Global Content Recommendation Engine Market Size study, by Component (Solution, Service), by Filtering Approach (Collaborative, Content-Based, Hybrid), by Vertical (E-Commerce, Media, Entertainment & Gaming, Retail, Hospitality, IT & Telecommunication, BFSI, Education & Training, Healthcare & Pharmaceutical, Others) and Regional Forecasts 2019-2026

Report Id

111209

Publisher Name

Bizwit Research & Consulting LLP

Published Date

15-May-19

No of Pages

200

Market Scenario

Global Content Recommendation Engine Market valued approximately USD 1.58 billion in 2018 is anticipated to grow with a CAGR of 33.72% over the forecasted period of 2019-2026. The content recommendation engine is a software that analyzes available data to make suggestions for something that a website user might be interested in, such as a book, a video or a job, among other possibilities. Content Recommendation Engine has enabled the corporate world to work smarter, faster as well as doing more with significantly less. Increasing focus on enhancing customer experience, rapid digitalization, and need for analyzing large volumes of customer data are factors driving the market across the globe. It is essential to understand that Content Recommendation Engine includes several minor technologies like deep learning, machine learning, robotics, etc. The regional analysis of Global Content Recommendation Engine Market is considered for the key regions such as Asia Pacific, North America, Europe, Latin America and Rest of the World. North America is the fastest growing region across the world in terms of market share. Whereas, owing to the countries such as China, Japan, and India, Asia Pacific region is anticipated to be the dominating region over the forecast period 2019-2026. The leading market players mainly include- IBM Amazon Web Services Revcontent Taboola Outbrain Cxense Dynamic Yield Curata The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below: By Component: Solution Service By Filtering Approach: Collaborative Content-Based Hybrid By Vertical: E-commerce Media, Entertainment & Gaming Retail Hospitality IT & Telecommunication BFSI Education & training Healthcare & Pharmaceutical Others By Regions: North America U.S. Canada Europe UK Germany Asia Pacific China India Japan Latin America Brazil Mexico Rest of the World Furthermore, years considered for the study are as follows: Historical year – 2016, 2017 Base year – 2018 Forecast period – 2019 to 2026 Target Audience of the Global Content Recommendation Engine Market in Market Study: Key Consulting Companies & Advisors Large, medium-sized, and small enterprises Venture capitalists Value-Added Resellers (VARs) Third-party knowledge providers Investment bankers Investors

Table of Contents

TABLE OF CONTENTS Chapter 1. Executive Summary 1.1. Market Snapshot 1.2. Key Trends 1.3. Global & Segmental Market Estimates & Forecasts, 2016-2026 (USD Billion) 1.3.1. Content Recommendation Engine Market, by Component, 2016-2026 (USD Billion) 1.3.2. Content Recommendation Engine Market, by Filtering Approach, 2016-2026 (USD Billion) 1.3.3. Content Recommendation Engine Market, by Vertical, 2016-2026 (USD Billion) 1.3.4. Content Recommendation Engine Market, by Region, 2016-2026 (USD Billion) 1.4. Estimation Methodology 1.5. Research Assumption Chapter 2. Global Content Recommendation Engine Market Definition and Scope 2.1. Objective of the Study 2.2. Market Definition & Scope 2.2.1. Industry Evolution 2.2.2. Scope of the Study 2.3. Years Considered for the Study 2.4. Currency Conversion Rates Chapter 3. Global Content Recommendation Engine Market Dynamics 3.1. See Saw Analysis 3.1.1. Market Drivers 3.1.2. Market Challenges 3.1.3. Market Opportunities Chapter 4. Global Content Recommendation Engine Market Industry Analysis 4.1. Porter’s 5 Force Model 4.1.1. Bargaining Power of Buyers 4.1.2. Bargaining Power of Suppliers 4.1.3. Threat of New Entrants 4.1.4. Threat of Substitutes 4.1.5. Competitive Rivalry 4.1.6. Futuristic Approach to Porter’s 5 Force Model 4.2. PEST Analysis 4.2.1. Political Scenario 4.2.2. Economic Scenario 4.2.3. Social Scenario 4.2.4. Technological Scenario 4.3. Key Buying Criteria 4.4. Regulatory Framework 4.5. Investment Vs Adoption Scenario 4.6. Analyst Recommendation & Conclusion Chapter 5. Global Content Recommendation Engine Market, by Component 5.1. Market Snapshot 5.2. Market Performance - Potential Model 5.3. Content Recommendation Engine Market, Sub Segment Analysis 5.3.1. Solution 5.3.1.1. Market estimates & forecasts, 2016-2026 (USD Billion) 5.3.1.2. Regional breakdown estimates & forecasts, 2016-2026 (USD Billion) 5.3.2. Service 5.3.2.1. Market estimates & forecasts, 2016-2026 (USD Billion) 5.3.2.2. Regional breakdown estimates & forecasts, 2016-2026 (USD Billion) Chapter 6. Global Content Recommendation Engine Market, by Filtering Approach 6.1. Market Snapshot 6.2. Market Performance - Potential Model 6.3. Content Recommendation Engine Market, Sub Segment Analysis 6.3.1. Collaborative 6.3.1.1. Market estimates & forecasts, 2016-2026 (USD Billion) 6.3.1.2. Regional breakdown estimates & forecasts, 2016-2026 (USD Billion) 6.3.2. Content-Based 6.3.2.1. Market estimates & forecasts, 2016-2026 (USD Billion) 6.3.2.2. Regional breakdown estimates & forecasts, 2016-2026 (USD Billion) 6.3.3. Hybrid 6.3.3.1. Market estimates & forecasts, 2016-2026 (USD Billion) 6.3.3.2. Regional breakdown estimates & forecasts, 2016-2026 (USD Billion) Chapter 7. Global Content Recommendation Engine Market, by Vertical 7.1. Market Snapshot 7.2. Market Performance - Potential Model 7.3. Content Recommendation Engine Market, Sub Segment Analysis 7.3.1. E-Commerce 7.3.1.1. Market estimates & forecasts, 2016-2026 (USD Billion) 7.3.1.2. Regional breakdown estimates & forecasts, 2016-2026 (USD Billion) 7.3.2. Media, Entertainment & Gaming 7.3.2.1. Market estimates & forecasts, 2016-2026 (USD Billion) 7.3.2.2. Regional breakdown estimates & forecasts, 2016-2026 (USD Billion) 7.3.3. Retail 7.3.3.1. Market estimates & forecasts, 2016-2026 (USD Billion) 7.3.3.2. Regional breakdown estimates & forecasts, 2016-2026 (USD Billion) 7.3.4. Hospitality 7.3.4.1. Market estimates & forecasts, 2016-2026 (USD Billion) 7.3.4.2. Regional breakdown estimates & forecasts, 2016-2026 (USD Billion) 7.3.5. IT & Telecommunication 7.3.5.1. Market estimates & forecasts, 2016-2026 (USD Billion) 7.3.5.2. Regional breakdown estimates & forecasts, 2016-2026 (USD Billion) 7.3.6. BFSI 7.3.6.1. Market estimates & forecasts, 2016-2026 (USD Billion) 7.3.6.2. Regional breakdown estimates & forecasts, 2016-2026 (USD Billion) 7.3.7. Education & Training 7.3.7.1. Market estimates & forecasts, 2016-2026 (USD Billion) 7.3.7.2. Regional breakdown estimates & forecasts, 2016-2026 (USD Billion) 7.3.8. Healthcare & Pharmaceutical 7.3.8.1. Market estimates & forecasts, 2016-2026 (USD Billion) 7.3.8.2. Regional breakdown estimates & forecasts, 2016-2026 (USD Billion) 7.3.9. Others 7.3.9.1. Market estimates & forecasts, 2016-2026 (USD Billion) 7.3.9.2. Regional breakdown estimates & forecasts, 2016-2026 (USD Billion) Chapter 8. Global Content Recommendation Engine Market, by Regional Analysis 8.1. Content Recommendation Engine Market, Regional Market Snapshot (2016-2026) 8.2. North America Content Recommendation Engine Market Snapshot 8.2.1. U.S. 8.2.1.1. Market estimates & forecasts, 2016-2026 (USD Billion) 8.2.1.2. Component breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.2.1.3. Filtering Approach breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.2.1.4. Vertical breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.2.2. Canada 8.2.2.1. Market estimates & forecasts, 2016-2026 (USD Billion) 8.2.2.2. Component breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.2.2.3. Filtering Approach breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.2.2.4. Vertical breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.3. Europe Content Recommendation Engine Market Snapshot 8.3.1. U.K. 8.3.1.1. Market estimates & forecasts, 2016-2026 (USD Billion) 8.3.1.2. Component breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.3.1.3. Filtering Approach breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.3.1.4. Vertical breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.3.2. Germany 8.3.2.1. Market estimates & forecasts, 2016-2026 (USD Billion) 8.3.2.2. Component breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.3.2.3. Filtering Approach breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.3.2.4. Vertical breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.3.3. Rest of Europe 8.3.3.1. Market estimates & forecasts, 2016-2026 (USD Billion) 8.3.3.2. Component breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.3.3.3. Filtering Approach breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.3.3.4. Vertical breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.4. Asia Content Recommendation Engine Market Snapshot 8.4.1. China 8.4.1.1. Market estimates & forecasts, 2016-2026 (USD Billion) 8.4.1.2. Component breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.4.1.3. Filtering Approach breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.4.1.4. Vertical breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.4.2. India 8.4.2.1. Market estimates & forecasts, 2016-2026 (USD Billion) 8.4.2.2. Component breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.4.2.3. Filtering Approach breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.4.2.4. Vertical breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.4.3. Japan 8.4.3.1. Market estimates & forecasts, 2016-2026 (USD Billion) 8.4.3.2. Component breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.4.3.3. Filtering Approach breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.4.3.4. Vertical breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.4.4. Rest of Asia Pacific 8.4.4.1. Market estimates & forecasts, 2016-2026 (USD Billion) 8.4.4.2. Component breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.4.4.3. Filtering Approach breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.4.4.4. Vertical breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.5. Latin America Content Recommendation Engine Market Snapshot 8.5.1. Brazil 8.5.1.1. Market estimates & forecasts, 2016-2026 (USD Billion) 8.5.1.2. Component breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.5.1.3. Filtering Approach breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.5.1.4. Vertical breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.5.2. Mexico 8.5.2.1. Market estimates & forecasts, 2016-2026 (USD Billion) 8.5.2.2. Component breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.5.2.3. Filtering Approach breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.5.2.4. Vertical breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.6. Rest of The World 8.6.1. South America 8.6.1.1. Market estimates & forecasts, 2016-2026 (USD Billion) 8.6.1.2. Component breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.6.1.3. Filtering Approach breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.6.1.4. Vertical breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.6.2. Middle East and Africa 8.6.2.1. Market estimates & forecasts, 2016-2026 (USD Billion) 8.6.2.2. Component breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.6.2.3. Filtering Approach breakdown estimates & forecasts, 2016-2026 (USD Billion) 8.6.2.4. Vertical breakdown estimates & forecasts, 2016-2026 (USD Billion) Chapter 9. Competitive Intelligence 9.1. Company Market Share (Subject to Data Availability) 9.2. Top Market Strategies 9.3. Company Profiles 9.3.1. IBM 9.3.1.1. Overview 9.3.1.2. Financial (Subject to Data Availability) 9.3.1.3. Product Summary 9.3.1.4. Recent Developments 9.3.2. Amazon Web Services 9.3.3. Revcontent 9.3.4. Taboola 9.3.5. Outbrain 9.3.6. Cxense 9.3.7. Dynamic Yield 9.3.8. Curata Chapter 10. Research Process 10.1. Research Process 10.1.1. Data Mining 10.1.2. Analysis 10.1.3. Market Estimation 10.1.4. Validation 10.1.5. Publishing 10.1.6. Research Assumption

Methodology

This research report involves complete picture of the market with the help of in-depth secondary and primary research. This research report studies several aspects of the market and analyze vital industry influencers. Extensive secondary research has been conducted using paid as well as open access data sources in order to gather information on the market and parent market. These key findings are then analyzed and validated with the help of in-house data models and primary discussions with key industry participants and experts across the value chain

research-methodology

Research Tools and Models

  • Top-Down Approach and Bottom-Up Approach
  • QFD Modeling for Market Size and Share Calculation
  • Regression, Variable and Impact Analysis
  • Penetration Modeling

Qualitative Research

  • It comprises briefing about market dynamics and business opportunities and strategies.
  • Finally, all the research findings are validated through interviews with in-house industry experts, freelance consultants and key opinion leaders etc.

Quantitative Research

It involves various mathematical tools, models, projection, and sampling techniques. It involves following steps:

  • Identification of market variables and market size derivation
  • Assessment of future prospects, opportunities and market penetration rates by analyzing product commercialization, regional trends etc.
  • Evaluation historical market trends and derivation of present and future year-on-year growth trends

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