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Content Recommendation Engine-Global Market Insights and Sales Trends 2024
Synopsis
A recommender system or a recommendation system is a subclass of information filtering system that seeks to predict the "rating" or "preference" a user would give to an item.
The global Content Recommendation Engine market size is expected to reach US$ 16070 million by 2029, growing at a CAGR of 18.0% from 2023 to 2029. The market is mainly driven by the significant applications of Content Recommendation Engine in various end use industries. The expanding demands from the Media, Entertainment and Gaming, Retail and Consumer Goods and Hospitality, are propelling Content Recommendation Engine market. Solution, one of the segments analysed in this report, is projected to record % CAGR and reach US$ million by the end of the analysis period. Growth in the Service segment is estimated at % CAGR for the next seven-year period.
The top two companies in Content Recommendation Engines Global Market are Taboola and Outbrain with over 50% in total. Comparing by regions, North America and Europe take a huge proportion of over 80% of the global market.
Report Objectives
This report provides market insight on the different segments, by players, by Type, by Application. Market size and forecast (2018-2029) has been provided in the report. The primary objectives of this report are to provide 1) global market size and forecasts, growth rates, market dynamics, industry structure and developments, market situation, trends; 2) global market share and ranking by company; 3) comprehensive presentation of the global market for Content Recommendation Engine, with both quantitative and qualitative analysis through detailed segmentation; 4) detailed value chain analysis and review of growth factors essential for the existing market players and new entrants; 5) emerging opportunities in the market and the future impact of major drivers and restraints of the market.
Key Features of The Study:
This report provides in-depth analysis of the global Content Recommendation Engine market, and provides market size (US$ million) and CAGR for the forecast period (2023-2029), considering 2022 as the base year.
This report profiles key players in the global Content Recommendation Engine market based on the following parameters - company details (found date, headquarters, manufacturing bases), products portfolio, Content Recommendation Engine sales data, market share and ranking.
This report elucidates potential market opportunities across different segments and explains attractive investment proposition matrices for this market.
This report illustrates key insights about market drivers, restraints, opportunities, market trends, regional outlook.
Key companies of Content Recommendation Engine covered in this report include Amazon Web Services (US), Boomtrain, Certona, Curata, Cxense, Dynamic Yield, IBM, Kibo Commerce and Outbrain, etc.
The global Content Recommendation Engine market report caters to various stakeholders in this industry including investors, suppliers, product players, distributors, new entrants, and financial analysts.
Market Segmentation
Company Profiles:
Amazon Web Services (US)
Boomtrain
Certona
Curata
Cxense
Dynamic Yield
IBM
Kibo Commerce
Outbrain
Revcontent
Taboola
ThinkAnalytics
Global Content Recommendation Engine market, by region:
North America (U.S., Canada, Mexico)
Europe (Germany, France, UK, Italy, etc.)
Asia Pacific (China, Japan, South Korea, Southeast Asia, India, etc.)
South America (Brazil, etc.)
Middle East and Africa (Turkey, GCC Countries, Africa, etc.)
Global Content Recommendation Engine market, Segment by Type:
Solution
Service
Global Content Recommendation Engine market, by Application
Media
Entertainment and Gaming
Retail and Consumer Goods
Hospitality
Others
Core Chapters
Chapter One: Introduces the report scope of the report, executive summary of global and regional market size and CAGR for the history and forecast period (2018-2023, 2024-2029). It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter Two: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter Three: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter Four: Detailed analysis of Content Recommendation Engine companies’ competitive landscape, revenue, market share and ranking, latest development plan, merger, and acquisition information, etc.
Chapter Five: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product introduction, revenue, recent development, etc.
Chapter Six, Seven, Eight, Nine and Ten: North America, Europe, Asia Pacific, Latin America, Middle East & Africa, revenue by country.
Chapter Eleven: this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter Twelve: Research Finding/Conclusion
A recommender system or a recommendation system is a subclass of information filtering system that seeks to predict the "rating" or "preference" a user would give to an item.
The global Content Recommendation Engine market size is expected to reach US$ 16070 million by 2029, growing at a CAGR of 18.0% from 2023 to 2029. The market is mainly driven by the significant applications of Content Recommendation Engine in various end use industries. The expanding demands from the Media, Entertainment and Gaming, Retail and Consumer Goods and Hospitality, are propelling Content Recommendation Engine market. Solution, one of the segments analysed in this report, is projected to record % CAGR and reach US$ million by the end of the analysis period. Growth in the Service segment is estimated at % CAGR for the next seven-year period.
The top two companies in Content Recommendation Engines Global Market are Taboola and Outbrain with over 50% in total. Comparing by regions, North America and Europe take a huge proportion of over 80% of the global market.
Report Objectives
This report provides market insight on the different segments, by players, by Type, by Application. Market size and forecast (2018-2029) has been provided in the report. The primary objectives of this report are to provide 1) global market size and forecasts, growth rates, market dynamics, industry structure and developments, market situation, trends; 2) global market share and ranking by company; 3) comprehensive presentation of the global market for Content Recommendation Engine, with both quantitative and qualitative analysis through detailed segmentation; 4) detailed value chain analysis and review of growth factors essential for the existing market players and new entrants; 5) emerging opportunities in the market and the future impact of major drivers and restraints of the market.
Key Features of The Study:
This report provides in-depth analysis of the global Content Recommendation Engine market, and provides market size (US$ million) and CAGR for the forecast period (2023-2029), considering 2022 as the base year.
This report profiles key players in the global Content Recommendation Engine market based on the following parameters - company details (found date, headquarters, manufacturing bases), products portfolio, Content Recommendation Engine sales data, market share and ranking.
This report elucidates potential market opportunities across different segments and explains attractive investment proposition matrices for this market.
This report illustrates key insights about market drivers, restraints, opportunities, market trends, regional outlook.
Key companies of Content Recommendation Engine covered in this report include Amazon Web Services (US), Boomtrain, Certona, Curata, Cxense, Dynamic Yield, IBM, Kibo Commerce and Outbrain, etc.
The global Content Recommendation Engine market report caters to various stakeholders in this industry including investors, suppliers, product players, distributors, new entrants, and financial analysts.
Market Segmentation
Company Profiles:
Amazon Web Services (US)
Boomtrain
Certona
Curata
Cxense
Dynamic Yield
IBM
Kibo Commerce
Outbrain
Revcontent
Taboola
ThinkAnalytics
Global Content Recommendation Engine market, by region:
North America (U.S., Canada, Mexico)
Europe (Germany, France, UK, Italy, etc.)
Asia Pacific (China, Japan, South Korea, Southeast Asia, India, etc.)
South America (Brazil, etc.)
Middle East and Africa (Turkey, GCC Countries, Africa, etc.)
Global Content Recommendation Engine market, Segment by Type:
Solution
Service
Global Content Recommendation Engine market, by Application
Media
Entertainment and Gaming
Retail and Consumer Goods
Hospitality
Others
Core Chapters
Chapter One: Introduces the report scope of the report, executive summary of global and regional market size and CAGR for the history and forecast period (2018-2023, 2024-2029). It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter Two: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter Three: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter Four: Detailed analysis of Content Recommendation Engine companies’ competitive landscape, revenue, market share and ranking, latest development plan, merger, and acquisition information, etc.
Chapter Five: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product introduction, revenue, recent development, etc.
Chapter Six, Seven, Eight, Nine and Ten: North America, Europe, Asia Pacific, Latin America, Middle East & Africa, revenue by country.
Chapter Eleven: this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter Twelve: Research Finding/Conclusion
Index1 Market Overview of Content Recommendation Engine
1.1 Content Recommendation Engine Market Overview
1.1.1 Content Recommendation Engine Product Scope
1.1.2 Content Recommendation Engine Market Status and Outlook
1.2 Global Content Recommendation Engine Market Size Overview by Region 2018 VS 2022 VS 2029
1.3 Global Content Recommendation Engine Market Size by Region (2018-2029)
1.4 Global Content Recommendation Engine Historic Market Size by Region (2018-2023)
1.5 Global Content Recommendation Engine Market Size Forecast by Region (2024-2029)
1.6 Key Regions, Content Recommendation Engine Market Size (2018-2029)
1.6.1 North America Content Recommendation Engine Market Size (2018-2029)
1.6.2 Europe Content Recommendation Engine Market Size (2018-2029)
1.6.3 Asia-Pacific Content Recommendation Engine Market Size (2018-2029)
1.6.4 Latin America Content Recommendation Engine Market Size (2018-2029)
1.6.5 Middle East & Africa Content Recommendation Engine Market Size (2018-2029)
2 Content Recommendation Engine Market by Type
2.1 Introduction
2.1.1 Solution
2.1.2 Service
2.2 Global Content Recommendation Engine Market Size by Type: 2018 VS 2022 VS 2029
2.2.1 Global Content Recommendation Engine Historic Market Size by Type (2018-2023)
2.2.2 Global Content Recommendation Engine Forecasted Market Size by Type (2024-2029)
2.3 Key Regions Market Size by Type
2.3.1 North America Content Recommendation Engine Revenue Breakdown by Type (2018-2029)
2.3.2 Europe Content Recommendation Engine Revenue Breakdown by Type (2018-2029)
2.3.3 Asia-Pacific Content Recommendation Engine Revenue Breakdown by Type (2018-2029)
2.3.4 Latin America Content Recommendation Engine Revenue Breakdown by Type (2018-2029)
2.3.5 Middle East and Africa Content Recommendation Engine Revenue Breakdown by Type (2018-2029)
3 Content Recommendation Engine Market Overview by Application
3.1 Introduction
3.1.1 Media
3.1.2 Entertainment and Gaming
3.1.3 Retail and Consumer Goods
3.1.4 Hospitality
3.1.5 Others
3.2 Global Content Recommendation Engine Market Size by Application: 2018 VS 2022 VS 2029
3.2.1 Global Content Recommendation Engine Historic Market Size by Application (2018-2023)
3.2.2 Global Content Recommendation Engine Forecasted Market Size by Application (2024-2029)
3.3 Key Regions Market Size by Application
3.3.1 North America Content Recommendation Engine Revenue Breakdown by Application (2018-2029)
3.3.2 Europe Content Recommendation Engine Revenue Breakdown by Application (2018-2029)
3.3.3 Asia-Pacific Content Recommendation Engine Revenue Breakdown by Application (2018-2029)
3.3.4 Latin America Content Recommendation Engine Revenue Breakdown by Application (2018-2029)
3.3.5 Middle East and Africa Content Recommendation Engine Revenue Breakdown by Application (2018-2029)
4 Content Recommendation Engine Competition Analysis by Players
4.1 Global Content Recommendation Engine Market Size by Players (2018-2023)
4.2 Global Top Players by Company Type (Tier 1, Tier 2 and Tier 3) & (based on the Revenue in Content Recommendation Engine as of 2022)
4.3 Date of Key Players Enter into Content Recommendation Engine Market
4.4 Global Top Players Content Recommendation Engine Headquarters and Area Served
4.5 Key Players Content Recommendation Engine Product Solution and Service
4.6 Competitive Status
4.6.1 Content Recommendation Engine Market Concentration Rate
4.6.2 Mergers & Acquisitions, Expansion Plans
5 Company (Top Players) Profiles
5.1 Amazon Web Services (US)
5.1.1 Amazon Web Services (US) Profile
5.1.2 Amazon Web Services (US) Main Business
5.1.3 Amazon Web Services (US) Content Recommendation Engine Products, Services and Solutions
5.1.4 Amazon Web Services (US) Content Recommendation Engine Revenue (US$ Million) & (2018-2023)
5.1.5 Amazon Web Services (US) Recent Developments
5.2 Boomtrain
5.2.1 Boomtrain Profile
5.2.2 Boomtrain Main Business
5.2.3 Boomtrain Content Recommendation Engine Products, Services and Solutions
5.2.4 Boomtrain Content Recommendation Engine Revenue (US$ Million) & (2018-2023)
5.2.5 Boomtrain Recent Developments
5.3 Certona
5.3.1 Certona Profile
5.3.2 Certona Main Business
5.3.3 Certona Content Recommendation Engine Products, Services and Solutions
5.3.4 Certona Content Recommendation Engine Revenue (US$ Million) & (2018-2023)
5.3.5 Curata Recent Developments
5.4 Curata
5.4.1 Curata Profile
5.4.2 Curata Main Business
5.4.3 Curata Content Recommendation Engine Products, Services and Solutions
5.4.4 Curata Content Recommendation Engine Revenue (US$ Million) & (2018-2023)
5.4.5 Curata Recent Developments
5.5 Cxense
5.5.1 Cxense Profile
5.5.2 Cxense Main Business
5.5.3 Cxense Content Recommendation Engine Products, Services and Solutions
5.5.4 Cxense Content Recommendation Engine Revenue (US$ Million) & (2018-2023)
5.5.5 Cxense Recent Developments
5.6 Dynamic Yield
5.6.1 Dynamic Yield Profile
5.6.2 Dynamic Yield Main Business
5.6.3 Dynamic Yield Content Recommendation Engine Products, Services and Solutions
5.6.4 Dynamic Yield Content Recommendation Engine Revenue (US$ Million) & (2018-2023)
5.6.5 Dynamic Yield Recent Developments
5.7 IBM
5.7.1 IBM Profile
5.7.2 IBM Main Business
5.7.3 IBM Content Recommendation Engine Products, Services and Solutions
5.7.4 IBM Content Recommendation Engine Revenue (US$ Million) & (2018-2023)
5.7.5 IBM Recent Developments
5.8 Kibo Commerce
5.8.1 Kibo Commerce Profile
5.8.2 Kibo Commerce Main Business
5.8.3 Kibo Commerce Content Recommendation Engine Products, Services and Solutions
5.8.4 Kibo Commerce Content Recommendation Engine Revenue (US$ Million) & (2018-2023)
5.8.5 Kibo Commerce Recent Developments
5.9 Outbrain
5.9.1 Outbrain Profile
5.9.2 Outbrain Main Business
5.9.3 Outbrain Content Recommendation Engine Products, Services and Solutions
5.9.4 Outbrain Content Recommendation Engine Revenue (US$ Million) & (2018-2023)
5.9.5 Outbrain Recent Developments
5.10 Revcontent
5.10.1 Revcontent Profile
5.10.2 Revcontent Main Business
5.10.3 Revcontent Content Recommendation Engine Products, Services and Solutions
5.10.4 Revcontent Content Recommendation Engine Revenue (US$ Million) & (2018-2023)
5.10.5 Revcontent Recent Developments
5.11 Taboola
5.11.1 Taboola Profile
5.11.2 Taboola Main Business
5.11.3 Taboola Content Recommendation Engine Products, Services and Solutions
5.11.4 Taboola Content Recommendation Engine Revenue (US$ Million) & (2018-2023)
5.11.5 Taboola Recent Developments
5.12 ThinkAnalytics
5.12.1 ThinkAnalytics Profile
5.12.2 ThinkAnalytics Main Business
5.12.3 ThinkAnalytics Content Recommendation Engine Products, Services and Solutions
5.12.4 ThinkAnalytics Content Recommendation Engine Revenue (US$ Million) & (2018-2023)
5.12.5 ThinkAnalytics Recent Developments
6 North America
6.1 North America Content Recommendation Engine Market Size by Country (2018-2029)
6.2 U.S.
6.3 Canada
7 Europe
7.1 Europe Content Recommendation Engine Market Size by Country (2018-2029)
7.2 Germany
7.3 France
7.4 U.K.
7.5 Italy
7.6 Russia
7.7 Nordic Countries
7.8 Rest of Europe
8 Asia-Pacific
8.1 Asia-Pacific Content Recommendation Engine Market Size by Region (2018-2029)
8.2 China
8.3 Japan
8.4 South Korea
8.5 Southeast Asia
8.6 India
8.7 Australia
8.8 Rest of Asia-Pacific
9 Latin America
9.1 Latin America Content Recommendation Engine Market Size by Country (2018-2029)
9.2 Mexico
9.3 Brazil
9.4 Rest of Latin America
10 Middle East & Africa
10.1 Middle East & Africa Content Recommendation Engine Market Size by Country (2018-2029)
10.2 Turkey
10.3 Saudi Arabia
10.4 UAE
10.5 Rest of Middle East & Africa
11 Content Recommendation Engine Market Dynamics
11.1 Content Recommendation Engine Industry Trends
11.2 Content Recommendation Engine Market Drivers
11.3 Content Recommendation Engine Market Challenges
11.4 Content Recommendation Engine Market Restraints
12 Research Finding /Conclusion
13 Methodology and Data Source
13.1 Methodology/Research Approach
13.1.1 Research Programs/Design
13.1.2 Market Size Estimation
13.1.3 Market Breakdown and Data Triangulation
13.2 Data Source
13.2.1 Secondary Sources
13.2.2 Primary Sources
13.3 Disclaimer
13.4 Author List
Published By : QY Research
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