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시장보고서

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세계의 컨텐츠 추천 엔진 시장 규모 조사 및 예측 : 구성요소별, 필터링 접근 방식별, 조직 규모별, 지역별 예측(2025-2035년)

Global Content Recommendation Engine Market Size Study & Forecast, by Component, by Filtering Approach, by Organization Size and Regional Forecasts 2025-2035

발행일: 2025년 09월 | 리서치사:

Bizwit Research & Consulting LLP | 페이지 정보: 영문 285 Pages | 배송안내 : 2-3일 (영업일 기준)

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시장 정의와 개요

세계 컨텐츠 추천 엔진 시장은 2024년에 약 84억 2,000만 달러로 평가되며, 2025년부터 2035년까지 예측 기간 동안 28.50%의 CAGR로 확대되어 2035년에는 1,328억 1,000만 달러에 달할 것으로 예상됩니다. 컨텐츠 추천 엔진은 인공지능(AI), 머신러닝(ML), 예측 분석을 활용하여 디지털 플랫폼에서 사용자에게 개인화된 제안을 제공하는 고도화된 시스템입니다. 선호도, 검색 기록, 검색 패턴, 구매 행동 등 방대한 소비자 데이터의 흐름을 분석함으로써, 이들 엔진은 사용자 참여를 높일 뿐만 아니라 기업의 수익화 전략도 촉진합니다. 이러한 시스템에 대한 수요는 디지털 미디어 소비의 급격한 증가, E-Commerce 활동의 급증, 고객 경험과 고객 유지를 향상시키기 위한 데이터 기반 개인화에 대한 기업의 의존도가 높아짐에 따라 증가하고 있습니다.

각 산업 분야에서 디지털 전환이 가속화되면서 추천 엔진의 도입이 가속화되고 있습니다. 소매, 엔터테인먼트, BFSI, 헬스케어 등 다양한 분야의 기업들은 교차판매, 상향판매, 고객 참여 이니셔티브를 강화하기 위해 이러한 시스템을 자사 플랫폼에 통합하고 있습니다. 업계에서는 고급 추천 시스템을 갖춘 플랫폼의 경우 사용자 참여도가 최대 30%까지 향상되고 전환율이 크게 개선된 것으로 보고되고 있습니다. 또한, 클라우드 컴퓨팅과 실시간 분석 추천 기술의 통합은 애플리케이션의 범위를 넓히고 배포의 복잡성을 줄여주고 있습니다. 그럼에도 불구하고, 데이터 프라이버시에 대한 우려와 소비자 데이터의 윤리적 사용에 대한 규제 프레임워크와 같은 이슈는 향후 몇 년 동안 시장 성장 속도를 저해할 수 있는 요인으로 작용할 수 있습니다.

본 보고서에 포함된 세부 부문 및 하위 부문은 다음과 같습니다:

Porter's Five Forces 모델
- 구매자의 교섭력
- 공급업체의 협상력
- 신규 참여업체의 위협
- 대체품의 위협
- 경쟁 기업 간의 경쟁 관계
Porter's Five Forces 예측 모델(2024-2035)
PESTEL 분석
- 정치
- 경제
- 사회
- 기술
- 환경
- 법률
주요 투자 기회
주요 성공 전략(2025)
시장 점유율 분석(2024-2025)
세계의 가격 분석과 동향 2025
애널리스트의 제안과 결론

제5장 세계의 컨텐츠 추천 엔진 시장 규모 및 예측 : 구성요소별, 2025-2035년

시장 개요
세계의 컨텐츠 추천 엔진 시장 실적 - 잠재적 분석(2025)
솔루션

제6장 세계의 컨텐츠 추천 엔진 시장 규모 및 예측 : 필터링 접근 방식별, 2025-2035년

시장 개요
세계의 컨텐츠 추천 엔진 시장 실적 - 잠재적 분석(2025)
협업 필터링
컨텐츠 기반 필터링

제7장 세계의 컨텐츠 추천 엔진 시장 규모 및 예측 : 조직 규모별, 2025-2035년

시장 개요
세계의 컨텐츠 추천 엔진 시장 실적 - 잠재적 분석(2025)
중소기업
대기업

제8장 세계의 컨텐츠 추천 엔진 시장 규모 및 예측 : 지역별, 2025-2035년

지역 시장 현황
주요 선진국 및 신흥국
북미
- 미국
- 캐나다
유럽
- 영국
- 독일
- 프랑스
- 스페인
- 이탈리아
- 기타 유럽
아시아태평양
- 중국
- 인도
- 일본
- 호주
- 한국
- 기타 아시아태평양
라틴아메리카
- 브라질
- 멕시코
중동 및 아프리카
- 아랍에미리트
- 사우디아라비아(KSA)
- 남아프리카공화국

제9장 경쟁 정보

주요 시장 전략
Amazon Web Services Inc.
- 기업 개요
- 주요 임원
- 기업 개요
- 재무 실적(데이터 가용성에 따라 다름)
- 제품/서비스 포트
- 최근의 개발
- 시장 전략
- SWOT 분석
Google LLC
Microsoft Corporation
IBM Corporation
Oracle Corporation
Salesforce Inc.
Adobe Inc.
SAP SE
Intel Corporation
Hewlett Packard Enterprise Development LP
Tata Consultancy Services Limited
Infosys Limited
Accenture Plc
SAS Institute Inc.
Netflix Inc.

KSM 25.10.13

Market Definition and Overview

The Global Content Recommendation Engine Market is valued at approximately USD 8.42 billion in 2024 and is expected to expand at a CAGR of 28.50% during the forecast period of 2025-2035, ultimately reaching USD 132.81 billion by 2035. A content recommendation engine is a sophisticated system that leverages artificial intelligence (AI), machine learning (ML), and predictive analytics to deliver personalized suggestions to users across digital platforms. By analyzing vast streams of consumer data such as preferences, search history, browsing patterns, and purchasing behavior, these engines not only enhance user engagement but also drive monetization strategies for enterprises. The demand for such systems is being driven by exponential growth in digital media consumption, a surge in e-commerce activities, and the increasing reliance of businesses on data-driven personalization to improve customer experience and retention.

The accelerated digital transformation across industries has intensified the adoption of recommendation engines. Companies spanning retail, entertainment, BFSI, and healthcare are integrating these systems into their platforms to elevate cross-selling, upselling, and customer engagement initiatives. According to industry insights, platforms with advanced recommendation systems have reported up to 30% increases in user engagement and a marked improvement in conversion rates. Furthermore, the integration of cloud computing and real-time analytics into recommendation technologies is broadening the scope of applications and reducing deployment complexities. Nonetheless, challenges such as data privacy concerns and regulatory frameworks regarding the ethical use of consumer data pose certain restraints that may impede the pace of market growth in the coming years.

The detailed segments and sub-segments included in the report are:

By Component:

Solution

By Filtering Approach:

Collaborative Filtering
Content-Based Filtering

By Organization Size:

Small & Medium Enterprises (SMEs)
Large Enterprises

By Region:

North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Middle East & Africa
UAE
Saudi Arabia
South Africa
Rest of Middle East & Africa
Segment Insights
Collaborative filtering is anticipated to dominate the global content recommendation engine market throughout the forecast period. This approach capitalizes on user behavior patterns and community data to generate accurate predictions, making it especially effective for e-commerce platforms, video-on-demand services, and digital retail applications. As enterprises strive to replicate the seamless personalization experiences of global leaders such as Amazon and Netflix, collaborative filtering stands out as the cornerstone technology driving deeper customer connections and repeat interactions.
From a revenue contribution perspective, large enterprises currently lead the market. With their expansive customer bases and vast data ecosystems, these organizations are in a unique position to maximize the return on investment from recommendation systems. Enterprises in industries such as streaming, banking, and retail have been quick to scale solutions that enhance lifetime customer value, improve recommendation accuracy, and strengthen competitive positioning. Meanwhile, SMEs, powered by cloud-based and cost-efficient solutions, are rapidly catching up as accessibility to sophisticated recommendation platforms widens.
The Global Content Recommendation Engine Market exhibits notable geographic trends. North America accounted for the largest market share in 2025, underpinned by strong adoption across media and entertainment, retail, and IT sectors, along with the region's early embrace of AI-driven personalization. Europe follows closely, driven by its growing e-commerce penetration and regulatory compliance with GDPR, which has accelerated the adoption of transparent and ethical recommendation solutions. The Asia Pacific region is expected to witness the fastest growth over the forecast period, propelled by rapid digitalization, increasing smartphone penetration, and booming demand for streaming and e-commerce platforms in China, India, and Southeast Asia. Government-backed digital initiatives and robust startup ecosystems in the region are further augmenting growth prospects.

Major market players included in this report are:

Amazon Web Services Inc.
Google LLC
Microsoft Corporation
IBM Corporation
Oracle Corporation
Salesforce Inc.
Adobe Inc.
SAP SE
Intel Corporation
Hewlett Packard Enterprise Development LP
Tata Consultancy Services Limited
Infosys Limited
Accenture Plc
SAS Institute Inc.
Netflix Inc.

Global Content Recommendation Engine Market Report Scope:

Historical Data - 2023, 2024
Base Year for Estimation - 2024
Forecast period - 2025-2035
Report Coverage - Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Regional Scope - North America; Europe; Asia Pacific; Latin America; Middle East & Africa
Customization Scope - Free report customization (equivalent to up to 8 analysts' 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 for the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within the countries involved in the study. The report also provides detailed information about crucial aspects, such as driving factors and challenges, which will define the future growth of the market. Additionally, it incorporates potential opportunities in micro-markets for stakeholders to invest, along with a detailed analysis of the competitive landscape and product offerings of key players. The detailed segments and sub-segments of the market are explained below:

Key Takeaways:

Market Estimates & Forecast for 10 years from 2025 to 2035.
Annualized revenues and regional-level analysis for each market segment.
Detailed analysis of the geographical landscape with country-level analysis of major regions.
Competitive landscape with information on major players in the market.
Analysis of key business strategies and recommendations on future market approach.
Analysis of the competitive structure of the market.
Demand side and supply side analysis of the market.

Chapter 1. Global Content Recommendation Engine Market Report Scope & Methodology

1.1. Research Objective
1.2. Research Methodology
- 1.2.1. Forecast Model
- 1.2.2. Desk Research
- 1.2.3. Top Down and Bottom-Up Approach
1.3. Research Attributes
1.4. Scope of the Study
- 1.4.1. Market Definition
- 1.4.2. Market Segmentation
1.5. Research Assumption
- 1.5.1. Inclusion & Exclusion
- 1.5.2. Limitations
- 1.5.3. Years Considered for the Study

Chapter 2. Executive Summary

2.1. CEO/CXO Standpoint
2.2. Strategic Insights
2.3. ESG Analysis
2.4. key Findings

Chapter 3. Global Content Recommendation Engine Market Forces Analysis

3.1. Market Forces Shaping The Global Content Recommendation Engine Market (2024-2035)
3.2. Drivers
- 3.2.1. exponential growth in digital media consumption
- 3.2.2. a surge in e-commerce activities
3.3. Restraints
- 3.3.1. data privacy concerns
3.4. Opportunities
- 3.4.1. increasing reliance of businesses on data-driven personalization

Chapter 4. Global Content Recommendation Engine Industry Analysis

4.1. Porter's 5 Forces Model
- 4.1.1. Bargaining Power of Buyer
- 4.1.2. Bargaining Power of Supplier
- 4.1.3. Threat of New Entrants
- 4.1.4. Threat of Substitutes
- 4.1.5. Competitive Rivalry
4.2. Porter's 5 Force Forecast Model (2024-2035)
4.3. PESTEL 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 Opportunities
4.5. Top Winning Strategies (2025)
4.6. Market Share Analysis (2024-2025)
4.7. Global Pricing Analysis And Trends 2025
4.8. Analyst Recommendation & Conclusion

Chapter 5. Global Content Recommendation Engine Market Size & Forecasts by Component 2025-2035

5.1. Market Overview
5.2. Global Content Recommendation Engine Market Performance - Potential Analysis (2025)
5.3. Solution
- 5.3.1. Top Countries Breakdown Estimates & Forecasts, 2024-2035
- 5.3.2. Market size analysis, by region, 2025-2035

Chapter 6. Global Content Recommendation Engine Market Size & Forecasts by Filtering approach 2025-2035

6.1. Market Overview
6.2. Global Content Recommendation Engine Market Performance - Potential Analysis (2025)
6.3. Collaborative Filtering
- 6.3.1. Top Countries Breakdown Estimates & Forecasts, 2024-2035
- 6.3.2. Market size analysis, by region, 2025-2035
6.4. Content-Based Filtering
- 6.4.1. Top Countries Breakdown Estimates & Forecasts, 2024-2035
- 6.4.2. Market size analysis, by region, 2025-2035

Chapter 7. Global Content Recommendation Engine Market Size & Forecasts by Organization size 2025-2035

7.1. Market Overview
7.2. Global Content Recommendation Engine Market Performance - Potential Analysis (2025)
7.3. Small & Medium Enterprises (SMEs)
- 7.3.1. Top Countries Breakdown Estimates & Forecasts, 2024-2035
- 7.3.2. Market size analysis, by region, 2025-2035
7.4. Large Enterprises
- 7.4.1. Top Countries Breakdown Estimates & Forecasts, 2024-2035
- 7.4.2. Market size analysis, by region, 2025-2035

Chapter 8. Global Content Recommendation Engine Market Size & Forecasts by Region 2025-2035

8.1. Growth Content Recommendation Engine Market, Regional Market Snapshot
8.2. Top Leading & Emerging Countries
8.3. North America Content Recommendation Engine Market
- 8.3.1. U.S. Content Recommendation Engine Market
  - 8.3.1.1. Component breakdown size & forecasts, 2025-2035
  - 8.3.1.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.3.1.3. Organization size breakdown size & forecasts, 2025-2035
- 8.3.2. Canada Content Recommendation Engine Market
  - 8.3.2.1. Component breakdown size & forecasts, 2025-2035
  - 8.3.2.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.3.2.3. Organization size breakdown size & forecasts, 2025-2035
8.4. Europe Content Recommendation Engine Market
- 8.4.1. UK Content Recommendation Engine Market
  - 8.4.1.1. Component breakdown size & forecasts, 2025-2035
  - 8.4.1.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.4.1.3. Organization size breakdown size & forecasts, 2025-2035
- 8.4.2. Germany Content Recommendation Engine Market
  - 8.4.2.1. Component breakdown size & forecasts, 2025-2035
  - 8.4.2.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.4.2.3. Organization size breakdown size & forecasts, 2025-2035
- 8.4.3. France Content Recommendation Engine Market
  - 8.4.3.1. Component breakdown size & forecasts, 2025-2035
  - 8.4.3.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.4.3.3. Organization size breakdown size & forecasts, 2025-2035
- 8.4.4. Spain Content Recommendation Engine Market
  - 8.4.4.1. Component breakdown size & forecasts, 2025-2035
  - 8.4.4.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.4.4.3. Organization size breakdown size & forecasts, 2025-2035
- 8.4.5. Italy Content Recommendation Engine Market
  - 8.4.5.1. Component breakdown size & forecasts, 2025-2035
  - 8.4.5.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.4.5.3. Organization size breakdown size & forecasts, 2025-2035
- 8.4.6. Rest of Europe Content Recommendation Engine Market
  - 8.4.6.1. Component breakdown size & forecasts, 2025-2035
  - 8.4.6.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.4.6.3. Organization size breakdown size & forecasts, 2025-2035
8.5. Asia Pacific Content Recommendation Engine Market
- 8.5.1. China Content Recommendation Engine Market
  - 8.5.1.1. Component breakdown size & forecasts, 2025-2035
  - 8.5.1.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.5.1.3. Organization size breakdown size & forecasts, 2025-2035
- 8.5.2. India Content Recommendation Engine Market
  - 8.5.2.1. Component breakdown size & forecasts, 2025-2035
  - 8.5.2.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.5.2.3. Organization size breakdown size & forecasts, 2025-2035
- 8.5.3. Japan Content Recommendation Engine Market
  - 8.5.3.1. Component breakdown size & forecasts, 2025-2035
  - 8.5.3.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.5.3.3. Organization size breakdown size & forecasts, 2025-2035
- 8.5.4. Australia Content Recommendation Engine Market
  - 8.5.4.1. Component breakdown size & forecasts, 2025-2035
  - 8.5.4.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.5.4.3. Organization size breakdown size & forecasts, 2025-2035
- 8.5.5. South Korea Content Recommendation Engine Market
  - 8.5.5.1. Component breakdown size & forecasts, 2025-2035
  - 8.5.5.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.5.5.3. Organization size breakdown size & forecasts, 2025-2035
- 8.5.6. Rest of APAC Content Recommendation Engine Market
  - 8.5.6.1. Component breakdown size & forecasts, 2025-2035
  - 8.5.6.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.5.6.3. Organization size breakdown size & forecasts, 2025-2035
8.6. Latin America Content Recommendation Engine Market
- 8.6.1. Brazil Content Recommendation Engine Market
  - 8.6.1.1. Component breakdown size & forecasts, 2025-2035
  - 8.6.1.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.6.1.3. Organization size breakdown size & forecasts, 2025-2035
- 8.6.2. Mexico Content Recommendation Engine Market
  - 8.6.2.1. Component breakdown size & forecasts, 2025-2035
  - 8.6.2.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.6.2.3. Organization size breakdown size & forecasts, 2025-2035
8.7. Middle East and Africa Content Recommendation Engine Market
- 8.7.1. UAE Content Recommendation Engine Market
  - 8.7.1.1. Component breakdown size & forecasts, 2025-2035
  - 8.7.1.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.7.1.3. Organization size breakdown size & forecasts, 2025-2035
- 8.7.2. Saudi Arabia (KSA) Content Recommendation Engine Market
  - 8.7.2.1. Component breakdown size & forecasts, 2025-2035
  - 8.7.2.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.7.2.3. Organization size breakdown size & forecasts, 2025-2035
- 8.7.3. South Africa Content Recommendation Engine Market
  - 8.7.3.1. Component breakdown size & forecasts, 2025-2035
  - 8.7.3.2. Filtering approach breakdown size & forecasts, 2025-2035
  - 8.7.3.3. Organization size breakdown size & forecasts, 2025-2035

Chapter 9. Competitive Intelligence

9.1. Top Market Strategies
9.2. Amazon Web Services Inc.
- 9.2.1. Company Overview
- 9.2.2. Key Executives
- 9.2.3. Company Snapshot
- 9.2.4. Financial Performance (Subject to Data Availability)
- 9.2.5. Product/Services Port
- 9.2.6. Recent Development
- 9.2.7. Market Strategies
- 9.2.8. SWOT Analysis
9.3. Google LLC
9.4. Microsoft Corporation
9.5. IBM Corporation
9.6. Oracle Corporation
9.7. Salesforce Inc.
9.8. Adobe Inc.
9.9. SAP SE
9.10. Intel Corporation
9.11. Hewlett Packard Enterprise Development LP
9.12. Tata Consultancy Services Limited
9.13. Infosys Limited
9.14. Accenture Plc
9.15. SAS Institute Inc.
9.16. Netflix Inc.

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