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

コンテンツ・リコメンデーション・エンジンの世界市場予測(~2022年)

◆タイトル: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
◆商品コード:TC-6113
◆調査・発行会社:MarketsandMarkets
◆発行日:2018年3月21日
◆ページ数:127
◆レポート形式:PDF / 英語
◆納品方法:Eメール(受注後24時間以内)
◆調査対象地域:グローバル
◆産業分野:IT
◆販売価格オプション(消費税別)
Single User(1名利用)USD5,650 ⇒換算¥632,800見積依頼/購入/質問フォーム
Multi User (Five User)USD6,650 ⇒換算¥744,800見積依頼/購入/質問フォーム
Corporate License (全社内共有可)USD8,150 ⇒換算¥912,800見積依頼/購入/質問フォーム
販売価格オプションの説明はこちらでご利用ガイドはこちらでご確認いただけます。
※お支払金額は「換算金額(日本円)+消費税+配送料(Eメール納品は無料)」です。
※Eメールによる納品の場合、通常ご注文当日~2日以内に納品致します。
※商品の納品後、納品日+5日以内に請求書を発行し、お客様宛に郵送いたしますので、請求書発行日より2ヶ月以内に銀行振込にて支払をお願いします。(振込先:三菱東京UFJ銀行/京橋支店/H&Iグローバルリサーチ株式会社)
※上記の日本語題名はH&Iグローバルリサーチが翻訳したものです。英語版原本には日本語表記はありません。
※為替レートは適宜修正・更新しております。リアルタイム更新ではありません。
※ご購入後、レポートに記載の英語表現や単語の意味に関しましては無料でお答えいたします。(但し、対応範囲は弊社で判断)
※弊社H&Iグローバルリサーチ株式会社はMarketsandMarketsの日本における正規販売代理店です。

【レポートの概要】

MarketsandMarketsが発行した当調査レポートでは、コンテンツ・リコメンデーション・エンジンの世界市場について調査・分析し、エグゼクティブサマリー、市場インサイト、市場概観/市場動向、産業動向、構成要素別分析、フィルタリングアプローチ別分析、企業規模別分析、産業別分析、コンテンツ・リコメンデーション・エンジンの世界市場規模及び予測、市場動向、競争状況、関連企業分析などの情報をお届けいたします。

Increasing focus on enhancing customer experience and rapid digitalization are factors that are expected to drive the content recommendation engine market.The content recommendation engine market is projected to grow from USD 1.16 billion in 2017 to USD 4.95 billion by 2022, at a Compound Annual Growth Rate (CAGR) of 33.7% during the forecast period. Factors, such as increased focus on enhancing customer experience, rapid digitalization, and need for analyzing large volumes of customer data are expected to drive the content recommendation engine market. Protecting sensitive information of customers is a key factor restraining the growth of the market.
Based on component, the solution segment is estimated to lead the content recommendation engine market in 2017.
Based on component, the solution segment is estimated to lead the content recommendation engine market in 2017, as enterprises use it as a targeted marketing tool in their email campaigns and on their websites to enhance the ROI through effective customer engagement. Enterprises are increasingly deploying content recommendation system due to various benefits, such as enhanced customer satisfaction through the personalized online shopping experience.
Based on vertical, the E-commerce segment is estimated to lead the content recommendation engine market in 2017.
Based on vertical, the E-commerce segment is estimated to lead the content recommendation engine market in 2017. Increasing Internet penetration, the rise in the number of smartphones users, and the explosion of digital data have enabled organizations in E-commerce vertical to adopt content recommendation engine and enhance user experience.
The Asia Pacific content recommendation engine market is expected to grow at the highest CAGR during the forecast period.
The content recommendation engine market has been studied for North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America. The content recommendation engine is being adopted in the Asia Pacific region. Factors such as the rise of Over the Top (OTT) players and rapid digitization are expected to lead to the increasing deployment of content recommendation engine platforms in the Asia Pacific region. The demand for content recommendation engine solution in small and medium enterprises in the Asia Pacific region is high.
In-depth interviews were conducted with Chief Executive Officers (CEOs), marketing directors, innovation and technology directors, and executives from various key organizations operating in the content recommendation engine marketplace.
 By Company Type: Tier 1: 14%, Tier 2: 43%, and Tier 3: 43%
 By Designation: C-Level: 37%, Director Level: 13%, and Others: 50%
 By Region: North America: 37%, Europe: 25%, Asia Pacific: 25%, and Rest of the World: 13%
Key vendors profiled in the report are:
1. Amazon Web Services (US)
2. Boomtrain (US)
3. Certona (US)
4. Curata (US)
5. Cxense (Norway)
6. Dynamic Yield (US)
7. IBM (US)
8. Kibo Commerce (US)
9. Outbrain (US)
10. Revcontent (US)
11. Taboola (US)
12. ThinkAnalytics (UK)
Research Coverage
The content recommendation engine market has been segmented on the basis of component, filtering approach, organization size, vertical, and region. Based on component, the content recommendation engine market has been segmented into solution and service. Based on filtering approach, the market has been segmented into collaborative filtering, content-based filtering, and hybrid filtering. The content recommendation engine market has been segmented based on organization size into large enterprises and small and medium enterprises. Based on vertical, the market has been segmented into E-commerce, media, entertainment & gaming, retail & consumer goods, hospitality, IT & telecommunication, BFSI, education & training, healthcare & pharmaceutical, and others (which includes manufacturing, automotive, and supply chain management). The content recommendation engine market has been studied for North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America.
Key Benefits of Buying the Report:

The report will help market leaders and new entrants in the content recommendation engine market in the following ways:
The report will help market leaders/new entrants in this market by providing them the closest approximations of revenues of the content recommendation engine market and its subsegments. This report will also help stakeholders better understand the competitor landscape, gain more insights to position their businesses better, and implement suitable go-to-market strategies. The report will help stakeholders understand the pulse of the market and provide them with information on key market drivers, restraints, challenges, and opportunities.

【レポートの目次】

TABLE OF CONTENTS

1 INTRODUCTION 13
1.1 OBJECTIVES OF THE STUDY 13
1.2 MARKET DEFINITION 13
1.3 MARKET SCOPE 14
1.3.1 YEARS CONSIDERED FOR THE STUDY 15
1.4 CURRENCY 15
1.5 STAKEHOLDERS 15
2 RESEARCH METHODOLOGY 16
2.1 RESEARCH DATA 16
2.1.1 SECONDARY DATA 17
2.1.2 PRIMARY DATA 17
2.1.2.1 Breakdown of primaries 17
2.1.2.2 Key industry insights 18
2.2 MARKET SIZE ESTIMATION 19
2.3 RESEARCH ASSUMPTIONS 21
2.4 LIMITATIONS 21
3 EXECUTIVE SUMMARY 22
4 PREMIUM INSIGHTS 26
4.1 ATTRACTIVE OPPORTUNITIES IN THE CONTENT RECOMMENDATION ENGINE MARKET 26
4.2 NORTH AMERICA: CONTENT RECOMMENDATION ENGINE MARKET, BY COMPONENT 26
4.3 EUROPE: CONTENT RECOMMENDATION ENGINE MARKET, BY ORGANIZATION SIZE 27
4.4 ASIA PACIFIC: CONTENT RECOMMENDATION ENGINE MARKET, BY VERTICAL 27
4.5 CONTENT RECOMMENDATION ENGINE MARKET, BY TOP THREE VERTICALS & TOP THREE REGIONS 28
5 MARKET DYNAMICS AND INDUSTRY TRENDS 29
5.1 MARKET DYNAMIC 29
5.1.1 INTRODUCTION 29
5.1.2 DRIVERS 30
5.1.2.1 Increasing focus on enhancing customer experience 30
5.1.2.2 Rapid digitalization 30
5.1.2.3 Increasing need for analyzing large volumes of customer data 30
5.1.3 RESTRAINTS 31
5.1.3.1 Protecting sensitive information of customers 31
5.1.4 OPPORTUNITIES 31
5.1.4.1 Growing use of AI in recommendation engine to offer personalized customer experience 31
5.1.4.2 Increasing demand for personalization 32
5.1.5 CHALLENGES 32
5.1.5.1 Issues related to technology and infrastructural compatibilities 32
5.1.5.2 Lack of technical expertise 32
5.2 INDUSTRY TRENDS 33
5.2.1 INTRODUCTION 33
5.2.2 PHASES OF PERSONALIZATION 33
5.2.3 FILTERING APPROACHES IN RECOMMENDATION ENGINE 35
5.2.4 CASE STUDIES 36
5.2.4.1 Case study 1: InnoGames uses Outbrain targeting tools to reach audience and ensure App download growth 36
5.2.4.2 Case study 2: Huggies effectively engages target audience with the help of Outbrain Content Discovery Platform 37
6 CONTENT RECOMMENDATION ENGINE MARKET, BY COMPONENT 38
6.1 INTRODUCTION 39
6.2 SOLUTION 40
6.3 SERVICE 41
7 CONTENT RECOMMENDATION ENGINE MARKET, BY FILTERING APPROACH 42
7.1 INTRODUCTION 42
7.2 COLLABORATIVE FILTERING 42
7.3 CONTENT-BASED FILTERING 42
7.4 HYBRID FILTERING 43
8 CONTENT RECOMMENDATION ENGINE MARKET, BY ORGANIZATION SIZE 44
8.1 INTRODUCTION 45
8.2 SMALL AND MEDIUM ENTERPRISES 46
8.3 LARGE ENTERPRISES 47
9 CONTENT RECOMMENDATION ENGINE MARKET, BY VERTICAL 48
9.1 INTRODUCTION 49
9.2 E-COMMERCE 50
9.3 MEDIA, ENTERTAINMENT & GAMING 51
9.4 RETAIL & CONSUMER GOODS 52
9.5 HOSPITALITY 53
9.6 IT & TELECOMMUNICATION 54
9.7 BFSI 54
9.8 EDUCATION & TRAINING 55
9.9 HEALTHCARE & PHARMACEUTICAL 56
9.10 OTHERS 57
10 REGIONAL ANALYSIS 58
10.1 INTRODUCTION 59
10.2 NORTH AMERICA 60
10.3 EUROPE 65
10.4 ASIA PACIFIC 68
10.5 MIDDLE EAST & AFRICA 73
10.6 LATIN AMERICA 76
11 COMPETITIVE LANDSCAPE 80
11.1 OVERVIEW 80
11.2 COMPETITIVE SITUATION AND TRENDS 81
11.2.1 NEW PRODUCT LAUNCHES & PRODUCT ENHANCEMENTS 82
11.2.2 AGREEMENTS, COLLABORATIONS & PARTNERSHIPS 83
11.2.3 ACQUISITIONS 84
11.2.4 EXPANSIONS 85
11.3 MARKET RANKING OF KEY PLAYERS 85
12 COMPANY PROFILES 86
(Business overview, Products/Solutions/Services Offered, Recent Developments, SWOT analysis, MNM view)*
12.1 IBM 86
12.2 AMAZON WEB SERVICES 89
12.3 REVCONTENT 91
12.4 TABOOLA 97
12.5 OUTBRAIN 100
12.6 CXENSE 102
12.7 DYNAMIC YIELD 105
12.8 CURATA 107
12.9 BOOMTRAIN 108
12.10 THINKANALYTICS 110
12.11 KIBO COMMERCE 112
12.12 CERTONA 114
12.13 KEY INNOVATORS 116
12.13.1 RECOMBEE 116
12.13.2 UBERFLIP 116
12.13.3 NEWZMATE 116
*Details on Business overview, Products/Solutions/Services Offered, Recent Developments, SWOT analysis, MNM view might not be captured in case of unlisted companies.

13 APPENDIX 117
13.1 INDUSTRY EXCERPTS 117
13.2 DISCUSSION GUIDE 118
13.3 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 121
13.4 INTRODUCING RT: REAL-TIME MARKET INTELLIGENCE 123
13.5 AVAILABLE CUSTOMIZATIONS 124
13.6 RELATED REPORTS 124
13.7 AUTHOR DETAILS 125

LIST OF TABLES

TABLE 1 CONTENT RECOMMENDATION ENGINE MARKET SIZE, BY COMPONENT,
2015-2022 (USD MILLION) 39
TABLE 2 SOLUTION: CONTENT RECOMMENDATION ENGINE MARKET SIZE, BY REGION, 2015-2022 (USD MILLION) 40
TABLE 3 SERVICE: CONTENT RECOMMENDATION ENGINE MARKET SIZE, BY REGION,
2015-2022 (USD MILLION) 41
TABLE 4 CONTENT RECOMMENDATION ENGINE MARKET SIZE, BY ORGANIZATION SIZE, 2015-2022 (USD MILLION) 45
TABLE 5 SMALL AND MEDIUM ENTERPRISES: CONTENT RECOMMENDATION ENGINE MARKET SIZE, BY REGION, 2015-2022 (USD MILLION) 46
TABLE 6 LARGE ENTERPRISES: CONTENT RECOMMENDATION ENGINE MARKET SIZE,
BY REGION, 2015-2022 (USD MILLION) 47
TABLE 7 CONTENT RECOMMENDATION ENGINE MARKET SIZE, BY VERTICAL,
2015–2022 (USD MILLION) 50
TABLE 8 E-COMMERCE: CONTENT RECOMMENDATION ENGINE MARKET SIZE,
BY REGION, 2015–2022 (USD MILLION) 51
TABLE 9 MEDIA, ENTERTAINMENT & GAMING: CONTENT RECOMMENDATION ENGINE MARKET SIZE, BY REGION, 2015–2022 (USD MILLION) 52
TABLE 10 RETAIL & CONSUMER GOODS: CONTENT RECOMMENDATION ENGINE MARKET,
BY REGION, 2015–2022 (USD MILLION) 52
TABLE 11 HOSPITALITY: CONTENT RECOMMENDATION ENGINE MARKET SIZE, BY REGION, 2015–2022 (USD MILLION) 53
TABLE 12 IT & TELECOMMUNICATION: CONTENT RECOMMENDATION ENGINE MARKET SIZE, BY REGION, 2015–2022 (USD MILLION) 54
TABLE 13 BFSI: CONTENT RECOMMENDATION ENGINE MARKET, BY REGION,
2015–2022 (USD MILLION) 55
TABLE 14 EDUCATION & TRAINING: CONTENT RECOMMENDATION ENGINE MARKET SIZE,
BY REGION, 2015–2022 (USD MILLION) 55
TABLE 15 HEALTHCARE & PHARMACEUTICAL: CONTENT RECOMMENDATION ENGINE MARKET SIZE, BY REGION, 2015–2022 (USD MILLION) 56
TABLE 16 OTHERS: CONTENT RECOMMENDATION ENGINE MARKET SIZE, BY REGION,
2015–2022 (USD MILLION) 57
TABLE 17 CONTENT RECOMMENDATION ENGINE MARKET, BY REGION,
2015–2022 (USD MILLION) 59
TABLE 18 NORTH AMERICA: CONTENT RECOMMENDATION ENGINE MARKET,
BY COMPONENT, 2015–2022 (USD MILLION) 62
TABLE 19 NORTH AMERICA: CONTENT RECOMMENDATION ENGINE MARKET,
BY ORGANIZATION SIZE, 2015–2022 (USD MILLION) 62
TABLE 20 NORTH AMERICA: CONTENT RECOMMENDATION ENGINE MARKET,
BY VERTICAL, 2015–2022 (USD MILLION) 62
TABLE 21 NORTH AMERICA: CONTENT RECOMMENDATION ENGINE MARKET FOR E-COMMERCE, BY COMPONENT, 2015–2022 (USD MILLION) 63
TABLE 22 NORTH AMERICA: CONTENT RECOMMENDATION ENGINE MARKET FOR MEDIA, ENTERTAINMENT & GAMING, BY COMPONENT, 2015–2022 (USD MILLION) 63
TABLE 23 NORTH AMERICA: CONTENT RECOMMENDATION ENGINE MARKET FOR RETAIL & CONSUMER GOODS, BY COMPONENT, 2015–2022 (USD MILLION) 63
TABLE 24 NORTH AMERICA: CONTENT RECOMMENDATION ENGINE MARKET FOR HOSPITALITY, BY COMPONENT, 2015–2022 (USD MILLION) 64
TABLE 25 NORTH AMERICA: CONTENT RECOMMENDATION ENGINE MARKET FOR IT & TELECOMMUNICATION, BY COMPONENT, 2015–2022 (USD MILLION) 64
TABLE 26 NORTH AMERICA: CONTENT RECOMMENDATION ENGINE MARKET FOR BFSI,
BY COMPONENT, 2015–2022 (USD MILLION) 64
TABLE 27 EUROPE: CONTENT RECOMMENDATION ENGINE MARKET, BY COMPONENT, 2015–2022 (USD MILLION) 65
TABLE 28 EUROPE: CONTENT RECOMMENDATION ENGINE MARKET, BY ORGANIZATION SIZE, 2015–2022 (USD MILLION) 65
TABLE 29 EUROPE: CONTENT RECOMMENDATION ENGINE MARKET, BY VERTICAL,
2015–2022 (USD MILLION) 66
TABLE 30 EUROPE: CONTENT RECOMMENDATION ENGINE MARKET FOR E-COMMERCE,
BY COMPONENT, 2015–2022 (USD MILLION) 66
TABLE 31 EUROPE: CONTENT RECOMMENDATION ENGINE MARKET FOR MEDIA, ENTERTAINMENT & GAMING, BY COMPONENT, 2015–2022 (USD MILLION) 66
TABLE 32 EUROPE: CONTENT RECOMMENDATION ENGINE MARKET FOR RETAIL & CONSUMER GOODS, BY COMPONENT, 2015–2022 (USD MILLION) 67
TABLE 33 EUROPE: CONTENT RECOMMENDATION ENGINE MARKET FOR HOSPITALITY,
BY COMPONENT, 2015–2022 (USD MILLION) 67
TABLE 34 EUROPE: CONTENT RECOMMENDATION ENGINE MARKET FOR IT & TELECOMMUNICATION, BY COMPONENT, 2015–2022 (USD MILLION) 67
TABLE 35 EUROPE: CONTENT RECOMMENDATION ENGINE MARKET FOR BFSI, BY COMPONENT, 2015–2022 (USD MILLION) 68
TABLE 36 ASIA PACIFIC: CONTENT RECOMMENDATION ENGINE MARKET, BY COMPONENT, 2015–2022 (USD MILLION) 70
TABLE 37 ASIA PACIFIC: CONTENT RECOMMENDATION ENGINE MARKET, BY ORGANIZATION SIZE, 2015–2022 (USD MILLION) 70
TABLE 38 ASIA PACIFIC: CONTENT RECOMMENDATION ENGINE MARKET, BY VERTICAL, 2015–2022 (USD MILLION) 70
TABLE 39 ASIA PACIFIC: CONTENT RECOMMENDATION ENGINE MARKET FOR E-COMMERCE, BY COMPONENT, 2015–2022 (USD MILLION) 71
TABLE 40 ASIA PACIFIC: CONTENT RECOMMENDATION ENGINE MARKET FOR MEDIA, ENTERTAINMENT & GAMING, BY COMPONENT, 2015–2022 (USD MILLION) 71
TABLE 41 ASIA PACIFIC: CONTENT RECOMMENDATION ENGINE MARKET FOR RETAIL & CONSUMER GOODS, BY COMPONENT, 2015–2022 (USD MILLION) 71
TABLE 42 ASIA PACIFIC: CONTENT RECOMMENDATION ENGINE MARKET FOR HOSPITALITY, BY COMPONENT, 2015–2022 (USD MILLION) 72
TABLE 43 ASIA PACIFIC: CONTENT RECOMMENDATION ENGINE MARKET FOR IT & TELECOMMUNICATION, BY COMPONENT, 2015–2022 (USD MILLION) 72
TABLE 44 ASIA PACIFIC: CONTENT RECOMMENDATION ENGINE MARKET FOR BFSI,
BY COMPONENT, 2015–2022 (USD MILLION) 72
TABLE 45 MIDDLE EAST & AFRICA: CONTENT RECOMMENDATION ENGINE MARKET,
BY COMPONENT, 2015–2022 (USD MILLION) 73
TABLE 46 MIDDLE EAST & AFRICA: CONTENT RECOMMENDATION ENGINE MARKET,
BY ORGANIZATION SIZE, 2015–2022 (USD MILLION) 73
TABLE 47 MIDDLE EAST & AFRICA: CONTENT RECOMMENDATION ENGINE MARKET,
BY VERTICAL, 2015–2022 (USD MILLION) 74
TABLE 48 MIDDLE EAST & AFRICA: CONTENT RECOMMENDATION ENGINE MARKET FOR
E-COMMERCE, BY COMPONENT, 2015–2022 (USD MILLION) 74
TABLE 49 MIDDLE EAST & AFRICA: CONTENT RECOMMENDATION ENGINE MARKET FOR MEDIA, ENTERTAINMENT & GAMING, BY COMPONENT, 2015–2022 (USD MILLION) 75
TABLE 50 MIDDLE EAST & AFRICA: CONTENT RECOMMENDATION ENGINE MARKET FOR RETAIL & CONSUMER GOODS, BY COMPONENT, 2015–2022 (USD MILLION) 75
TABLE 51 MIDDLE EAST & AFRICA: CONTENT RECOMMENDATION ENGINE MARKET FOR HOSPITALITY, BY COMPONENT, 2015–2022 (USD MILLION) 75
TABLE 52 MIDDLE EAST & AFRICA: CONTENT RECOMMENDATION ENGINE MARKET FOR IT & TELECOMMUNICATION, BY COMPONENT, 2015–2022 (USD MILLION) 76
TABLE 53 MIDDLE EAST & AFRICA: CONTENT RECOMMENDATION ENGINE MARKET FOR BFSI, BY COMPONENT, 2015–2022 (USD MILLION) 76
TABLE 54 LATIN AMERICA: CONTENT RECOMMENDATION ENGINE MARKET, BY COMPONENT, 2015–2022 (USD MILLION) 77
TABLE 55 LATIN AMERICA: CONTENT RECOMMENDATION ENGINE MARKET,
BY ORGANIZATION SIZE, 2015–2022 (USD MILLION) 77
TABLE 56 LATIN AMERICA: CONTENT RECOMMENDATION ENGINE MARKET, BY VERTICAL, 2015–2022 (USD MILLION) 77
TABLE 57 LATIN AMERICA: CONTENT RECOMMENDATION ENGINE MARKET FOR E-COMMERCE, BY COMPONENT, 2015–2022 (USD MILLION) 78
TABLE 58 LATIN AMERICA: CONTENT RECOMMENDATION ENGINE MARKET FOR MEDIA, ENTERTAINMENT & GAMING, BY COMPONENT, 2015–2022 (USD MILLION) 78
TABLE 59 LATIN AMERICA: CONTENT RECOMMENDATION ENGINE MARKET FOR RETAIL & CONSUMER GOODS, BY COMPONENT, 2015–2022 (USD MILLION) 78
TABLE 60 LATIN AMERICA: CONTENT RECOMMENDATION ENGINE MARKET FOR HOSPITALITY, BY COMPONENT, 2015–2022 (USD MILLION) 79
TABLE 61 LATIN AMERICA: CONTENT RECOMMENDATION ENGINE MARKET FOR IT & TELECOMMUNICATION, BY COMPONENT, 2015–2022 (USD MILLION) 79
TABLE 62 LATIN AMERICA: CONTENT RECOMMENDATION ENGINE MARKET FOR BFSI,
BY COMPONENT, 2015–2022 (USD MILLION) 79
TABLE 63 MARKET EVALUATION FRAMEWORK 81
TABLE 64 NEW PRODUCT LAUNCHES & PRODUCT ENHANCEMENTS, APRIL
2017- JANUARY 2018 82
TABLE 65 AGREEMENTS, COLLABORATIONS & PARTNERSHIPS, JULY 2017- JANUARY 2018 83
TABLE 66 ACQUISITIONS, JUNE 2015- FEBRUARY 2017 84
TABLE 67 EXPANSIONS, MAY 2015-JUNE 2017 85
TABLE 68 MARKET RANKING OF KEY PLAYERS IN THE CONTENT RECOMMENDATION ENGINE MARKET, 2017 85



LIST OF FIGURES

FIGURE 1 MARKET SEGMENTATION 14
FIGURE 2 CONTENT RECOMMENDATION ENGINE MARKET: RESEARCH DESIGN 16
FIGURE 3 DATA TRIANGULATION 18
FIGURE 4 MARKET SIZE ESTIMATION METHODOLOGY: BOTTOM-UP APPROACH 19
FIGURE 5 MARKET SIZE ESTIMATION METHODOLOGY: TOP-DOWN APPROACH 20
FIGURE 6 ASSUMPTIONS 21
FIGURE 7 CONTENT RECOMMENDATION ENGINE MARKET, BY COMPONENT,
2017 & 2022 (USD MILLION) 23
FIGURE 8 CONTENT RECOMMENDATION ENGINE MARKET, BY ORGANIZATION SIZE,
2017 & 2022 (USD MILLION) 23
FIGURE 9 CONTENT RECOMMENDATION ENGINE MARKET, BY VERTICAL, 2017 24
FIGURE 10 CONTENT RECOMMENDATION ENGINE MARKET, BY REGION,
2017 & 2022 (USD MILLION) 24
FIGURE 11 ASIA PACIFIC CONTENT RECOMMENDATION ENGINE MARKET IS EXPECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 25
FIGURE 12 FOCUS ON ENHANCING CUSTOMER EXPERIENCE IS DRIVING THE CONTENT RECOMMENDATION ENGINE MARKET 26
FIGURE 13 SERVICE COMPONENT SEGMENT IS PROJECTED TO GROW AT A HIGHER CAGR DURING THE FORECAST PERIOD 26
FIGURE 14 SMALL AND MEDIUM ENTERPRISES SEGMENT IS EXPECTED TO GROW AT A HIGHER CAGR FROM 2017 TO 2022 27
FIGURE 15 RETAIL & CONSUMER GOODS SEGMENT IS PROJECTED TO GROW AT THE HIGHEST CAGR DURING FORECAST PERIOD 27
FIGURE 16 NORTH AMERICA IS ESTIMATED TO LEAD THE CONTENT RECOMMENDATION ENGINE MARKET IN 2017 28
FIGURE 17 CONTENT RECOMMENDATION ENGINE MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES 29
FIGURE 18 RECOMMENDATION ENGINE: PHASES OF PERSONALIZATION 33
FIGURE 19 RECOMMENDATION ENGINE: FILTERING APPROACHES 35
FIGURE 20 THE SERVICE SEGMENT IS ESTIMATED TO GROW AT A HIGHER CAGR AS COMPARED TO THE SOLUTION SEGMENT DURING THE FORECAST PERIOD 39
FIGURE 21 BASED ON ORGANIZATION SIZE, THE LARGE ENTERPRISES SEGMENT IS ESTIMATED TO ACCOUNT FOR A LARGER SHARE OF THE CONTENT RECOMMENDATION ENGINE MARKET IN 2017 45
FIGURE 22 THE RETAIL & CONSUMER GOODS VERTICAL SEGMENT IS EXPECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 49
FIGURE 23 NORTH AMERICA IS ESTIMATED TO BE THE LARGEST MARKET FOR CONTENT RECOMMENDATION ENGINE MARKET IN 2017 59
FIGURE 24 THE CONTENT RECOMMENDATION ENGINE MARKET IN ASIA PACIFIC AND LATIN AMERICA IS PROJECTED TO REGISTER HIGH CAGRS DURING THE FORECAST PERIOD 60
FIGURE 25 NORTH AMERICA: CONTENT RECOMMENDATION ENGINE MARKET SNAPSHOT 61
FIGURE 26 ASIA PACIFIC: CONTENT RECOMMENDATION ENGINE MARKET SNAPSHOT 69
FIGURE 27 COMPANIES ADOPTED AGREEMENTS, COLLABORATIONS & PARTNERSHIPS AS KEY GROWTH STRATEGIES BETWEEN MAY 2015 AND JANUARY 2018 80

FIGURE 28 IBM: COMPANY SNAPSHOT 86
FIGURE 29 IBM: SWOT ANALYSIS 88
FIGURE 30 AMAZON WEB SERVICES: COMPANY SNAPSHOT 89
FIGURE 31 AMAZON WEB SERVICES: SWOT ANALYSIS 90
FIGURE 32 REVCONTENT: SWOT ANALYSIS 95
FIGURE 33 TABOOLA: SWOT ANALYSIS 99
FIGURE 34 OUTBRAIN: SWOT ANALYSIS 101
FIGURE 35 CXENSE: COMPANY SNAPSHOT 102


★調査レポート[コンテンツ・リコメンデーション・エンジンの世界市場予測(~2022年)] ( 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 / TC-6113) 販売に関する免責事項
[コンテンツ・リコメンデーション・エンジンの世界市場予測(~2022年)] ( 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 / TC-6113) についてEメールでお問い合わせ


◆H&Iグローバルリサーチ株式会社のお客様(例)◆