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Global Content Recommendation Engines Market Analysis and Forecast 2026-2032

Publisher APO Research, Inc.
Published Dec 29, 2025
Length 208 Pages
SKU # APRC20785481

Description

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 Includes

This report presents an overview of global market for Content Recommendation Engines, market size. Analyses of the global market trends, with historic market revenue data for 2021 - 2025, estimates for 2026, and projections of CAGR through 2032.

This report researches the key producers of Content Recommendation Engines, also provides the revenue of main regions and countries. Of the upcoming market potential for Content Recommendation Engines, and key regions or countries of focus to forecast this market into various segments and sub-segments. Country specific data and market value analysis for the U.S., Canada, Mexico, Brazil, China, Japan, South Korea, Southeast Asia, India, Germany, the U.K., Italy, Middle East, Africa, and Other Countries.

This report focuses on the Content Recommendation Engines revenue, market share and industry ranking of main manufacturers, data from 2021 to 2026. Identification of the major stakeholders in the global Content Recommendation Engines market, and analysis of their competitive landscape and market positioning based on recent developments and segmental revenues. This report will help stakeholders to understand the competitive landscape and gain more insights and position their businesses and market strategies in a better way.

This report analyzes the segments data by Type and by Application, revenue, and growth rate, from 2021 to 2032. Evaluation and forecast the market size for Content Recommendation Engines revenue, projected growth trends, production technology, application and end-user industry.


Content Recommendation Engines Segment by Company

Taboola
Outbrain
Dynamic Yield (McDonald)
Amazon Web Services
Adob​​e
Kibo Commerce
Optimizely
Salesforce (Evergage)
Zeta Global
Emarsys (SAP)
Algonomy
ThinkAnalytics
Alibaba Cloud
Tencent.
Baidu
Byte Dance

Content Recommendation Engines Segment by Deployment Mode
Local Deployment
Cloud Deployment

Content Recommendation Engines Segment by Application

News and Media
Entertainment and Games
E-commerce
Finance
others

Content Recommendation Engines Segment by Region

North America
United States
Canada
Mexico
Europe
Germany
France
U.K.
Italy
Russia
Spain
Netherlands
Switzerland
Sweden
Poland
Asia-Pacific
China
Japan
South Korea
India
Australia
Taiwan
Southeast Asia
South America
Brazil
Argentina
Chile
Middle East & Africa
Egypt
South Africa
Israel
Türkiye
GCC Countries

Study Objectives

1. To analyze and research the global status and future forecast, involving growth rate (CAGR), market share, historical and forecast.
2. To present the key players, revenue, market share, and Recent Developments.
3. To split the breakdown data by regions, type, manufacturers, and Application.
4. To analyze the global and key regions market potential and advantage, opportunity and challenge, restraints, and risks.
5. To identify significant trends, drivers, influence factors in global and regions.
6. To analyze competitive developments such as expansions, agreements, new product launches, and acquisitions in the market.

Reasons to Buy This Report

1. This report will help the readers to understand the competition within the industries and strategies for the competitive environment to enhance the potential profit. The report also focuses on the competitive landscape of the global Content Recommendation Engines market, and introduces in detail the market share, industry ranking, competitor ecosystem, market performance, new product development, operation situation, expansion, and acquisition. etc. of the main players, which helps the readers to identify the main competitors and deeply understand the competition pattern of the market.
2. This report will help stakeholders to understand the global industry status and trends of Content Recommendation Engines and provides them with information on key market drivers, restraints, challenges, and opportunities.
3. This report will help stakeholders to understand competitors better and gain more insights to strengthen their position in their businesses. The competitive landscape section includes the market share and rank (in market size), competitor ecosystem, new product development, expansion, and acquisition.
4. This report stays updated with novel technology integration, features, and the latest developments in the market.
5. This report helps stakeholders to gain insights into which regions to target globally.
6. This report helps stakeholders to gain insights into the end-user perception concerning the adoption of Content Recommendation Engines.
7. This report helps stakeholders to identify some of the key players in the market and understand their valuable contribution.

Chapter Outline

Chapter 1: Introduces the report scope of the report, executive summary of different market segments (product type, application, etc), including the market size of each market segment, future development potential, and so on. 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 2: Introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Revenue of Content Recommendation Engines in global and regional level. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 4: Detailed analysis of Content Recommendation Engines company competitive landscape, revenue, market share and industry ranking, latest development plan, merger, and acquisition information, etc.
Chapter 5: Provides the analysis of various market segments by type, covering the revenue, and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 6: Provides the analysis of various market segments by application, covering the revenue, and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 7: Provides profiles of key companies, introducing the basic situation of the main companies in the market in detail, including product descriptions and specifications, Content Recommendation Engines revenue, gross margin, and recent development, etc.
Chapter 8: North America by type, by application and by country, revenue for each segment.
Chapter 9: Europe by type, by application and by country, revenue for each segment.
Chapter 10: China type, by application, revenue for each segment.
Chapter 11: Asia (excluding China) type, by application and by region, revenue for each segment.
Chapter 12: South America, Middle East and Africa by type, by application and by country, revenue for each segment.
Chapter 13: The main concluding insights of the report.

Please Note: Single-User license will be delivered via PDF from the publisher without the rights to print or to edit.

Table of Contents

208 Pages
1 Market Overview
1.1 Product Definition
1.2 Content Recommendation Engines Market by Deployment Mode
1.2.1 Global Content Recommendation Engines Market Size by Deployment Mode, 2021 VS 2025 VS 2032
1.2.2 Local Deployment
1.2.3 Cloud Deployment
1.3 Content Recommendation Engines Market by Application
1.3.1 Global Content Recommendation Engines Market Size by Application, 2021 VS 2025 VS 2032
1.3.2 News and Media
1.3.3 Entertainment and Games
1.3.4 E-commerce
1.3.5 Finance
1.3.6 others
1.4 Assumptions and Limitations
1.5 Study Goals and Objectives
2 Content Recommendation Engines Market Dynamics
2.1 Content Recommendation Engines Industry Trends
2.2 Content Recommendation Engines Industry Drivers
2.3 Content Recommendation Engines Industry Opportunities and Challenges
2.4 Content Recommendation Engines Industry Restraints
3 Global Growth Perspective
3.1 Global Content Recommendation Engines Market Perspective (2021-2032)
3.2 Global Content Recommendation Engines Growth Trends by Region
3.2.1 Global Content Recommendation Engines Market Size by Region: 2021 VS 2025 VS 2032
3.2.2 Global Content Recommendation Engines Market Size by Region (2021-2026)
3.2.3 Global Content Recommendation Engines Market Size by Region (2027-2032)
4 Competitive Landscape by Players
4.1 Global Content Recommendation Engines Revenue by Players
4.1.1 Global Content Recommendation Engines Revenue by Players (2021-2026)
4.1.2 Global Content Recommendation Engines Revenue Market Share by Players (2021-2026)
4.1.3 Global Content Recommendation Engines Players Revenue Share Top 10 and Top 5 in 2025
4.2 Global Content Recommendation Engines Key Players Ranking, 2024 VS 2025 VS 2026
4.3 Global Content Recommendation Engines Key Players Headquarters & Area Served
4.4 Global Content Recommendation Engines Players, Product Type & Application
4.5 Global Content Recommendation Engines Players Establishment Date
4.6 Market Competitive Analysis
4.6.1 Global Content Recommendation Engines Market CR5 and HHI
4.6.3 2025 Content Recommendation Engines Tier 1, Tier 2, and Tier 3
5 Content Recommendation Engines Market Size by Type
5.1 Global Content Recommendation Engines Revenue by Type (2021 VS 2025 VS 2032)
5.2 Global Content Recommendation Engines Revenue by Type (2021-2032)
5.3 Global Content Recommendation Engines Revenue Market Share by Type (2021-2032)
6 Content Recommendation Engines Market Size by Application
6.1 Global Content Recommendation Engines Revenue by Application (2021 VS 2025 VS 2032)
6.2 Global Content Recommendation Engines Revenue by Application (2021-2032)
6.3 Global Content Recommendation Engines Revenue Market Share by Application (2021-2032)
7 Company Profiles
7.1 Taboola
7.1.1 Taboola Company Information
7.1.2 Taboola Business Overview
7.1.3 Taboola Content Recommendation Engines Revenue and Gross Margin (2021-2026)
7.1.4 Taboola Content Recommendation Engines Product Portfolio
7.1.5 Taboola Recent Developments
7.2 Outbrain
7.2.1 Outbrain Company Information
7.2.2 Outbrain Business Overview
7.2.3 Outbrain Content Recommendation Engines Revenue and Gross Margin (2021-2026)
7.2.4 Outbrain Content Recommendation Engines Product Portfolio
7.2.5 Outbrain Recent Developments
7.3 Dynamic Yield (McDonald)
7.3.1 Dynamic Yield (McDonald) Company Information
7.3.2 Dynamic Yield (McDonald) Business Overview
7.3.3 Dynamic Yield (McDonald) Content Recommendation Engines Revenue and Gross Margin (2021-2026)
7.3.4 Dynamic Yield (McDonald) Content Recommendation Engines Product Portfolio
7.3.5 Dynamic Yield (McDonald) Recent Developments
7.4 Amazon Web Services
7.4.1 Amazon Web Services Company Information
7.4.2 Amazon Web Services Business Overview
7.4.3 Amazon Web Services Content Recommendation Engines Revenue and Gross Margin (2021-2026)
7.4.4 Amazon Web Services Content Recommendation Engines Product Portfolio
7.4.5 Amazon Web Services Recent Developments
7.5 Adob​​e
7.5.1 Adob​​e Company Information
7.5.2 Adob​​e Business Overview
7.5.3 Adob​​e Content Recommendation Engines Revenue and Gross Margin (2021-2026)
7.5.4 Adob​​e Content Recommendation Engines Product Portfolio
7.5.5 Adob​​e Recent Developments
7.6 Kibo Commerce
7.6.1 Kibo Commerce Company Information
7.6.2 Kibo Commerce Business Overview
7.6.3 Kibo Commerce Content Recommendation Engines Revenue and Gross Margin (2021-2026)
7.6.4 Kibo Commerce Content Recommendation Engines Product Portfolio
7.6.5 Kibo Commerce Recent Developments
7.7 Optimizely
7.7.1 Optimizely Company Information
7.7.2 Optimizely Business Overview
7.7.3 Optimizely Content Recommendation Engines Revenue and Gross Margin (2021-2026)
7.7.4 Optimizely Content Recommendation Engines Product Portfolio
7.7.5 Optimizely Recent Developments
7.8 Salesforce (Evergage)
7.8.1 Salesforce (Evergage) Company Information
7.8.2 Salesforce (Evergage) Business Overview
7.8.3 Salesforce (Evergage) Content Recommendation Engines Revenue and Gross Margin (2021-2026)
7.8.4 Salesforce (Evergage) Content Recommendation Engines Product Portfolio
7.8.5 Salesforce (Evergage) Recent Developments
7.9 Zeta Global
7.9.1 Zeta Global Company Information
7.9.2 Zeta Global Business Overview
7.9.3 Zeta Global Content Recommendation Engines Revenue and Gross Margin (2021-2026)
7.9.4 Zeta Global Content Recommendation Engines Product Portfolio
7.9.5 Zeta Global Recent Developments
7.10 Emarsys (SAP)
7.10.1 Emarsys (SAP) Company Information
7.10.2 Emarsys (SAP) Business Overview
7.10.3 Emarsys (SAP) Content Recommendation Engines Revenue and Gross Margin (2021-2026)
7.10.4 Emarsys (SAP) Content Recommendation Engines Product Portfolio
7.10.5 Emarsys (SAP) Recent Developments
7.11 Algonomy
7.11.1 Algonomy Company Information
7.11.2 Algonomy Business Overview
7.11.3 Algonomy Content Recommendation Engines Revenue and Gross Margin (2021-2026)
7.11.4 Algonomy Content Recommendation Engines Product Portfolio
7.11.5 Algonomy Recent Developments
7.12 ThinkAnalytics
7.12.1 ThinkAnalytics Company Information
7.12.2 ThinkAnalytics Business Overview
7.12.3 ThinkAnalytics Content Recommendation Engines Revenue and Gross Margin (2021-2026)
7.12.4 ThinkAnalytics Content Recommendation Engines Product Portfolio
7.12.5 ThinkAnalytics Recent Developments
7.13 Alibaba Cloud
7.13.1 Alibaba Cloud Company Information
7.13.2 Alibaba Cloud Business Overview
7.13.3 Alibaba Cloud Content Recommendation Engines Revenue and Gross Margin (2021-2026)
7.13.4 Alibaba Cloud Content Recommendation Engines Product Portfolio
7.13.5 Alibaba Cloud Recent Developments
7.14 Tencent.
7.14.1 Tencent. Company Information
7.14.2 Tencent. Business Overview
7.14.3 Tencent. Content Recommendation Engines Revenue and Gross Margin (2021-2026)
7.14.4 Tencent. Content Recommendation Engines Product Portfolio
7.14.5 Tencent. Recent Developments
7.15 Baidu
7.15.1 Baidu Company Information
7.15.2 Baidu Business Overview
7.15.3 Baidu Content Recommendation Engines Revenue and Gross Margin (2021-2026)
7.15.4 Baidu Content Recommendation Engines Product Portfolio
7.15.5 Baidu Recent Developments
7.16 Byte Dance
7.16.1 Byte Dance Company Information
7.16.2 Byte Dance Business Overview
7.16.3 Byte Dance Content Recommendation Engines Revenue and Gross Margin (2021-2026)
7.16.4 Byte Dance Content Recommendation Engines Product Portfolio
7.16.5 Byte Dance Recent Developments
8 North America
8.1 North America Content Recommendation Engines Revenue (2021-2032)
8.2 North America Content Recommendation Engines Revenue by Deployment Mode (2021-2032)
8.2.1 North America Content Recommendation Engines Revenue by Deployment Mode (2021-2026)
8.2.2 North America Content Recommendation Engines Revenue by Deployment Mode (2027-2032)
8.3 North America Content Recommendation Engines Revenue Share by Deployment Mode (2021-2032)
8.4 North America Content Recommendation Engines Revenue by Application (2021-2032)
8.4.1 North America Content Recommendation Engines Revenue by Application (2021-2026)
8.4.2 North America Content Recommendation Engines Revenue by Application (2027-2032)
8.5 North America Content Recommendation Engines Revenue Share by Application (2021-2032)
8.6 North America Content Recommendation Engines Revenue by Country
8.6.1 North America Content Recommendation Engines Revenue by Country (2021 VS 2025 VS 2032)
8.6.2 North America Content Recommendation Engines Revenue by Country (2021-2026)
8.6.3 North America Content Recommendation Engines Revenue by Country (2027-2032)
8.6.4 United States
8.6.5 Canada
8.6.6 Mexico
9 Europe
9.1 Europe Content Recommendation Engines Revenue (2021-2032)
9.2 Europe Content Recommendation Engines Revenue by Deployment Mode (2021-2032)
9.2.1 Europe Content Recommendation Engines Revenue by Deployment Mode (2021-2026)
9.2.2 Europe Content Recommendation Engines Revenue by Deployment Mode (2027-2032)
9.3 Europe Content Recommendation Engines Revenue Share by Deployment Mode (2021-2032)
9.4 Europe Content Recommendation Engines Revenue by Application (2021-2032)
9.4.1 Europe Content Recommendation Engines Revenue by Application (2021-2026)
9.4.2 Europe Content Recommendation Engines Revenue by Application (2027-2032)
9.5 Europe Content Recommendation Engines Revenue Share by Application (2021-2032)
9.6 Europe Content Recommendation Engines Revenue by Country
9.6.1 Europe Content Recommendation Engines Revenue by Country (2021 VS 2025 VS 2032)
9.6.2 Europe Content Recommendation Engines Revenue by Country (2021-2026)
9.6.3 Europe Content Recommendation Engines Revenue by Country (2027-2032)
9.6.4 Germany
9.6.5 France
9.6.6 U.K.
9.6.7 Italy
9.6.8 Russia
9.6.9 Spain
9.6.10 Netherlands
9.6.11 Switzerland
9.6.12 Sweden
9.6.13 Poland
10 China
10.1 China Content Recommendation Engines Revenue (2021-2032)
10.2 China Content Recommendation Engines Revenue by Deployment Mode (2021-2032)
10.2.1 China Content Recommendation Engines Revenue by Deployment Mode (2021-2026)
10.2.2 China Content Recommendation Engines Revenue by Deployment Mode (2027-2032)
10.3 China Content Recommendation Engines Revenue Share by Deployment Mode (2021-2032)
10.4 China Content Recommendation Engines Revenue by Application (2021-2032)
10.4.1 China Content Recommendation Engines Revenue by Application (2021-2026)
10.4.2 China Content Recommendation Engines Revenue by Application (2027-2032)
10.5 China Content Recommendation Engines Revenue Share by Application (2021-2032)
11 Asia (Excluding China)
11.1 Asia Content Recommendation Engines Revenue (2021-2032)
11.2 Asia Content Recommendation Engines Revenue by Deployment Mode (2021-2032)
11.2.1 Asia Content Recommendation Engines Revenue by Deployment Mode (2021-2026)
11.2.2 Asia Content Recommendation Engines Revenue by Deployment Mode (2027-2032)
11.3 Asia Content Recommendation Engines Revenue Share by Deployment Mode (2021-2032)
11.4 Asia Content Recommendation Engines Revenue by Application (2021-2032)
11.4.1 Asia Content Recommendation Engines Revenue by Application (2021-2026)
11.4.2 Asia Content Recommendation Engines Revenue by Application (2027-2032)
11.5 Asia Content Recommendation Engines Revenue Share by Application (2021-2032)
11.6 Asia Content Recommendation Engines Revenue by Country
11.6.1 Asia Content Recommendation Engines Revenue by Country (2021 VS 2025 VS 2032)
11.6.2 Asia Content Recommendation Engines Revenue by Country (2021-2026)
11.6.3 Asia Content Recommendation Engines Revenue by Country (2027-2032)
11.6.4 Japan
11.6.5 South Korea
11.6.6 India
11.6.7 Australia
11.6.8 Taiwan
11.6.9 Southeast Asia
12 South America, Middle East and Africa
12.1 SAMEA Content Recommendation Engines Revenue (2021-2032)
12.2 SAMEA Content Recommendation Engines Revenue by Deployment Mode (2021-2032)
12.2.1 SAMEA Content Recommendation Engines Revenue by Deployment Mode (2021-2026)
12.2.2 SAMEA Content Recommendation Engines Revenue by Deployment Mode (2027-2032)
12.3 SAMEA Content Recommendation Engines Revenue Share by Deployment Mode (2021-2032)
12.4 SAMEA Content Recommendation Engines Revenue by Application (2021-2032)
12.4.1 SAMEA Content Recommendation Engines Revenue by Application (2021-2026)
12.4.2 SAMEA Content Recommendation Engines Revenue by Application (2027-2032)
12.5 SAMEA Content Recommendation Engines Revenue Share by Application (2021-2032)
12.6 SAMEA Content Recommendation Engines Revenue by Country
12.6.1 SAMEA Content Recommendation Engines Revenue by Country (2021 VS 2025 VS 2032)
12.6.2 SAMEA Content Recommendation Engines Revenue by Country (2021-2026)
12.6.3 SAMEA Content Recommendation Engines Revenue by Country (2027-2032)
12.6.4 Brazil
12.6.5 Argentina
12.6.6 Chile
12.6.7 Colombia
12.6.8 Peru
12.6.9 Saudi Arabia
12.6.10 Israel
12.6.11 UAE
12.6.12 Turkey
12.6.13 Iran
12.6.14 Egypt
13 Concluding Insights
14 Appendix
14.1 Reasons for Doing This Study
14.2 Research Methodology
14.3 Research Process
14.4 Authors List of This Report
14.5 Data Source
14.5.1 Secondary Sources
14.5.2 Primary Sources
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