In-store Analytics Market by Application (Marketing Management, Customer Management, Merchandising Analysis, Store Operations Management, and Risk and Compliance Management), Component, Deployment, Organization Size, and Region - Global Forecast to 2023

インストアアナリティクスの世界市場予測(~2023年)

◆タイトル:In-store Analytics Market by Application (Marketing Management, Customer Management, Merchandising Analysis, Store Operations Management, and Risk and Compliance Management), Component, Deployment, Organization Size, and Region - Global Forecast to 2023
◆商品コード:TC-7009
◆調査・発行会社:MarketsandMarkets
◆発行日:2019年4月10日
◆ページ数:125
◆レポート形式:PDF / 英語
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【レポートの概要】

インストアアナリティクスの世界市場は、2018年の11億米ドルから2023年には32億米ドルに達し、この期間中23.5%の年平均成長率で成長すると予測されています。この市場の成長は、電子商取引の小売業者と実店舗での小売業者間の競争の激化、顧客サービスの向上、ショッピングエクスペリエンスの向上、そして実店舗でのデータ量の増加が考えられます。一方で、伝統的な小売業者は新しい技術を採用するこちに対して積極的ではないため、市場の成長は制限される可能性があります。当調査レポートでは、インストアアナリティクス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、市場シェア分析、用途別(マーケティング管理、顧客管理、商品分析、店舗運営管理、リスク・コンプライアンス管理)分析、コンポーネント別分析、導入別分析、組織の規模別分析、インストアアナリティクス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。

Need for leveraging distinct data to enhance customer retention and store profitability, to drive the adoption of in-store analytics across the retail industryMarketsandMarkets estimates the global in-store analytics market to grow from USD 1.1 billion in 2018 to USD 3.2 billion by 2023, at a Compound Annual Growth Rate (CAGR) of 23.5% during the forecast period. The in-store analytics market is growing rapidly with the increasing competition of brick-and-mortar retailers from eCommerce players, growing need for better customer service and enhanced shopping experience, and rising data volume around in-store operations. However, the reluctance of traditional retailers to adopt newer technologies would limit the growth of the market.
Merchandising analysis segment is expected to grow at the highest CAGR during the forecast period
Brick-and-mortar retailers have witnessed intense competition from various eCommerce websites, which has led to a decline in their growth. Merchandising analysis software provides analytical insights for building a localized strategy on the basis of strong and weaker-performing stores. It also explores incremental revenue opportunities with flexible ad-hoc analysis. The adoption of such applications helps improve the operational efficiency of the enterprise by meeting changing conditions for each selling season.
In-store analytics market in Asia Pacific is projected to grow at the highest CAGR during the forecast period
The high growth of the market in Asia Pacific (APAC) is attributed to the high growth potential, growing retail market, and increasing digitalization in the region with the rising need of businesses to remain globally competitive. Furthermore, the inclination of countries across the region toward emerging technologies such as Artificial Intelligence (AI) and advanced analytics, is also expected to fuel the growth of the in-store analytics market. However, the lack of technological awareness, privacy issues, and limited technical expertise in advanced technologies remains the biggest hurdle in the in-store analytics adoption across the region. The cloud-based in-store analytics software presents an optimal solution for these countries by minimizing integration complexities, and installation costs.
Large enterprises to hold the largest market share during the forecast period in the in-store analytics market
Organizations have been gradually recognizing the importance of in-store analytics software, and have started deploying them, as per their needs and available resources. The adoption of in-store analytics software and services among large enterprises is high due to the voluminous data generation due to the widespread customer base. Large retailers need to correlate voluminous data with customer behavioral information exhibited across the stores to gain meaningful insights and help support revenue generation.
In-depth interviews were conducted with the Chief Executive Officers (CEOs), Chief Technology Officers (CTOs), Chief Operating Officers (COOs), Vice Presidents (VPs), Managing Directors (MDs), technology and innovation directors, and related key executives from various key companies and organizations operating in the in-store analytics market.
 By Company – Tier 1–10%, Tier 2–25%, and Tier 3–65%
 By Designation – C-Level–25%, Director Level–50%, and Others–25%
 By Region – North America–40%, Europe–30%, and APAC–20%, RoW – 10%
The in-store analytics market comprises major solution providers, such as RetailNext (US), SAP (Germany), Thinkinside (Italy), Mindtree (India), Happiest Minds (India), Celect (US), Capillary Technologies (Singapore), Scanalytics (US), Inpixon (US), Retail Solutions (US), Dor Technologies (US), SEMSEYE (Lithuania), InvenSense (US), Walkbase (Finland), and Amoobi (Belgium). The study includes an in-depth competitive analysis of these key players in the in-store analytics market with their company profiles, recent developments, and key market strategies.
Research Coverage
The in-store analytics market revenue is primarily classified into revenues from software and services. Software revenue is associated with software offerings while services’ revenue is associated with support and maintenance services and consulting services. The market is also segmented on the basis of application, deployment model, organization size, and region.
Key benefits of the report
The report would help the market leaders/new entrants in this market with the information on the closest approximations of the revenue numbers for the overall in-store analytics market and the subsegments. This report would help stakeholders understand the competitive landscape and gain insights to better position their businesses and plan suitable go-to-market strategies. The report also helps stakeholders understand the pulse of the market and provides them with information on the key market drivers, restraints, challenges, and opportunities.

【レポートの目次】

TABLE OF CONTENTS

1 INTRODUCTION 17
1.1 OBJECTIVES OF THE STUDY 17
1.2 MARKET DEFINITION 17
1.3 MARKET SCOPE 18
1.4 YEARS CONSIDERED FOR THE STUDY 19
1.5 CURRENCY CONSIDERED 19
1.6 STAKEHOLDERS 20
2 RESEARCH METHODOLOGY 21
2.1 RESEARCH DATA 21
2.1.1 SECONDARY DATA 22
2.1.2 PRIMARY DATA 22
2.1.2.1 Breakup of primaries 22
2.1.2.2 Key industry insights 23
2.2 MARKET BREAKUP AND DATA TRIANGULATION 24
2.3 MARKET SIZE ESTIMATION 25
2.4 MARKET FORECAST 26
2.5 MICROQUADRANT RESEARCH METHODOLOGY 27
2.5.1 VENDOR INCLUSION CRITERIA 27
2.6 RESEARCH ASSUMPTIONS 28
2.7 LIMITATIONS 28
3 EXECUTIVE SUMMARY 29
4 PREMIUM INSIGHTS 34
4.1 ATTRACTIVE MARKET OPPORTUNITIES IN THE IN-STORE ANALYTICS MARKET 34
4.2 IN-STORE ANALYTICS MARKET, BY APPLICATION (2018–2023) 34
4.3 IN-STORE ANALYTICS MARKET, BY ORGANIZATION SIZE (2018–2023) 35
4.4 IN-STORE ANALYTICS MARKET: MARKET SHARE ACROSS REGIONS 35
5 MARKET OVERVIEW AND INDUSTRY TRENDS 36
5.1 INTRODUCTION 36
5.2 MARKET DYNAMICS 36
5.2.1 DRIVERS 37
5.2.1.1 Increased competition from eCommerce players 37
5.2.1.2 Need for better customer service and enhanced shopping experience 37
5.2.1.3 Rising data volume around in-store operations 37

5.2.2 RESTRAINTS 38
5.2.2.1 Data security and privacy concerns over new advanced technologies 38
5.2.2.2 Lack of skilled personnel 38
5.2.3 OPPORTUNITIES 39
5.2.3.1 Advent of cloud-based analytics 39
5.2.3.2 High growth potential in emerging economies 39
5.2.4 CHALLENGES 39
5.2.4.1 Reluctance of retailers 39
5.3 INDUSTRY TRENDS 40
5.3.1 USE CASES 40
5.3.1.1 USE CASE 1: Increasing profits by leveraging store inventories 40
5.3.1.2 USE CASE 2: Understanding customer behavior to enhance revenue and profitability 40
5.3.1.3 USE CASE 3: Tracking engagement metrics and monitoring customer behavior in real time 41
5.3.2 IMPACT OF AI AND ML ON THE IN-STORE ANALYTICS MARKET 41
5.3.3 IN-STORE ANALYTICS PROCESS 42
6 IN-STORE ANALYTICS MARKET, BY COMPONENT 43
6.1 INTRODUCTION 44
6.2 SOFTWARE 45
6.2.1 NEED FOR LEVERAGING DISTINCT DATA TO ENHANCE CUSTOMER RETENTION AND STORE PROFITABILITY 45
6.3 SERVICES 46
6.3.1 PROFESSIONAL SERVICES 47
6.3.1.1 Support and maintenance services 48
6.3.1.1.1 Complexity of operations and the need for regular assistance during the software lifecycle to foster the growth of support and maintenance services 48
6.3.1.2 Consulting services 49
6.3.1.2.1 Need for a strategic outlook exploring new avenues for improving business performance to drive the growth of consulting services 49
6.3.2 MANAGED SERVICES 50
6.3.2.1 Need for monitoring and maintaining software operations and reducing overhead costs 50
7 IN-STORE ANALYTICS MARKET, BY APPLICATION 51
7.1 INTRODUCTION 52
7.2 CUSTOMER MANAGEMENT 53
7.2.1 CUSTOMER FOOTFALL ANALYSIS 53
7.2.1.1 Monitoring and measuring footfalls to identify various sales opportunities 53

7.2.2 CUSTOMER BEHAVIORAL ANALYSIS 54
7.2.2.1 Understanding customer behavior to discover pain points affecting customer behavior 54
7.2.3 CUSTOMER SERVICE 54
7.2.3.1 Assisting customers in enhancing customer experience and improving customer retention 54
7.3 MARKETING MANAGEMENT 54
7.3.1 CAMPAIGN MANAGEMENT 55
7.3.1.1 Improving customer experience through customized campaigns 55
7.3.2 LOYALTY MANAGEMENT 55
7.3.2.1 Initiating loyalty programs to target the mass market 55
7.3.3 CROSS-SELL AND UPSELL AND POINT OF SALE 55
7.3.3.1 Generating additional revenues and increasing customer lifetime value 55
7.3.4 MARKET BASKET ANALYSIS 55
7.3.4.1 Identifying correlation among products to provide real-time recommendations 55
7.4 MERCHANDISING ANALYSIS 56
7.4.1 SPACE PLANNING AND OPTIMIZATION 56
7.4.1.1 Optimizing spaces to improve operational efficiency 56
7.4.2 PRODUCT CATEGORY ANALYSIS 56
7.4.2.1 Categorizing products of similar nature and attributes 56
7.4.3 STORE LAYOUT ANALYSIS 57
7.4.3.1 Optimizing store layout for maximum utilization of floor space 57
7.5 STORE OPERATIONS MANAGEMENT 57
7.5.1 WORKFORCE OPTIMIZATION 57
7.5.1.1 Scheduling tasks and utilizing workforce to improve the overall efficiency 57
7.5.2 TOP-PERFORMING CATEGORIES AND PRODUCT IDENTIFICATION 58
7.5.2.1 Predicting customer demands and top performing categories to drive sales and profitability 58
7.5.3 INVENTORY MANAGEMENT 58
7.5.3.1 Managing inventory to identify non-performing products and prevent out-of-stock situations 58
7.6 RISK AND COMPLIANCE MANAGEMENT 58
7.6.1 FRAUD DETECTION 59
7.6.1.1 Real-time recognition of suspicious activities to safeguard confidential information 59
7.7 OTHERS 59

8 IN-STORE ANALYTICS MARKET, BY DEPLOYMENT MODEL 60
8.1 INTRODUCTION 61
8.2 CLOUD 62
8.2.1 IMPROVED FLEXIBILITY AND SCALABILITY TO DRIVE THE GROWTH OF CLOUD-BASED IN-STORE ANALYTICS SOFTWARE 62
8.3 ON-PREMISES 62
8.3.1 DATA SECURITY AND PRIVACY REQUIREMENTS TO REMAIN FACTORS DOMINATING ON-PREMISES IN-STORE ANALYTICS SOLUTIONS 62
9 IN-STORE ANALYTICS MARKET, BY ORGANIZATION SIZE 64
9.1 INTRODUCTION 65
9.2 SMALL AND MEDIUM-SIZED ENTERPRISES 66
9.2.1 DEMAND FOR ANALYTICS SOFTWARE WITH LOW OPERATIONAL COSTS 66
9.3 LARGE ENTERPRISES 67
9.3.1 NEED FOR LEVERAGING VOLUMINOUS DATA TO STAY COMPETITIVE 67
10 IN-STORE ANALYTICS MARKET, BY REGION 68
10.1 INTRODUCTION 69
10.2 NORTH AMERICA 70
10.2.1 UNITED STATES 73
10.2.1.1 Notable technology spending and presence of a large number of retailers to bolster the growth of in-store analytics market in the United States 73
10.2.2 CANADA 73
10.2.2.1 Demand for comprehensive marketing, footfall measurement, and enhanced customer engagement to propel the market growth 73
10.3 EUROPE 74
10.3.1 UNITED KINGDOM 76
10.3.1.1 Increasing technology adoption and various government initiatives to fuel the growth of in-store analytics market in the United Kingdom 76
10.3.2 GERMANY 76
10.3.2.1 Need for maintaining a competitive edge to drive the adoption of advanced technologies, such as in-store analytics, in Germany 76
10.3.3 FRANCE 77
10.3.3.1 Expansion of in-store analytics vendors in France to open new avenues for in-store analytics 77
10.3.4 REST OF EUROPE 77

10.4 ASIA PACIFIC 77
10.4.1 CHINA 80
10.4.1.1 Steady income growth and growing retail market to drive the implementation of in-store analytics in China 80
10.4.2 JAPAN 81
10.4.2.1 Expansion of the retail industry and its inclination toward emerging technologies to fuel the growth of in-store analytics market in Japan 81
10.4.3 INDIA 81
10.4.3.1 Partnerships of brick and mortar retailers with leading analytics solution providers to further bolster the adoption of in-store analytics in India 81
10.4.4 REST OF ASIA PACIFIC 81
10.5 MIDDLE EAST AND AFRICA 82
10.5.1 MIDDLE EAST 84
10.5.1.1 Price consciousness and high purchasing power of people to fuel the growth of in-store analytics market among retailers in the Middle East 84
10.5.2 AFRICA 84
10.5.2.1 Making well-informed business decisions to increase basket size and footfall driving the growth of in-store analytics market in Africa 84
10.6 LATIN AMERICA 85
10.6.1 MEXICO 87
10.6.1.1 Need to curb decreasing RoI and increase profitability fueling the growth of in-store analytics market in Mexico 87
10.6.2 BRAZIL 87
10.6.2.1 Need for one-step pricing and customer engagement solution to propel the growth of in-store analytics market in Brazil 87
10.6.3 REST OF LATIN AMERICA 87
11 COMPETITIVE LANDSCAPE 88
11.1 MICROQUADRANT OVERVIEW 88
11.1.1 VISIONARIES 88
11.1.2 INNOVATORS 88
11.1.3 DYNAMIC DIFFERENTIATORS 88
11.1.4 EMERGING COMPANIES 88
11.2 COMPETITIVE BENCHMARKING 90
11.2.1 STRENGTH OF PRODUCT OFFERINGS OF MAJOR PLAYERS IN THE IN-STORE ANALYTICS MARKET 90
11.2.2 BUSINESS STRATEGY EXCELLENCE OF MAJOR PLAYERS IN THE IN-STORE ANALYTICS MARKET 91
11.3 MARKET RANKING 92

12 COMPANY PROFILES 93
(Business overview, Products offered, Recent developments, SWOT analysis & MnM View)*
12.1 INTRODUCTION 93
12.2 RETAILNEXT 93
12.3 MINDTREE 96
12.4 THINKINSIDE 99
12.5 HAPPIEST MINDS 101
12.6 SAP 103
12.7 CELECT 106
12.8 CAPILLARY TECHNOLOGIES 108
12.9 INPIXON 109
12.10 SCANALYTICS 111
12.11 RETAIL SOLUTIONS 113
12.12 DOR TECHNOLOGIES 115
12.13 SEMSEYE 115
12.14 INVENSENSE 116
12.15 WALKBASE 116
12.16 AMOOBI 117
*Details on Business overview, Products offered, Recent developments, SWOT analysis & MnM View might not be captured in case of unlisted companies.
13 APPENDIX 118
13.1 DISCUSSION GUIDE 118
13.2 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 121
13.3 AVAILABLE CUSTOMIZATION 123
13.4 RELATED REPORTS 123
13.5 AUTHOR DETAILS 124

LIST OF TABLES

TABLE 1 UNITED STATES DOLLAR EXCHANGE RATE, 2015–2017 19
TABLE 2 FACTOR ANALYSIS 26
TABLE 3 EVALUATION CRITERIA 27
TABLE 4 IN-STORE ANALYTICS MARKET SIZE AND GROWTH RATE,
2016–2023 (USD MILLION, Y-O-Y %) 30
TABLE 5 IN-STORE ANALYTICS MARKET SIZE, BY COMPONENT, 2016–2023 (USD MILLION) 44
TABLE 6 SOFTWARE: IN-STORE ANALYTICS MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 45
TABLE 7 IN-STORE ANALYTICS MARKET SIZE, BY SERVICE, 2016–2023 (USD MILLION) 46
TABLE 8 SERVICES: IN-STORE ANALYTICS MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 47
TABLE 9 IN-STORE ANALYTICS MARKET SIZE, BY PROFESSIONAL SERVICE,
2016–2023 (USD MILLION) 48
TABLE 10 PROFESSIONAL SERVICES: IN-STORE ANALYTICS MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 48
TABLE 11 SUPPORT AND MAINTENANCE SERVICES: IN-STORE ANALYTICS MARKET SIZE,
BY REGION, 2016–2023 (USD MILLION) 49
TABLE 12 CONSULTING SERVICES: IN-STORE ANALYTICS MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 49
TABLE 13 MANAGED SERVICES: IN-STORE ANALYTICS MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 50
TABLE 14 IN-STORE ANALYTICS MARKET SIZE, BY APPLICATION, 2016–2023 (USD MILLION) 52
TABLE 15 CUSTOMER MANAGEMENT: IN-STORE ANALYTICS MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 53
TABLE 16 MARKETING MANAGEMENT: IN-STORE ANALYTICS MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 54
TABLE 17 MERCHANDISING ANALYSIS: IN-STORE ANALYTICS MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 56
TABLE 18 STORE OPERATIONS MANAGEMENT: IN-STORE ANALYTICS MARKET SIZE,
BY REGION, 2016–2023 (USD MILLION) 57
TABLE 19 RISK AND COMPLIANCE MANAGEMENT: IN-STORE ANALYTICS MARKET SIZE,
BY REGION, 2016–2023 (USD MILLION) 58
TABLE 20 OTHERS: IN-STORE ANALYTICS MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 59
TABLE 21 IN-STORE ANALYTICS MARKET SIZE, BY DEPLOYMENT MODEL,
2016–2023 (USD MILLION) 61
TABLE 22 CLOUD: IN-STORE ANALYTICS MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 62
TABLE 23 ON-PREMISES: IN-STORE ANALYTICS MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 63
TABLE 24 IN-STORE ANALYTICS MARKET SIZE, BY ORGANIZATION SIZE,
2016–2023 (USD MILLION) 65
TABLE 25 SMALL AND MEDIUM-SIZED ENTERPRISES: IN-STORE ANALYTICS MARKET SIZE,
BY REGION, 2016–2023 (USD MILLION) 66
TABLE 26 LARGE ENTERPRISES: IN-STORE ANALYTICS MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 67

TABLE 27 IN-STORE ANALYTICS MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 70
TABLE 28 NORTH AMERICA: IN-STORE ANALYTICS MARKET SIZE, BY COMPONENT,
2016–2023 (USD MILLION) 71
TABLE 29 NORTH AMERICA: IN-STORE ANALYTICS MARKET SIZE, BY SERVICE,
2016–2023 (USD MILLION) 72
TABLE 30 NORTH AMERICA: IN-STORE ANALYTICS MARKET SIZE, BY APPLICATION,
2016–2023 (USD MILLION) 72
TABLE 31 NORTH AMERICA: IN-STORE ANALYTICS MARKET SIZE, BY DEPLOYMENT MODEL, 2016–2023 (USD MILLION) 72
TABLE 32 NORTH AMERICA: IN-STORE ANALYTICS MARKET SIZE, BY ORGANIZATION SIZE, 2016–2023 (USD MILLION) 73
TABLE 33 NORTH AMERICA: IN-STORE ANALYTICS MARKET SIZE, BY COUNTRY,
2016–2023 (USD MILLION) 73
TABLE 34 EUROPE: IN-STORE ANALYTICS MARKET SIZE, BY COMPONENT,
2016–2023 (USD MILLION) 74
TABLE 35 EUROPE: IN-STORE ANALYTICS MARKET SIZE, BY SERVICE,
2016–2023 (USD MILLION) 74
TABLE 36 EUROPE: IN-STORE ANALYTICS MARKET SIZE, BY APPLICATION,
2016–2023 (USD MILLION) 75
TABLE 37 EUROPE: IN-STORE ANALYTICS MARKET SIZE, BY DEPLOYMENT MODEL,
2016–2023 (USD MILLION) 75
TABLE 38 EUROPE: IN-STORE ANALYTICS MARKET SIZE, BY ORGANIZATION SIZE,
2016–2023 (USD MILLION) 75
TABLE 39 EUROPE: IN-STORE ANALYTICS MARKET SIZE, BY COUNTRY,
2016–2023 (USD MILLION) 76
TABLE 40 ASIA PACIFIC: IN-STORE ANALYTICS MARKET SIZE, BY COMPONENT,
2016–2023 (USD MILLION) 78
TABLE 41 ASIA PACIFIC: IN-STORE ANALYTICS MARKET SIZE, BY SERVICE,
2016–2023 (USD MILLION) 79
TABLE 42 ASIA PACIFIC: IN-STORE ANALYTICS MARKET SIZE, BY APPLICATION,
2016–2023 (USD MILLION) 79
TABLE 43 ASIA PACIFIC: IN-STORE ANALYTICS MARKET SIZE, BY DEPLOYMENT MODEL, 2016–2023 (USD MILLION) 79
TABLE 44 ASIA PACIFIC: IN-STORE ANALYTICS MARKET SIZE, BY ORGANIZATION SIZE,
2016–2023 (USD MILLION) 80
TABLE 45 ASIA PACIFIC: IN-STORE ANALYTICS MARKET SIZE, BY COUNTRY,
2016–2023 (USD MILLION) 80
TABLE 46 MIDDLE EAST AND AFRICA: IN-STORE ANALYTICS MARKET SIZE, BY COMPONENT, 2016–2023 (USD MILLION) 82
TABLE 47 MIDDLE EAST AND AFRICA: IN-STORE ANALYTICS MARKET SIZE, BY SERVICE, 2016–2023 (USD MILLION) 82
TABLE 48 MIDDLE EAST AND AFRICA: IN-STORE ANALYTICS MARKET SIZE, BY APPLICATION, 2016–2023 (USD MILLION) 83
TABLE 49 MIDDLE EAST AND AFRICA: IN-STORE ANALYTICS MARKET SIZE,
BY DEPLOYMENT MODEL, 2016–2023 (USD MILLION) 83
TABLE 50 MIDDLE EAST AND AFRICA: IN-STORE ANALYTICS MARKET SIZE,
BY ORGANIZATION SIZE, 2016–2023 (USD MILLION) 83
TABLE 51 MIDDLE EAST AND AFRICA: IN-STORE ANALYTICS MARKET SIZE, BY SUB REGION, 2016–2023 (USD MILLION) 84

TABLE 52 LATIN AMERICA: IN-STORE ANALYTICS MARKET SIZE, BY COMPONENT,
2016–2023 (USD MILLION) 85
TABLE 53 LATIN AMERICA: IN-STORE ANALYTICS MARKET SIZE, BY SERVICE,
2016–2023 (USD MILLION) 85
TABLE 54 LATIN AMERICA: IN-STORE ANALYTICS MARKET SIZE, BY APPLICATION,
2016–2023 (USD MILLION) 86
TABLE 55 LATIN AMERICA: IN-STORE ANALYTICS MARKET SIZE, BY DEPLOYMENT MODEL, 2016–2023 (USD MILLION) 86
TABLE 56 LATIN AMERICA: IN-STORE ANALYTICS MARKET SIZE, BY ORGANIZATION SIZE, 2016–2023 (USD MILLION) 86
TABLE 57 LATIN AMERICA: IN-STORE ANALYTICS MARKET SIZE, BY COUNTRY,
2016–2023 (USD MILLION) 87


LIST OF FIGURES

FIGURE 1 MARKET SEGMENTATION 18
FIGURE 2 REGIONS COVERED 18
FIGURE 3 GLOBAL IN-STORE ANALYTICS MARKET: RESEARCH DESIGN 21
FIGURE 4 IN-STORE ANALYTICS MARKET: MARKET ESTIMATION AND FORECAST METHODOLOGY 25
FIGURE 5 IN-STORE ANALYTICS MARKET OVERVIEW 31
FIGURE 6 IN-STORE ANALYTICS MARKET TO WITNESS HIGH GROWTH DURING
THE FORECAST PERIOD 32
FIGURE 7 IN-STORE ANALYTICS MARKET, BY COMPONENT (2018 VS. 2023) 33
FIGURE 8 IN-STORE ANALYTICS MARKET, BY DEPLOYMENT MODEL (2018–2023) 33
FIGURE 9 INCREASING NEED TO ANALYZE CONSUMER DATA IN REAL-TIME FOR MAKING INFORMED DECISIONS TO DRIVE THE IN-STORE ANALYTICS MARKET GROWTH 34
FIGURE 10 MERCHANDISING ANALYSIS SEGMENT TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 34
FIGURE 11 LARGE ENTERPRISES SEGMENT TO HOLD A HIGHER MARKET SHARE DURING
THE FORECAST PERIOD 35
FIGURE 12 NORTH AMERICA TO ACCOUNT FOR THE HIGHEST MARKET SHARE IN 2018 35
FIGURE 13 DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES:
IN-STORE ANALYTICS MARKET 36
FIGURE 14 IN-STORE ANALYTICS PROCESS 42
FIGURE 15 SERVICES SEGMENT TO GROW AT A HIGHER CAGR DURING
THE FORECAST PERIOD 44
FIGURE 16 MANAGED SERVICES SEGMENT TO GROW AT A HIGHER CAGR DURING
THE FORECAST PERIOD 46
FIGURE 17 CONSULTING SERVICES SEGMENT TO GROW AT A HIGHER CAGR DURING
THE FORECAST PERIOD 47
FIGURE 18 MERCHANDISING ANALYSIS SEGMENT TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 52
FIGURE 19 ON-PREMISES SEGMENT TO GROW AT A HIGHER CAGR DURING
THE FORECAST PERIOD 61
FIGURE 20 SMALL AND MEDIUM-SIZED ENTERPRISES SEGMENT TO GROW AT A HIGHER CAGR DURING THE FORECAST PERIOD 65
FIGURE 21 ASIA PACIFIC TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 69
FIGURE 22 NORTH AMERICA: MARKET SNAPSHOT 71
FIGURE 23 ASIA PACIFIC: MARKET SNAPSHOT 78
FIGURE 24 IN-STORE ANALYTICS, COMPETITIVE LEADERSHIP MAPPING, 2018 89
FIGURE 25 RANKING OF KEY PLAYERS IN THE IN-STORE ANALYTICS MARKET, 2018 92
FIGURE 26 RETAILNEXT: SWOT ANALYSIS 94
FIGURE 27 MINDTREE: COMPANY SNAPSHOT 96
FIGURE 28 MINDTREE: SWOT ANALYSIS 98
FIGURE 29 THINKINSIDE: SWOT ANALYSIS 100

FIGURE 30 HAPPIEST MINDS: SWOT ANALYSIS 102
FIGURE 31 SAP: COMPANY SNAPSHOT 103
FIGURE 32 SAP: SWOT ANALYSIS 104
FIGURE 33 INPIXON: COMPANY SNAPSHOT 109


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[インストアアナリティクスの世界市場予測(~2023年)] ( In-store Analytics Market by Application (Marketing Management, Customer Management, Merchandising Analysis, Store Operations Management, and Risk and Compliance Management), Component, Deployment, Organization Size, and Region - Global Forecast to 2023 / TC-7009) についてEメールでお問い合わせ


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