AI-Driven News Aggregation Market size was valued at USD 2.43 billion in 2024 and is expected to reach USD 8.84 billion by 2032, growing at a CAGR of 17.62% over 2025-2032.
The AI-Driven News Aggregation Market growth is primarily fueled by the rising demand for personalized, real-time, and bias-free news experiences. Increasing volumes of digital content and social media data have created a need for intelligent filtering and summarization tools.
AI systems, such as News360 process content from over 100,000 sources, clustering and ranking news for each user based on semantic and interest-graph analysis, ensuring high relevance. Advancements in natural language processing (NLP), machine learning, and sentiment analysis continue to enhance content accuracy and user engagement.
Institutions, such as the U.S. Department of Justice and the Copyright Office are actively researching the use of AI in detecting misinformation and improving content credibility.
Moreover, tools such as the Washington Post’s Heliograf leverage AI-driven A/B headline testing, achieving an 18% increase in click-through rates, showcasing how media organizations are optimizing content delivery. The surge in mobile and smart device usage also drives adoption across individual and enterprise users, further accelerating market expansion
U.S. AI-Driven News Aggregation Market size was valued at USD 0.68 billion in 2024 and is expected to reach USD 2.46 billion by 2032, growing at a CAGR of 17.38% over 2025-2032.
The U.S. AI-Driven News Aggregation Market is growing rapidly due to rising demand for real-time, personalized content, increased mobile usage, and advancements in AI technologies, such as NLP and sentiment analysis, enhancing news delivery, accuracy, and user engagement across platforms.
Drivers:
Rising Demand for Real-Time, Personalized News Experiences Among Digital Consumers Across Platforms Is Fueling Market Expansion Rapidly
The growth of the AI-Driven News Aggregation Market is primarily due to the high demand for personalized, on-demand, and non-biased news experiences. With the rising volumes of digital content and social media data, there are new needs for filter and summary tools that can help read minds intelligently.
In the U.S., 82% of adults consume news via digital devices, with 36% using mobile news apps daily. This surge supports growing demand for AI-driven tools, as NLP, machine learning, and sentiment analysis improve content relevance, personalization, and engagement.
Moreover, a Salesforce report indicates that global daily use of AI among desktop workers has surged by 233% in the last six months, with three in five now using AI tools daily demonstrating the growing reliance on AI technologies across sectors.
Notably, 67–75% of digital consumers report loyalty to the same news brands across platforms, rising to 75% among mobile users, reflecting the strong retention potential of well-personalized content.
Increase in use of mobile devices and AI adoption by media platforms for content delivery, reduction of misinformation, and improve user engagement and retention.
Restraints:
Concerns Over Misinformation Amplification and Algorithmic Bias Pose Ethical Risks to Market Adoption and Credibility
Aggregators that rely heavily on AI can spread misinformation by selecting content according to how likely it is to generate engagement, rather than how truthful it is. Biased or sensationalist content can result from flawed training data and poor editorial oversight. The black-box nature of these models means it is difficult to resolve attributions or evaluate credibility, which in turn erodes public trust particularly in politically charged situations. Regulatory scrutiny is growing, forcing platforms to do more to ensure fair and responsible outcomes. While there is not transparency and fact checking, there will remain ethical and legal impediments to mass adoption and investor faith in the marketplace.
A recent Wired report uncovered a pro‑Russia disinformation campaign (Operation Overload) that used readily available AI tools to produce 587 deceptive content pieces between September 2024 and May 2025 compared to 230 the previous year demonstrating how AI can rapidly amplify false narratives.
Opportunities:
Growing Integration of Voice Assistants and Smart Devices for News Consumption Offers Immense Potential for AI Aggregation Platforms
Voice-activated assistants, such as Alexa, Google Assistant and Siri are becoming a central way to consume bite-size news. This lends itself to great potential for AI aggregators to send short-form, context-sensitive updates through smart speakers, car infotainment systems, and wearables. These integrations lift daily engagement by folding news into routines such as commuting or cooking. Fueled by AI voice synthesis and sentiment analysis, audio-centric, screen-light user consumption will promote wider distribution with integrations or partnerships with device makers for bundled or native content delivery
As of 2025, the U.S. has 154.3 million voice-assistant users, including 77.6 million Alexa, 92.4 million Google Assistant, and 87.0 million Siri users spanning smart speakers, phones, cars, and wearables.
Additionally, 62% of Americans aged 18 and above regularly use voice assistants on such devices.
Alexa alone supports over 100,000 skills, including news flash briefings and voice-enabled routines, making it a robust platform for AI-driven news delivery.
Challenges:
Lack of Standardized Evaluation Metrics for AI News Aggregators Hinders Trust, Benchmarking, and Adoption Across Markets
The lack of measurements and benchmarks to gauge accuracy, bias-mitigation, and algorithmic performance in the AI news aggregation ecosystem. This lack of benchmarks makes it difficult for consumers and businesses to compare services or claims of being fair and transparent. This lack of clarity does not help our platform credibility, it does not support institutional trust, and it does not support investment. Regulators also struggle to enforce compliance in the absence of standardized assessment. This can only be solved through industry-wide standards and third-party audits. Until then, partial definitions of “quality” AI aggregation will prevent mainstream adoption and global scale.
In Canada, 85% of news consumers want transparency around how AI is used in journalism, and 75% want AI content clearly labeled.
A Pew/Brookings-style survey found that 82% of the U.S. voters believe tech companies cannot be trusted to self-regulate AI and support multi-stakeholder oversight.
Additionally, a Reuters Institute survey of ~100,000 people across 47 countries revealed that 52% of U.S. respondents are uncomfortable with AI-generated news, with only 23% expressing comfort highlighting persistent skepticism toward AI in journalism.
By Component
Software segment dominated the AI-Driven News Aggregation Market share of about 64% in 2024 due to its scalability, rapidly deployable, easy to integrate with a company's existing virtual infrastructure, and is scalable. It supports real-time processing data at scale, advanced analysis, and dynamic updates, and is widely adopted in business for automated and personalized news recommendation. Its cross-platform flexibility also helps drive enterprise adoption across industries, such as media, finance and education.
Services segment is expected to grow at the fastest CAGR of about 18.83% over 2025–2032, owing to increase in requirement for custom implementation, training, and AI integration support. Companies are increasingly using managed services to keep their AI systems running and performing well, especially in a lack of in-house AI expertise. Consulting services that provide custom aggregation solutions to help users draw better conclusions, monitoring and user engagement are driving growth as well.
By Application
Personalized News segment dominated the AI-Driven News Aggregation Market with the highest revenue share of about 30% in 2024 due to the increasing consumers demand for content that mirrors their behavior, interests, and browsing history. Personalization engines driven by AI increase user engagement and retention by weeding out junk stories, serving up relevant updates on-the-fly, and raising the value of news sites for advertisers and subscribers that want more clicks and loyalty.
Content Recommendation segment is expected to grow at the fastest CAGR of about 19.33% during 2025–2032, as a rising innovation in machine learning algorithms for improved content discovery and cross-platform engagement. Such systems encourage users to discover new topics and sources, thereby enhancing interaction time and user satisfaction. Increasing need for predictive analytics and contextual content placement is also expected to drive the growth of this segment in both consumer and enterprise applications.
By End-User
Media & Entertainment segment dominated the AI-Driven News Aggregation Market with the highest revenue share of about 30% in 2024 as they invested heavily in real time news delivery, audience analytics, and competitive content strategies. AI is used by media houses for personalized headlines, trend tracking, and user experience enhancement. This segment is early to increase the use of AI aggregation solutions due to high digital penetration and growing preference for consumption of the dynamic content.
Individuals segment is expected to grow at the fastest CAGR of about 19.68% during 2025–2032 as end-users demand personalized, spam-free news experiences on all devices. With the ubiquity of smartphones, smartwatches and voice assistants, we are happy to adopt AI tools that enable us to consume the news at greater speed. Greater transparency of algorithmic curation and the prevalence of freemium models also contribute to participation, particularly from younger, digitally savvy users who have a preference for personalized, real-time news feeds.
By Deployment Mode
Cloud segment dominated the AI-Driven News Aggregation Market with the highest revenue share of about 60% in 2024, and is expected to grow at the fastest CAGR of about 18.37% during 2025–2032. This growth is driven by the cloud’s ability to scale, change and be cost-efficient in managing large amounts of real-time data. Cloud-based platforms help to streamline the use of AI tools, and expedite the roll-out of updates, anywhere, anytime on any device. Cloud based models are preferred by media companies and organizations for enabling dynamic content delivery, improving user experience and reducing maintenance/infrastructure spend substantially.
North America
North America dominated the AI-Driven News Aggregation Market with the highest revenue share of about 40% in 2024 as the region has high adoption rate of advanced digital technologies, higher number of smartphone users, and existence of major tech giants. Heavy investment in AI technologies, extensive adoption of personalized content platforms and need for real-time news analytics from enterprises and media organizations also served the region well in leading in this segment.
A June 2025 Reuters Institute report found that 15% of Americans under 25 use AI chatbots such as ChatGPT and Gemini weekly for news, compared to 7% overall.
The same report highlighted a post-January 2025 trend where more Americans now get news from social and video platforms than from traditional TV or news websites marking a significant shift in consumption behavior that fuels AI aggregator adoption.
The U.S. is dominating the AI-Driven News Aggregation Market due to its advanced AI ecosystem, strong digital infrastructure, and high adoption across media platforms.
Asia Pacific
Asia Pacific is expected to grow at the fastest CAGR of about 20.13% during 2025–2032, due to the fast-paced digitalization, increase in the internet user base, and increasing requirement of local language news content. Governments and enterprises in India, China, and Southeast Asia are actively promoting the adoption of AI to enhance information accessibility. Rising adoption of smartphones and multilingual content requirement are also aiding the need for smart, instantaneous news delivery systems across various communities.
China is dominating the AI-Driven News Aggregation Market in Asia Pacific due to its massive user base, strong AI capabilities, and government-backed digital transformation initiatives.
Europe
AI-Driven News Aggregation Market trends in Europe indicate moderate growth, driven by a rising user base seeking personalized content, strict government regulations on news transparency and AI technologies, and increasing investments by media organizations across the UK, Germany, France, and other key markets.
The EU AI Act, effective 1 August 2024, introduces mandatory transparency rules for all AI systems including news aggregators and bans “unacceptable risk” AI systems, such as those that manipulate or socially score users.
Prohibitions on banned AI practices came into effect on 2 February 2025
Transparency obligations for general-purpose AI systems, such as publisher aggregators, will begin on 2 August 2025
The U.K. is dominating the AI-Driven News Aggregation Market in Europe due to its strong tech ecosystem, digital media consumption, and AI innovation leadership.
Middle East & Africa and Latin America
In the AI-Driven News Aggregation Market Middle East & Africa and Latin America are also increasing their growth by adopting news applications for smartphones, digital news platforms, and localized AI-driven content delivery within urban populated areas and emerging tech ecosystems.
AI-Driven News Aggregation Market companies are Google, Microsoft, Yahoo, Apple, Flipboard, SmartNews, News360, Feedly, Inshorts, Axel Springer, Reddit, Mozilla, Microsoft (for Bing News), Euronews, ByteDance (for News Republic), Ground News, Briefly News, and Artifact.
2024: Flipboard unveiled Surf, a decentralized content aggregator that combines content from Bluesky, Threads, and Mastodon. Surf aims to unify federated social feeds with AI-enhanced personalization inside the Flipboard ecosystem.
2025: Reddit launched Reddit Answers, an AI-powered search tool that summarizes user discussions using real posts. It provides contextual overviews and links back to original threads, enhancing content discovery and transparency.
2024: Yahoo acquired Artifact, a personalized AI-driven news app by Instagram’s founders. Artifact’s advanced recommendation technology is being integrated into Yahoo News to deliver more tailored and intelligent content discovery.
| Report Attributes | Details |
|---|---|
| Market Size in 2024 | USD 2.43 Billion |
| Market Size by 2032 | USD 8.84 Billion |
| CAGR | CAGR of 17.62% From 2025 to 2032 |
| Base Year | 2024 |
| Forecast Period | 2025-2032 |
| Historical Data | 2021-2023 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segments | • By Component(Software,Services) • By Application(Personalized News,Real-Time Alerts,Content Recommendation,Sentiment Analysis,Others) • By DeploymentMode(Cloud,On-Premises) • By End-User(Media & Entertainment,Enterprises,Individuals,Government,Others) |
| Regional Analysis/Coverage | North America (US, Canada, Mexico), Europe (Germany, France, UK, Italy, Spain, Poland, Turkey, Rest of Europe), Asia Pacific (China, India, Japan, South Korea, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (UAE, Saudi Arabia, Qatar, South Africa, Rest of Middle East & Africa), Latin America (Brazil, Argentina, Rest of Latin America) |
| Company Profiles | Google, Microsoft, Yahoo, Apple, Flipboard, SmartNews, News360, Feedly, Inshorts, Axel Springer, Reddit, Mozilla, Microsoft (for Bing News), Euronews, ByteDance (for News Republic), Ground News, Briefly News, Artifact |
Ans: The AI-Driven News Aggregation Market is projected to grow at a CAGR of 17.62% from 2025 to 2032, driven by rising demand for personalized content.
Ans: The market size of the AI-Driven News Aggregation Market was valued at USD 2.43 billion in 2024 globally, led by software and media segments.
Ans: The major growth factor is increasing demand for real-time, personalized news experiences enhanced by AI, NLP, and sentiment analysis technologies.
Ans: The software segment dominated with a 64% share in 2024 due to scalability, real-time analytics, and easy integration with digital infrastructures.
Ans: North America led the market in 2024 with a 40% revenue share, driven by tech innovation, mobile usage, and AI-powered media adoption.
Table Of Content
1. Introduction
1.1 Market Definition
1.2 Scope (Inclusion and Exclusions)
1.3 Research Assumptions
2. Executive Summary
2.1 Market Overview
2.2 Regional Synopsis
2.3 Competitive Summary
3. Research Methodology
3.1 Top-Down Approach
3.2 Bottom-up Approach
3.3. Data Validation
3.4 Primary Interviews
4. Market Dynamics Impact Analysis
4.1 Market Driving Factors Analysis
4.1.1 Drivers
4.1.2 Restraints
4.1.3 Opportunities
4.1.4 Challenges
4.2 PESTLE Analysis
4.3 Porter’s Five Forces Model
5. Statistical Insights and Trends Reporting
5.1 Content Output & Engagement Metrics
5.2 Data Source Diversity
5.3 Consumer Trust & Behavior Trends
5.4 Sentiment & Bias Detection Metrics
5.5 Cross-Platform Integration Stats
6. Competitive Landscape
6.1 List of Major Companies By Region
6.2 Market Share Analysis By Region
6.3 Product Benchmarking
6.3.1 Product specifications and features
6.3.2 Pricing
6.4 Strategic Initiatives
6.4.1 Marketing and promotional activities
6.4.2 Distribution and Supply Chain Strategies
6.4.3 Expansion plans and new product launches
6.4.4 Strategic partnerships and collaborations
6.5 Technological Advancements
6.6 Market Positioning and Branding
7. AI-Driven News Aggregation Market Segmentation By Application
7.1 Chapter Overview
7.2 Personalized News
7.2.1 Personalized News Market Trends Analysis (2021-2032)
7.2.2 Personalized News Market Size Estimates and Forecasts to 2032 (USD Billion)
7.3 Real-Time Alerts
7.3.1 Real-Time Alerts Market Trends Analysis (2021-2032)
7.3.2 Real-Time Alerts Market Size Estimates and Forecasts to 2032 (USD Billion)
7.4 Content Recommendation
7.4.1 Content Recommendation Market Trends Analysis (2021-2032)
7.4.2 Content Recommendation Market Size Estimates and Forecasts to 2032 (USD Billion)
7.5 Sentiment Analysis
7.5.1 Sentiment Analysis Market Trends Analysis (2021-2032)
7.5.2 Sentiment Analysis Market Size Estimates and Forecasts to 2032 (USD Billion)
7.6 Others
7.6.1 Others Market Trends Analysis (2021-2032)
7.6.2 Others Market Size Estimates and Forecasts to 2032 (USD Billion)
8. AI-Driven News Aggregation Market Segmentation By Component
8.1 Chapter Overview
8.2 Software
8.2.1 Software Market Trends Analysis (2021-2032)
8.2.2 Software Market Size Estimates and Forecasts to 2032 (USD Billion)
8.3 Services
8.3.1 Services Market Trends Analysis (2021-2032)
8.3.2 Services Market Size Estimates and Forecasts to 2032 (USD Billion)
9. AI-Driven News Aggregation Market Segmentation By Deployment Mode
9.1 Chapter Overview
9.2 On-Premise
9.2.1 On-Premise Market Trends Analysis (2021-2032)
9.2.2 On-Premise Market Size Estimates and Forecasts to 2032 (USD Billion)
9.3 Cloud
9.3.1 Cloud Market Trends Analysis (2021-2032)
9.3.2 Cloud Market Size Estimates and Forecasts to 2032 (USD Billion)
10. AI-Driven News Aggregation Market Segmentation by End-User
10.1 Chapter Overview
10.2 Media & Entertainment
10.2.1 Media & Entertainment Market Trends Analysis (2021-2032)
10.2.2 Media & Entertainment Market Size Estimates and Forecasts to 2032 (USD Billion)
10.3 Enterprises
10.3.1 Enterprises Market Trend Analysis (2021-2032)
10.3.2 Enterprises Market Size Estimates and Forecasts to 2032 (USD Billion)
10.4 Individuals
10.4.1 Individuals Market Trends Analysis (2021-2032)
10.4.2 Individuals Market Size Estimates and Forecasts to 2032 (USD Billion)
10.5 Government
10.5.1 Government Market Trends Analysis (2021-2032)
10.5.2 Government Market Size Estimates and Forecasts to 2032 (USD Billion)
10.6 Others
10.6.1 Others Market Trends Analysis (2021-2032)
10.6.2 Others Market Size Estimates and Forecasts to 2032 (USD Billion)
11. Regional Analysis
11.1 Chapter Overview
11.2 North America
11.2.1 Trend Analysis
11.2.2 North America AI-Driven News Aggregation Market Estimates and Forecasts by Country (2021-2032) (USD Billion)
11.2.3 North America AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.2.4 North America AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.2.5 North America AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.2.6 North America AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.2.7 USA
11.2.7.1 USA AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.2.7.2 USA AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.2.7.3 USA AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.2.7.4 USA AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.2.8 Canada
11.2.8.1 Canada AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.2.8.2 Canada AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.2.8.3 Canada AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.2.8.4 Canada AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.2.9 Mexico
11.2.9.1 Mexico AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.2.9.2 Mexico AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.2.9.3 Mexico AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.2.9.4 Mexico AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.3 Europe
11.3.1 Trend Analysis
11.3.2 Europe AI-Driven News Aggregation Market Estimates and Forecasts by Country (2021-2032) (USD Billion)
11.3.3 Europe AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.3.4 Europe AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.3.5 Europe AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.3.6 Europe AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.3.7 Germany
11.3.7.1 Germany AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.3.7.2 Germany AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.3.7.3 Germany AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.3.7.4 Germany AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.3.8 France
11.3.8.1 France AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.3.8.2 France AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.3.8.3 France AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.3.8.4 France AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.3.9 UK
11.3.9.1 UK AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.3.9.2 UK AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.3.9.3 UK AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.3.9.4 UK AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.3.10 Italy
11.3.10.1 ItalyAI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.3.10.2 Italy AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.3.10.3 Italy AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.3.10.4 Italy AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.3.11 Spain
11.3.11.1 Spain AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.3.11.2 Spain AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.3.11.3 Spain AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.3.11.4 Spain AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.3.12 Poland
11.3.12.1 Poland AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.3.12.2 Poland AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.3.12.3 Poland AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.3.12.4 Poland AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.3.13 Turkey
11.3.13.1 Turkey AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.3.13.2 Turkey AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.3.13.3 Turkey AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.3.13.4 Turkey AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.3.14 Rest of Europe
11.3.14.1 Rest of Europe AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.3.14.2 Rest of Europe AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.3.14.3 Rest of Europe AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.3.14.4 Rest of Europe AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.4 Asia Pacific
11.4.1 Trend Analysis
11.4.2 Asia Pacific AI-Driven News Aggregation Market Estimates and Forecasts by Country (2021-2032) (USD Billion)
11.4.3 Asia Pacific AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.4.4 Asia Pacific AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.4.5 Asia Pacific AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.4.6 Asia Pacific AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.4.7 China
11.4.7.1 China AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.4.7.2 China AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.4.7.3 China AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.4.7.4 China AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.4.8 India
11.4.8.1 India AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.4.8.2 India AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.4.8.3 India AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.4.8.4 India AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.4.9 Japan
11.4.9.1 Japan AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.4.9.2 Japan AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.4.9.3 Japan AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.4.9.4 Japan AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.4.10 South Korea
11.4.10.1 South Korea AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.4.10.2 South Korea AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.4.10.3 South Korea AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.4.10.4 South Korea AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.4.11 Singapore
11.4.11.1 Singapore AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.4.11.2 Singapore AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.4.11.3 Singapore AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.4.11.4 Singapore AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.4.12 Australia
11.4.12.1 Australia AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.4.12.2 Australia AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.4.12.3 Australia AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.4.12.4 Australia AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.4.13 Rest of Asia Pacific
11.4.13.1 Rest of Asia Pacific AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.4.13.2 Rest of Asia Pacific AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.4.13.3 Rest of Asia Pacific AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.4.13.4 Rest of Asia Pacific AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.5 Middle East and Africa
11.5.1 Trend Analysis
11.5.2 Middle East and Africa AI-Driven News Aggregation Market Estimates and Forecasts by Country (2021-2032) (USD Billion)
11.5.3 Middle East and Africa AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.5.4 Middle East and Africa AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.5.5 Middle East and Africa AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.5.6 Middle East and Africa AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.5.7 UAE
11.5.7.1 UAE AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.5.7.2 UAE AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.5.7.3 UAE AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.5.7.4 UAE AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.5.8 Saudi Arabia
11.5.8.1 Saudi Arabia AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.5.8.2 Saudi Arabia AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.5.8.3 Saudi Arabia AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.5.8.4 Saudi Arabia AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.5.9 Qatar
11.5.9.1 Qatar AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.5.9.2 Qatar AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.5.9.3 Qatar AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.5.1.9.4 Qatar AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.5.10 South Africa
11.5.10.1 South Africa AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.5.10.2 South Africa AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.5.10.3 South Africa AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.5.10.4 South Africa AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.5.11 Rest of Middle East & Africa
11.5.11.1 Rest of Middle East & Africa AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.5.11.2 Rest of Middle East & Africa AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.5.11.3 Rest of Middle East & Africa AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.5.11.4 Rest of Middle East & Africa AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.6 Latin America
11.6.1 Trend Analysis
11.6.2 Latin America AI-Driven News Aggregation Market Estimates and Forecasts by Country (2021-2032) (USD Billion)
11.6.3 Latin America AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.6.4 Latin America AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.6.5 Latin America AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.6.6 Latin America AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.6.7 Brazil
11.6.7.1 Brazil AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.6.7.2 Brazil AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.6.7.3 Brazil AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.6.7.4 Brazil AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.6.8 Argentina
11.6.8.1 Argentina AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.6.8.2 Argentina AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.6.8.3 Argentina AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.6.8.4 Argentina AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
11.6.9 Rest of Latin America
11.6.9.1 Rest of Latin America AI-Driven News Aggregation Market Estimates and Forecasts By Application (2021-2032) (USD Billion)
11.6.9.2 Rest of Latin America AI-Driven News Aggregation Market Estimates and Forecasts By Component (2021-2032) (USD Billion)
11.6.9.3 Rest of Latin America AI-Driven News Aggregation Market Estimates and Forecasts By Deployment Mode (2021-2032) (USD Billion)
11.6.9.4 Rest of Latin America AI-Driven News Aggregation Market Estimates and Forecasts by End-User (2021-2032) (USD Billion)
12. Company Profiles
12.1 Google
12.1.1 Company Overview
12.1.2 Financial
12.1.3 Products/ Services Offered
12.1.4 SWOT Analysis
12.2 Microsoft
12.2.1 Company Overview
12.2.2 Financial
12.2.3 Products/ Services Offered
12.2.4 SWOT Analysis
12.3 Yahoo
12.3.1 Company Overview
12.3.2 Financial
12.3.3 Products/ Services Offered
12.3.4 SWOT Analysis
12.4 Apple
12.4.1 Company Overview
12.4.2 Financial
12.4.3 Products/ Services Offered
12.4.4 SWOT Analysis
12.5 Flipboard
12.5.1 Company Overview
12.5.2 Financial
12.5.3 Products/ Services Offered
12.5.4 SWOT Analysis
12.6 SmartNews
12.6.1 Company Overview
12.6.2 Financial
12.6.3 Products/ Services Offered
12.6.4 SWOT Analysis
12.7 News360
12.7.1 Company Overview
12.7.2 Financial
12.7.3 Products/ Services Offered
12.7.4 SWOT Analysis
12.8 Feedly
12.8.1 Company Overview
12.8.2 Financial
12.8.3 Products/ Services Offered
12.8.4 SWOT Analysis
12.9 Inshorts
12.9.1 Company Overview
12.9.2 Financial
12.9.3 Products/ Services Offered
12.9.4 SWOT Analysis
12.10 Axel Springer
12.10.1 Company Overview
12.10.2 Financial
12.10.3 Products/ Services Offered
12.10.4 SWOT Analysis
13. Use Cases and Best Practices
14. Conclusion
An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.
Each report that we prepare takes a timeframe of 350-400 business hours for production. Starting from the selection of titles through a couple of in-depth brain storming session to the final QC process before uploading our titles on our website we dedicate around 350 working hours. The titles are selected based on their current market cap and the foreseen CAGR and growth.
The 5 steps process:
Step 1: Secondary Research:
Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.
Step 2: Primary Research
When we talk about primary research, it is a type of study in which the researchers collect relevant data samples directly, rather than relying on previously collected data. This type of research is focused on gaining content specific facts that can be sued to solve specific problems. Since the collected data is fresh and first hand therefore it makes the study more accurate and genuine.
We at SNS Insider have divided Primary Research into 2 parts.
Part 1 wherein we interview the KOLs of major players as well as the upcoming ones across various geographic regions. This allows us to have their view over the market scenario and acts as an important tool to come closer to the accurate market numbers. As many as 45 paid and unpaid primary interviews are taken from both the demand and supply side of the industry to make sure we land at an accurate judgement and analysis of the market.
This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.
Part 2: In this part of primary research the data collected via secondary research and the part 1 of the primary research is validated with the interviews from individual consultants and subject matter experts.
Consultants are those set of people who have at least 12 years of experience and expertise within the industry whereas Subject Matter Experts are those with at least 15 years of experience behind their back within the same space. The data with the help of two main processes i.e., FGDs (Focused Group Discussions) and IDs (Individual Discussions). This gives us a 3rd party nonbiased primary view of the market scenario making it a more dependable one while collation of the data pointers.
Step 3: Data Bank Validation
Once all the information is collected via primary and secondary sources, we run that information for data validation. At our intelligence centre our research heads track a lot of information related to the market which includes the quarterly reports, the daily stock prices, and other relevant information. Our data bank server gets updated every fortnight and that is how the information which we collected using our primary and secondary information is revalidated in real time.
Step 4: QA/QC Process
After all the data collection and validation our team does a final level of quality check and quality assurance to get rid of any unwanted or undesired mistakes. This might include but not limited to getting rid of the any typos, duplication of numbers or missing of any important information. The people involved in this process include technical content writers, research heads and graphics people. Once this process is completed the title gets uploader on our platform for our clients to read it.
Step 5: Final QC/QA Process:
This is the last process and comes when the client has ordered the study. In this process a final QA/QC is done before the study is emailed to the client. Since we believe in giving our clients a good experience of our research studies, therefore, to make sure that we do not lack at our end in any way humanly possible we do a final round of quality check and then dispatch the study to the client.
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Rest of Europe
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Rest of Asia Pacific
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With the given market data, SNS Insider offers customization as per the company’s specific needs. The following customization options are available for the report:
Detailed Volume Analysis
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Competitive Product Benchmarking
Geographic Analysis
Additional countries in any of the regions
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