhanced its portfoliby obtaining Rank Ranger, a bendy rank-tracking and analysis platform that gives vast analytics and seservices, which includes strong multi-channel organic seek functionalities.
Segmentation Table
ATTRIBUTE DETAILS
Study Period 2016-2027
Base Year 2019
Forecast Period 2020-2027
Historical Period 2018
Unit Value (USD million)
Segmentation Type; Application; and Geography
By Type
On Premise
Cloud-Based
By Application
BFSI
IT & Telecom
Automotive
Retail
Health Care
Energy
Industrial
Education
By Region
North America (By Type; Application; and Country)
United States (By Application)
Canada (By Application)
Mexic(By Application)
South America (By Type; Application; and Country)
Brazil (By Application)
Argentina (By Application)
Rest of South America
Europe (By Type; Application; and Country)
Germany (By Application)
United Kingdom (By Application)
France (By Application)
Italy (By Application)
Rest of Europe
The Middle East & Africa (By Type; Application; and Country)
Turkey (By Application)
Israel (By Application)
GCC (By Application)
North Africa (By Application)
South Africa (By Application)
Rest of the Middle East & Africa
Asia Pacific (By Type; Application; and Country)
China (By Application)
Japan (By Application)
India (By Application)
South Korea (By Application)
ASEAN (By Application)
Oceania (By Application)
- 1. Introduction
- 1.1. Definition, By Segment
- 1.2. Research Methodology/Approach
- 1.3. Data Sources
- 2. Key Takeaways
- 3. Market Dynamics
- 3.1. Macro and Micro Economic Indicators
- 3.2. Drivers, Restraints, Opportunities and Trends
- 3.3. Impact of COVID-19
- 3.3.1. Short-term Impact
- 3.3.2. Long-term Impact
- 4. Competition Landscape
- 4.1. Business Strategies Adopted by Key Players
- 4.2. Consolidated SWOT Analysis of Key Players
- 4.3. PESTLE Analysis
- 4.4. Porter’s Five Force Analysis
- 4.5. Supply chain Analysis
- 5. Global Competitive Intelligence Tool Key Players Market Share Insights and Analysis, 2019
- 6. Key Market Insights and Strategic Recommendations
- 7. Primary Interviewee’s Key Responses
- 8. Companies Profiled (Covered for key 10 players only)
- 8.1. Overview
- 8.1.1. Key Management
- 8.1.2. Headquarters etc.
- 8.2. Offerings/Business Segments
- 8.3. Key Details (Key details are subjected to data availability in public domain and/or on paid databases)
- 8.3.1. Employee Size
- 8.3.2. Key Financials
- 8.3.2.1. Past and Current Revenue
- 8.3.2.2. Gross Margin
- 8.3.2.3. Geographical Share
- 8.3.2.4. Business Segment Share
- 8.4. Recent Developments
- 9. Annexure/Appendix
- 9.1. Global Competitive Intelligence Tools Market Size Estimates and Forecasts (Quantitative Data), By Segments, 2016-2027
- 9.1.1. By Type (Value)
- 9.1.1.1. On Premise
- 9.1.1.2. Cloud-Based
- 9.1.2. By Application (Value)
- 9.1.2.1. BFSI
- 9.1.2.2. IT & Telecom
- 9.1.2.3. Automotive
- 9.1.2.4. Retail
- 9.1.2.5. Health Care
- 9.1.2.6. Energy
- 9.1.2.7. Industrial
- 9.1.2.8. Education
- 9.1.3. By Region (Value)
- 9.1.3.1. North America
- 9.1.3.2. Europe
- 9.1.3.3. Asia Pacific
- 9.1.3.4. Middle East & Africa
- 9.1.3.5. South America
- 9.2. North America Competitive Intelligence Tools Market Size Estimates and Forecasts (Quantitative Data), By Segments, 2016-2027
- 9.2.1. By Type (Value)
- 9.2.1.1. On Premise
- 9.2.1.2. Cloud-Based
- 9.2.2. By Application (Value)
- 9.2.2.1. BFSI
- 9.2.2.2. IT & Telecom
- 9.2.2.3. Automotive
- 9.2.2.4. Retail
- 9.2.2.5. Health Care
- 9.2.2.6. Energy
- 9.2.2.7. Industrial
- 9.2.2.8. Education
- 9.2.3. By Country (Value)
- 9.2.3.1. US
- 9.2.3.1.1. By Application (Value)
- 9.2.3.1.1.1. BFSI
- 9.2.3.1.1.2. IT & Telecom
- 9.2.3.1.1.3. Automotive
- 9.2.3.1.1.4. Retail
- 9.2.3.1.1.5. Health Care
- 9.2.3.1.1.6. Energy
- 9.2.3.1.1.7. Industrial
- 9.2.3.1.1.8. Education
- 9.2.3.2. Canada
- 9.2.3.2.1. By Application (Value)
- 9.2.3.2.1.1. BFSI
- 9.2.3.2.1.2. IT & Telecom
- 9.2.3.2.1.3. Automotive
- 9.2.3.2.1.4. Retail
- 9.2.3.2.1.5. Health Care
- 9.2.3.2.1.6. Energy
- 9.2.3.2.1.7. Industrial
- 9.2.3.2.1.8. Education
- 9.2.3.3. Mexico
- 9.2.3.3.1. By Application (Value)
- 9.2.3.3.1.1. BFSI
- 9.2.3.3.1.2. IT & Telecom
- 9.2.3.3.1.3. Automotive
- 9.2.3.3.1.4. Retail
- 9.2.3.3.1.5. Health Care
- 9.2.3.3.1.6. Energy
- 9.2.3.3.1.7. Industrial
- 9.2.3.3.1.8. Education
- 9.3. Europe Competitive Intelligence Tools Market Size Estimates and Forecasts (Quantitative Data), By Segments, 2016-2027
- 9.3.1. By Type (Value)
- 9.3.1.1. On Premise
- 9.3.1.2. Cloud-Based
- 9.3.2. By Application (Value)
- 9.3.2.1. BFSI
- 9.3.2.2. IT & Telecom
- 9.3.2.3. Automotive
- 9.3.2.4. Retail
- 9.3.2.5. Health Care
- 9.3.2.6. Energy
- 9.3.2.7. Industrial
- 9.3.2.8. Education
- 9.3.3. By Country (Value)
- 9.3.3.1. Germany
- 9.3.3.1.1. By Application (Value)
- 9.3.3.1.1.1. BFSI
- 9.3.3.1.1.2. IT & Telecom
- 9.3.3.1.1.3. Automotive
- 9.3.3.1.1.4. Retail
- 9.3.3.1.1.5. Health Care
- 9.3.3.1.1.6. Energy
- 9.3.3.1.1.7. Industrial
- 9.3.3.1.1.8. Education
- 9.3.3.2. United Kingdom
- 9.3.3.2.1. By Application (Value)
- 9.3.3.2.1.1. BFSI
- 9.3.3.2.1.2. IT & Telecom
- 9.3.3.2.1.3. Automotive
- 9.3.3.2.1.4. Retail
- 9.3.3.2.1.5. Health Care
- 9.3.3.2.1.6. Energy
- 9.3.3.2.1.7. Industrial
- 9.3.3.2.1.8. Education
- 9.3.3.3. France
- 9.3.3.3.1. By Application (Value)
- 9.3.3.3.1.1. BFSI
- 9.3.3.3.1.2. IT & Telecom
- 9.3.3.3.1.3. Automotive
- 9.3.3.3.1.4. Retail
- 9.3.3.3.1.5. Health Care
- 9.3.3.3.1.6. Energy
- 9.3.3.3.1.7. Industrial
- 9.3.3.3.1.8. Education
- 9.3.3.4. Italy
- 9.3.3.4.1. By Application (Value)
- 9.3.3.4.1.1. BFSI
- 9.3.3.4.1.2. IT & Telecom
- 9.3.3.4.1.3. Automotive
- 9.3.3.4.1.4. Retail
- 9.3.3.4.1.5. Health Care
- 9.3.3.4.1.6. Energy
- 9.3.3.4.1.7. Industrial
- 9.3.3.4.1.8. Education
- 9.3.3.5. Rest of Europe
- 9.4. Asia Pacific Competitive Intelligence Tools Market Size Estimates and Forecasts (Quantitative Data), By Segments, 2016-2027
- 9.4.1. By Type (Value)
- 9.4.1.1. On Premise
- 9.4.1.2. Cloud-Based
- 9.4.2. By Application (Value)
- 9.4.2.1. BFSI
- 9.4.2.2. IT & Telecom
- 9.4.2.3. Automotive
- 9.4.2.4. Retail
- 9.4.2.5. Health Care
- 9.4.2.6. Energy
- 9.4.2.7. Industrial
- 9.4.2.8. Education
- 9.4.3. By Country (Value)
- 9.4.3.1. China
- 9.4.3.1.1. By Application (Value)
- 9.4.3.1.1.1. BFSI
- 9.4.3.1.1.2. IT & Telecom
- 9.4.3.1.1.3. Automotive
- 9.4.3.1.1.4. Retail
- 9.4.3.1.1.5. Health Care
- 9.4.3.1.1.6. Energy
- 9.4.3.1.1.7. Industrial
- 9.4.3.1.1.8. Education
- 9.4.3.2. India
- 9.4.3.2.1. By Application (Value)
- 9.4.3.2.1.1. BFSI
- 9.4.3.2.1.2. IT & Telecom
- 9.4.3.2.1.3. Automotive
- 9.4.3.2.1.4. Retail
- 9.4.3.2.1.5. Health Care
- 9.4.3.2.1.6. Energy
- 9.4.3.2.1.7. Industrial
- 9.4.3.2.1.8. Education
- 9.4.3.3. Japan
- 9.4.3.3.1. By Application (Value)
- 9.4.3.3.1.1. BFSI
- 9.4.3.3.1.2. IT & Telecom
- 9.4.3.3.1.3. Automotive
- 9.4.3.3.1.4. Retail
- 9.4.3.3.1.5. Health Care
- 9.4.3.3.1.6. Energy
- 9.4.3.3.1.7. Industrial
- 9.4.3.3.1.8. Education
- 9.4.3.4. South Korea
- 9.4.3.4.1. By Application (Value)
- 9.4.3.4.1.1. BFSI
- 9.4.3.4.1.2. IT & Telecom
- 9.4.3.4.1.3. Automotive
- 9.4.3.4.1.4. Retail
- 9.4.3.4.1.5. Health Care
- 9.4.3.4.1.6. Energy
- 9.4.3.4.1.7. Industrial
- 9.4.3.4.1.8. Education
- 9.4.3.5. ASEAN
- 9.4.3.5.1. By Application (Value)
- 9.4.3.5.1.1. BFSI
- 9.4.3.5.1.2. IT & Telecom
- 9.4.3.5.1.3. Automotive
- 9.4.3.5.1.4. Retail
- 9.4.3.5.1.5. Health Care
- 9.4.3.5.1.6. Energy
- 9.4.3.5.1.7. Industrial
- 9.4.3.5.1.8. Education
- 9.4.3.6. Oceania
- 9.4.3.6.1. By Application (Value)
- 9.4.3.6.1.1. BFSI
- 9.4.3.6.1.2. IT & Telecom
- 9.4.3.6.1.3. Automotive
- 9.4.3.6.1.4. Retail
- 9.4.3.6.1.5. Health Care
- 9.4.3.6.1.6. Energy
- 9.4.3.6.1.7. Industrial
- 9.4.3.6.1.8. Education
- 9.4.3.7. Rest of Asia Pacific
- 9.5. Middle East & Africa Competitive Intelligence Tools Market Size Estimates and Forecasts (Quantitative Data), By Segments, 2016-2027
- 9.5.1. By Type (Value)
- 9.5.1.1. On Premise
- 9.5.1.2. Cloud-Based
- 9.5.2. By Application (Value)
- 9.5.2.1. BFSI
- 9.5.2.2. IT & Telecom
- 9.5.2.3. Automotive
- 9.5.2.4. Retail
- 9.5.2.5. Health Care
- 9.5.2.6. Energy
- 9.5.2.7. Industrial
- 9.5.2.8. Education
- 9.5.3. By Country (Value)
- 9.5.3.1. Turkey
- 9.5.3.1.1. By Application (Value)
- 9.5.3.1.1.1. BFSI
- 9.5.3.1.1.2. IT & Telecom
- 9.5.3.1.1.3. Automotive
- 9.5.3.1.1.4. Retail
- 9.5.3.1.1.5. Health Care
- 9.5.3.1.1.6. Energy
- 9.5.3.1.1.7. Industrial
- 9.5.3.1.1.8. Education
- 9.5.3.2. Israel
- 9.5.3.2.1. By Application (Value)
- 9.5.3.2.1.1. BFSI
- 9.5.3.2.1.2. IT & Telecom
- 9.5.3.2.1.3. Automotive
- 9.5.3.2.1.4. Retail
- 9.5.3.2.1.5. Health Care
- 9.5.3.2.1.6. Energy
- 9.5.3.2.1.7. Industrial
- 9.5.3.2.1.8. Education
- 9.5.3.3. GCC
- 9.5.3.3.1. By Application (Value)
- 9.5.3.3.1.1. BFSI
- 9.5.3.3.1.2. IT & Telecom
- 9.5.3.3.1.3. Automotive
- 9.5.3.3.1.4. Retail
- 9.5.3.3.1.5. Health Care
- 9.5.3.3.1.6. Energy
- 9.5.3.3.1.7. Industrial
- 9.5.3.3.1.8. Education
- 9.5.3.4. North Africa
- 9.5.3.4.1. By Application (Value)
- 9.5.3.4.1.1. BFSI
- 9.5.3.4.1.2. IT & Telecom
- 9.5.3.4.1.3. Automotive
- 9.5.3.4.1.4. Retail
- 9.5.3.4.1.5. Health Care
- 9.5.3.4.1.6. Energy
- 9.5.3.4.1.7. Industrial
- 9.5.3.4.1.8. Education
- 9.5.3.5. South Africa
- 9.5.3.5.1. By Application (Value)
- 9.5.3.5.1.1. BFSI
- 9.5.3.5.1.2. IT & Telecom
- 9.5.3.5.1.3. Automotive
- 9.5.3.5.1.4. Retail
- 9.5.3.5.1.5. Health Care
- 9.5.3.5.1.6. Energy
- 9.5.3.5.1.7. Industrial
- 9.5.3.5.1.8. Education
- 9.5.3.6. Rest of Middle East & Africa
- 9.6. South America Competitive Intelligence Tools Market Size Estimates and Forecasts (Quantitative Data), By Segments, 2016-2027
- 9.6.1. By Type (Value)
- 9.6.1.1. On Premise
- 9.6.1.2. Cloud-Based
- 9.6.2. By Application (Value)
- 9.6.2.1. BFSI
- 9.6.2.2. IT & Telecom
- 9.6.2.3. Automotive
- 9.6.2.4. Retail
- 9.6.2.5. Health Care
- 9.6.2.6. Energy
- 9.6.2.7. Industrial
- 9.6.2.8. Education
- 9.6.3. By Country (Value)
- 9.6.4. Brazil
- 9.6.4.1.
- 9.6.4.1.1. By Application (Value)
- 9.6.4.1.1.1. BFSI
- 9.6.4.1.1.2. IT & Telecom
- 9.6.4.1.1.3. Automotive
- 9.6.4.1.1.4. Retail
- 9.6.4.1.1.5. Health Care
- 9.6.4.1.1.6. Energy
- 9.6.4.1.1.7. Industrial
- 9.6.4.1.1.8. Education
- 9.6.5. Argentina
- 9.6.5.1.
- 9.6.5.1.1. By Application (Value)
- 9.6.5.1.1.1. BFSI
- 9.6.5.1.1.2. IT & Telecom
- 9.6.5.1.1.3. Automotive
- 9.6.5.1.1.4. Retail
- 9.6.5.1.1.5. Health Care
- 9.6.5.1.1.6. Energy
- 9.6.5.1.1.7. Industrial
- 9.6.5.1.1.8. Education
- 9.6.6. Rest of South America
- 10. Companies Analyzed (In order to estimate the market size and/or understanding the market ecosystem) (Note that the purpose of the below list is to highlight the exhaustiveness of coverage. Only top 10 players are profiled in the scope. Additionally, we are open to profile additional company(s) on specific request)
- 10.1. Alphabet Inc. (Google LLC)
- 10.2. Crunchbase
- 10.3. SEMrush
- 10.4. Owler
- 10.5. Talkwalker
- 10.6. Slintel Inc.
- 10.7. Evalueserve
- 10.8. Klue Labs
- 10.9. Crayon
- 10.10. Brandwatch
- 10.11. SimilarWeb LTD
- 10.12. Alexa Internet, Inc.
- 10.13. Fornova
- 10.14. Contify, Inc.
- 10.15. Digimind
- 10.16. SpyFu
- 10.17. kompyte.com
- 10.18. CI Radar
- 10.19. App Annie
- 10.20. Consensus Point
- 10.21. NetBase Quid
- 10.22. Ceralytics
- 10.23. CompeteIQ
- 10.24. Nichefire, Inc.
- 10.25. Arbit. Inc.
- 10.26. Ahrefs Pte. Ltd.
- 10.27. ArchIntel
- 10.28. Comintelli
- 10.29. SEMrush "
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