Content Recommendation Engine Market

Content Recommendation Engine Market by Component (Solution, Service), Filtering Approach, Organization Size, Vertical (E-commerce, Media, Entertainment & Gaming, Retail & Consumer Goods, Hospitality), and Region - Global Forecast to 2022

Report Code: TC 6113 Mar, 2018, by marketsandmarkets.com

[128 Pages Report] The content recommendation engine market was valued at USD 1.04 Billion in 2016 and is expected to reach USD 4.95 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 33.7% during the forecast period. The base year considered for the study is 2016 and the forecast period is from 2017 to 2022. 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.

Objectives of the study:

  • To determine and forecast the global content recommendation engine market based on component, filtering approach, organization size, vertical, and region from 2017 to 2022 and analyze various macro- and microeconomic factors that affect market growth
  • To forecast the size of market segments with respect to 5 main regions, namely North America, Europe, Asia Pacific (APAC), Middle East & Africa (MEA), and Latin America
  • To provide detailed information regarding major factors, such as drivers, restraints, opportunities, and challenges influencing the growth of the content recommendation engine market
  • To strategically analyze each submarket with respect to individual growth trends, prospects, and contribution to the total content market
  • To analyze the opportunities in the market for stakeholders by identifying high-growth segments of the market
  • To profile key market players, provide comparative analysis based on business overviews, product offerings, regional presence, business strategies, and key financials with the help of in-house statistical tools to understand the competitive landscape
  • To track and analyze competitive developments, such as mergers & acquisitions, agreements & contracts, joint ventures, partnerships, and strategic alliances in the content recommendation engine market

The research methodology used to estimate and forecast the market size begins with obtaining data of key vendor revenues through secondary research such as annual reports, white papers, certified publications, databases, such as Factiva and Hoovers, press releases, and investor presentations of content recommendation engine vendors, as well as articles from recognized industry associations, statistics bureaus, and government publishing sources. Vendor offerings are also taken into consideration to determine the market segmentation. The bottom-up procedure has been employed to arrive at the overall global content recommendation engine market size from the revenues of key market players. After arriving at the overall market size, the total market was split into several segments and subsegments, which were then verified through primary research by conducting extensive interviews with key individuals, such as Chief Executive Officers (CEOs), Vice Presidents (VPs), directors, and executives. Data triangulation and market breakdown procedures were employed to complete the overall market engineering process and arrive at the exact statistics for all the segments and subsegments.

The breakdown of profiles of primary participants is depicted in the figure below:

Content Recommendation Engine Market

To know about the assumptions considered for the study, download the pdf brochure

Key players in the content recommendation engine market include IBM (US), Amazon Web Services (US), Cxense (Norway), Taboola (US), Outbrain (US), Revcontent (US), Kibo Commerce (US), Dynamic Yield (US), Curata (US), Boomtrain (US), ThinkAnalytics(UK), Certona (US), Recombee (Czech Republic), Uberflip (Canada), and Newzmate (US). These companies are adopting different growth strategies such as expansions, mergers & acquisitions, partnerships, and new product launches to increase their market shares in the market.

Key Target Audience

  • Providers of Content Recommendation Engine Services
  • Suppliers of IT Hardware/Software/Services
  • Software and System Integrators
  • IT Infrastructure Providers
  • Marketing Analytics Executives
  • System Administrators
  • App Developers
  • Third-Party Service Providers
  • Technology Providers

Scope of the Report

Report Metrics

Details

Market size available for years

2015-2022

Estimated year considered

2016

Forecast period

2017-2022

Forecast units

Value (USD)

Segments covered

Component(Solution, Service), Filtering Approach, Organization Size, Vertical, and Region

Geographies covered

North America, Europe, APAC, RoW

Companies covered

IBM (US), Amazon Web Services (US), Cxense (Norway), Taboola (US), Outbrain (US), Revcontent (US), Kibo Commerce (US), Dynamic Yield (US), Curata (US), Boomtrain (US), ThinkAnalytics(UK), Certona (US), Recombee (Czech Republic), Uberflip (Canada), and Newzmate (US).

The research report categorizes the market to forecast the revenues and analyze the trends in each of the following subsegments:

Content Recommendation Engine Market by Component:

  • Solution
  • Service

Content Recommendation Engine Market by Filtering Approach:

  • Collaborative Filtering
  • Content-based Filtering
  • Hybrid Filtering

Content Recommendation Engine Market by Organization size:

  • Large Enterprises
  • Small and Medium Enterprises

Content Recommendation Engine Market by Vertical

  • E-commerce
  • Media, Entertainment & Gaming
  • Retail & Consumer Goods
  • Hospitality
  • IT & Telecommunication
  • BFSI
  • Education & Training
  • Healthcare & Pharmaceutical
  • Others (Manufacturing, Automotive, and Supply Chain Management) 

Content Recommendation Engine Market by Region

  • North America
  • Europe
  • Asia Pacific
  • Middle East & Africa
  • Latin America

Available Customizations

Along with the given market data, MarketsandMarkets offers customization as per the company’s specific requirements. The following customization options are available for the report:

Geographic Analysis

  • Further country-level breakdown of the North America content recommendation engine market
  • Further country-level breakdown of the Europe market
  • Further country-level breakdown of the Asia Pacific market
  • Further country-level breakdown of the Middle East & Africa market
  • Further country-level breakdown of the Latin America market

Company Information

  • Detailed analysis and profiles of additional market players

Among components, the service segment of the market is projected to grow at the highest CAGR during the forecast period. The high growth of the service segment can be attributed to the growing need to deploy development services, consulting services, implementation services, training services, support services, and others. The solution segment is expected to lead the market during the forecast period.

Based on organization size, the small and medium enterprises segment of the content recommendation engine market is projected to grow at the highest CAGR during the forecast period. The growth of this segment of the market can be attributed to the increased adoption of content recommendation engine by small and medium enterprises, as these solutions help enterprises obtain benefits, such as keeping track of a number of users viewing and searching their products and services. The large enterprises segment is projected to lead the market during the forecast period.

Based on vertical, the E-commerce segment is projected to lead the content recommendation engine market during the forecast period. The growth of the E-commerce segment of the market can be attributed to the rise in the use of mobile applications and websites to order products and services online. This retail & consumer goods segment of the market is projected to grow at the highest CAGR during the forecast period.

The Asia Pacific market is projected to grow at the highest CAGR from 2017 to 2022. The growth of the Asia Pacific market can be attributed to the rise in Over the Top (OTT) players and rapid digitization, which is expected to lead to the increasing deployment of content recommendation engine in the region. The market in China, Japan, India, Australia, Indonesia, and Korea is projected to witness significant growth during the forecast period, owing to the increase in the number of mobile users and investments made by various companies for deploying content recommendation engine.

Content Recommendation Engine Market

The factor restraining the growth of the content recommendation engine market is the need to protect the sensitive information of the customers in content recommendation engine, and the use of this technology could lead hackers to breach systems and access the source code.

To speak to our analyst for a discussion on the above findings, click Speak to Analyst

Table of Contents

1 Introduction (Page No. - 14)
    1.1 Objectives of the Study
    1.2 Market Definition
    1.3 Market Scope
           1.3.1 Market Segmentation
    1.4 Years Considered for the Study
    1.5 Currency
    1.6 Stakeholders

2 Research Methodology (Page No. - 17)
    2.1 Research Data
           2.1.1 Secondary Data
           2.1.2 Primary Data
                    2.1.2.1 Breakdown of Primaries
                    2.1.2.2 Key Industry Insights
    2.2 Data Triangulation
    2.3 Market Size Estimation
    2.4 Research Assumptions
    2.5 Limitations

3 Executive Summary (Page No. - 24)

4 Premium Insights (Page No. - 29)
    4.1 Attractive Opportunities in the Content Recommendation Engine Market
    4.2 North America Market By Component
    4.3 Europe Market By Organization Size
    4.4 Asia Pacific Market By Vertical
    4.5 Content Recommendation Engine Market By Top 3 Verticals and Top 3 Regions

5 Market Dynamics and Industry Trends (Page No. - 33)
    5.1 Market Dynamics
           5.1.1 Drivers
                    5.1.1.1 Increasing Focus of Companies on Enhancing Customer Experience
                    5.1.1.2 Ongoing Digitalization Across the Globe
                    5.1.1.3 Increasing Requirement of Organizations to Analyze Large Volumes of Customer Data for Valuable Insights
           5.1.2 Restraints
                    5.1.2.1 Protecting Sensitive Information of Customers
           5.1.3 Opportunities
                    5.1.3.1 Growing Use of Artificial Intelligence in Content Recommendation Engines to Offer Personalized Customer Experience
                    5.1.3.2 Increasing Demand for Personalized Recommendations
           5.1.4 Challenges
                    5.1.4.1 Issues Related to Technology and Infrastructural Compatibilities
                    5.1.4.2 Lack of Technical Expertise
    5.2 Industry Trends
           5.2.1 Introduction
           5.2.2 Phases of Personalization of Information
           5.2.3 Filtering Approaches in Content Recommendation Engines
           5.2.4 Case Studies
                    5.2.4.1 Case Study 1: InnoGames Uses Outbrain Targeting Tools to Reach the Audience and Ensure an Increase in App Downloads
                    5.2.4.2 Case Study 2: Huggies Effectively Engages Target Audience With the Help of Outbrain Content Discovery Platform

6 Market By Component (Page No. - 42)
    6.1 Introduction
    6.2 Solution
    6.3 Service

7 Content Recommendation Engine Market By Filtering Approach (Page No. - 46)
    7.1 Introduction
    7.2 Collaborative Filtering
    7.3 Content-Based Filtering
    7.4 Hybrid Filtering

8 Content Recommendation Engine Market By Organization Size (Page No. - 48)
    8.1 Introduction
    8.2 Small and Medium Enterprises
    8.3 Large Enterprises

9 Content Recommendation Engine Market By Vertical (Page No. - 52)
    9.1 Introduction
    9.2 E-Commerce
    9.3 Media, Entertainment, and Gaming
    9.4 Retail & Consumer Goods
    9.5 Hospitality
    9.6 IT & Telecommunication
    9.7 BFSI
    9.8 Education & Training
    9.9 Healthcare & Pharmaceutical
    9.10 Others

10 Regional Analysis (Page No. - 62)
     10.1 Introduction
     10.2 North America
     10.3 Europe
     10.4 Asia Pacific
     10.5 Middle East & Africa
     10.6 Latin America

11 Competitive Landscape (Page No. - 83)
     11.1 Overview
     11.2 Competitive Situation and Trends
             11.2.1 New Product Launches & Product Enhancements
             11.2.2 Agreements, Collaborations, Partnerships, Contracts, and Alliances
             11.2.3 Acquisitions
             11.2.4 Expansions
     11.3 Ranking of Key Players of the Content Recommendation Engine Market in 2017

12 Company Profiles (Page No. - 89)
     12.1 IBM
(Business Overview, Products, Solutions, & Services, Key Insights, Recent Developments, SWOT Analysis, MnM View)*
     12.2 Amazon Web Services
     12.3 Revcontent
     12.4 Taboola
     12.5 Outbrain
     12.6 Cxense
     12.7 Dynamic Yield
     12.8 Curata
     12.9 Boomtrain
     12.10 Thinkanalytics
     12.11 Kibo Commerce
     12.12 Certona
*Details on Business Overview, Products, Solutions, & Services, Key Insights, Recent Developments, SWOT Analysis, MnM View Might Not Be Captured in Case of Unlisted Companies.
     12.13 Key Innovators
             12.13.1 Recombee
             12.13.2 Uberflip
             12.13.3 Newzmate

13 Appendix (Page No. - 121)
     13.1 Industry Excerpts
     13.2 Discussion Guide
     13.3 Knowledge Store: MarketsandMarkets’ Subscription Portal
     13.4 Available Customizations
     13.5 Related Reports
     13.6 Author Details

List of Tables (67 Tables)

Table 1 Content Recommendation Engine Market Size, By Component, 2015–2022 (USD Million)
Table 2 Solution: Market Size By Region, 2015–2022 (USD Million)
Table 3 Service: Market Size By Region, 2015–2022 (USD Million)
Table 4 Content Recommendation Engine Market Size, By Organization Size, 2015–2022 (USD Million)
Table 5 Small and Medium Enterprises: Market Size By Region, 2015–2022 (USD Million)
Table 6 Large Enterprises: Market Size By Region, 2015–2022 (USD Million)
Table 7 Content Recommendation Engine Market Size, By Vertical, 2015–2022 (USD Million)
Table 8 E-Commerce: Market Size By Region, 2015–2022 (USD Million)
Table 9 Media, Entertainment, and Gaming: Market Size By Region, 2015–2022 (USD Million)
Table 10 Retail & Consumer Goods: Market Size By Region, 2015–2022 (USD Million)
Table 11 Hospitality: Market Size By Region, 2015–2022 (USD Million)
Table 12 IT & Telecommunication: Market Size By Region, 2015–2022 (USD Million)
Table 13 BFSI: Market Size By Region, 2015–2022 (USD Million)
Table 14 Education & Training: Market Size By Region, 2015–2022 (USD Million)
Table 15 Healthcare & Pharmaceutical: Market Size By Region, 2015–2022 (USD Million)
Table 16 Others: Market Size By Region, 2015–2022 (USD Million)
Table 17 Content Recommendation Engine Market Size, By Region, 2015–2022 (USD Million)
Table 18 North America: Content Recommendation Engine Market Size By Component, 2015–2022 (USD Million)
Table 19 North America: Market Size By Organization Size, 2015–2022 (USD Million)
Table 20 North America: Market Size By Vertical, 2015–2022 (USD Million)
Table 21 North America: Market for E-Commerce, By Component, 2015–2022 (USD Million)
Table 22 North America: Market for Media, Entertainment, and Gaming, By Component, 2015–2022 (USD Million)
Table 23 North America: Market for Retail & Consumer Goods, By Component, 2015–2022 (USD Million)
Table 24 North America: Market for Hospitality, By Component, 2015–2022 (USD Million)
Table 25 North America: Market for IT & Telecommunication, By Component, 2015–2022 (USD Million)
Table 26 North America: Market for BFSI, By Component, 2015–2022 (USD Million)
Table 27 Europe: Content Recommendation Engine Market Size, By Component, 2015–2022 (USD Million)
Table 28 Europe: Market Size By Organization Size, 2015–2022 (USD Million)
Table 29 Europe: Market Size By Vertical, 2015–2022 (USD Million)
Table 30 Europe: Market for E-Commerce, By Component, 2015–2022 (USD Million)
Table 31 Europe: Market for Media, Entertainment, and Gaming, By Component, 2015–2022 (USD Million)
Table 32 Europe: Market for Retail & Consumer Goods, By Component, 2015–2022 (USD Million)
Table 33 Europe: Market for Hospitality, By Component, 2015–2022 (USD Million)
Table 34 Europe: Market for IT & Telecommunication, By Component, 2015–2022 (USD Million)
Table 35 Europe: Market for BFSI, By Component, 2015–2022 (USD Million)
Table 36 Asia Pacific: Content Recommendation Engine Market Size, By Component, 2015–2022 (USD Million)
Table 37 Asia Pacific: Market Size By Organization Size, 2015–2022 (USD Million)
Table 38 Asia Pacific: Market Size By Vertical, 2015–2022 (USD Million)
Table 39 Asia Pacific: Market for E-Commerce, By Component, 2015–2022 (USD Million)
Table 40 Asia Pacific: Market for Media, Entertainment, and Gaming, By Component, 2015–2022 (USD Million)
Table 41 Asia Pacific: Market for Retail & Consumer Goods, By Component, 2015–2022 (USD Million)
Table 42 Asia Pacific: Market for Hospitality, By Component, 2015–2022 (USD Million)
Table 43 Asia Pacific: Market for IT & Telecommunication, By Component, 2015–2022 (USD Million)
Table 44 Asia Pacific: Market for BFSI, By Component, 2015–2022 (USD Million)
Table 45 Middle East & Africa: Content Recommendation Engine Market, By Component, 2015–2022 (USD Million)
Table 46 Middle East & Africa: Market Size By Organization Size, 2015–2022 (USD Million)
Table 47 Middle East & Africa: Market Size By Vertical, 2015–2022 (USD Million)
Table 48 Middle East & Africa: Market for E-Commerce, By Component, 2015–2022 (USD Million)
Table 49 Middle East & Africa: Market for Media, Entertainment, and Gaming, By Component, 2015–2022 (USD Million)
Table 50 Middle East & Africa: Market for Retail & Consumer Goods, By Component, 2015–2022 (USD Million)
Table 51 Middle East & Africa: Market for Hospitality, By Component, 2015–2022 (USD Million)
Table 52 Middle East & Africa: Market for IT & Telecommunication, By Component, 2015–2022 (USD Million)
Table 53 Middle East & Africa: Market for BFSI, By Component, 2015–2022 (USD Million)
Table 54 Latin America: Content Recommendation Engine Market Size, By Component, 2015–2022 (USD Million)
Table 55 Latin America: Market Size By Organization Size, 2015–2022 (USD Million)
Table 56 Latin America: Market Size By Vertical, 2015–2022 (USD Million)
Table 57 Latin America: Market for E-Commerce, By Component, 2015–2022 (USD Million)
Table 58 Latin America: Market for Media, Entertainment, and Gaming, By Component, 2015–2022 (USD Million)
Table 59 Latin America: Market for Retail & Consumer Goods, By Component, 2015–2022 (USD Million)
Table 60 Latin America: Market for Hospitality, By Component, 2015–2022 (USD Million)
Table 61 Latin America: Market for IT & Telecommunication, By Component, 2015–2022 (USD Million)
Table 62 Latin America: Market for BFSI, By Component, 2015–2022 (USD Million)
Table 63 Market Evaluation Framework
Table 64 New Product Launches & Product Enhancements, May 2017–January 2018
Table 65 Agreements, Collaborations, Partnerships, Contracts, and Alliances, July 2017–January 2018
Table 66 Acquisitions, June 2017–July 2017
Table 67 Expansions, May 2015–June 2018

List of Figures (33 Figures)

Figure 1 Content Recommendation Engine Market: Research Design
Figure 2 Market Size Estimation Methodology: Bottom-Up Approach
Figure 3 Market Size Estimation Methodology: Top-Down Approach
Figure 4 Content Recommendation Engine Market By Component, 2017 & 2022 (USD Million)
Figure 5 Content Recommendation Engine Market By Organization Size, 2017 & 2022 (USD Million)
Figure 6 Content Recommendation Engine Market Share, By Vertical, 2017 (%)
Figure 7 Content Recommendation Engine Market By Region, 2017 & 2022 (USD Million)
Figure 8 Asia Pacific Content Recommendation Engine Market is Projected to Grow at the Highest CAGR From 2017 to 2022
Figure 9 Increasing Focus of Companies on Enhancing Customer Experience is Driving the Growth of the Content Recommendation Engine Market
Figure 10 Service Segment of the North America Market is Projected to Grow at A Higher CAGR Than Solution Segment From 2017 to 2022
Figure 11 Small and Medium Enterprises Segment of the Europe Market is Projected to Grow at A Higher CAGR Than Large Enterprises Segment From 2017 to 2022
Figure 12 Retail & Consumer Goods Segment of the Asia Pacific Market is Projected to Grow at the Highest CAGR From 2017 to 2022
Figure 13 North America is Expected to Lead the Market in 2017
Figure 14 Content Recommendation Engine Market: Drivers, Restraints, Opportunities, and Challenges
Figure 15 Phases of Personalization of Information Carried Out By Content Recommendation Engines
Figure 16 Content Recommendation Engines: Filtering Approaches
Figure 17 Service Segment is Estimated to Grow at A Higher CAGR as Compared to Solution Segment From 2017 to 2022
Figure 18 Large Enterprises Segment is Expected to Lead the Content Recommendation Engine Market in 2017
Figure 19 Retail & Consumer Goods Segment of the Market is Projected to Grow at the Highest CAGR From 2017 to 2022
Figure 20 North America is Projected to Lead the Market in 2017
Figure 21 Content Recommendation Engine Market in Asia Pacific and Latin America are Projected to Grow at High Rates From 2017 to 2022
Figure 22 North America Market Snapshot
Figure 23 Asia Pacific Market Snapshot
Figure 24 Companies Adopted Agreements, Collaborations, and Partnerships as Key Growth Strategies Between May 2015 and January 2018
Figure 25 Ranking of Key Players in the Content Recommendation Engine Market, 2017
Figure 26 IBM: Company Snapshot
Figure 27 IBM: SWOT Analysis
Figure 28 Amazon Web Services: Company Snapshot
Figure 29 Amazon Web Services: SWOT Analysis
Figure 30 Revcontent: SWOT Analysis
Figure 31 Taboola: SWOT Analysis
Figure 32 Outbrain: SWOT Analysis
Figure 33 Cxense: Company Snapshot


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Report Code
TC 6113
Published ON
Mar, 2018
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