 | • レポートコード：D0MOR-NV117 • 出版社/出版日：Mordor Intelligence / 2020年8月 • レポート形態：英文、PDF、120ページ • 納品方法：Eメール（受注後2-3営業日） • 産業分類：小売り |
| Single User | ￥629,000 (USD4,250) | ▷ お問い合わせ |
| Team User | ￥703,000 (USD4,750) | ▷ お問い合わせ |
| Corporate License | ￥888,000 (USD6,000) | ▷ お問い合わせ |
• お支払方法：銀行振込（納品後、ご請求書送付）
レポート概要
| 本調査レポートでは、小売分析の世界市場について調査し、イントロダクション、調査手法、エグゼクティブサマリー、市場インサイト、市場動向、ソリューション別（ソフトウェア、サービス）分析、展開モード別（PC（クラウド、オンプレミス）分析、機能別（顧客管理、店内運営（在庫管理・フォーマンス管理）、サプライチェーン管理、マーケティング・マーチャンダイジング（価格設定・収益管理）、その他）分析、地域別分析、競争状況、投資分析、将来市場などを整理しました。 ・イントロダクション ・調査手法 ・エグゼクティブサマリー ・市場インサイト ・市場動向 ・小売分析の世界市場規模：ソリューション別（ソフトウェア、サービス） ・小売分析の世界市場規模：展開モード別（PC（クラウド、オンプレミス） ・小売分析の世界市場規模：機能別（顧客管理、店内運営（在庫管理・フォーマンス管理）、サプライチェーン管理、マーケティング・マーチャンダイジング（価格設定・収益管理）、その他） ・小売分析の世界市場規模：地域別 ・競争状況 ・投資分析 ・将来市場 |
The Retail Analytics market was valued at USD 5.29 billion in 2019 and is expected to reach USD 15.03 billion by 2025, at a CAGR of 19% over the forecast period 2020 2025. Retail data analytics follows analyzing historical data to enable smarter decisions, improving operations, and increasing sales. Both enduser data and backend processes, such as supply chain and inventory management, have been primary sources for data analytics.
Business Intelligence and Analytics systems have been integrated with back end applications to understand better shoppers’ behavior to facilitate consistent customer conversation. The omnichannel strategies being adopted led analytics to cater to multiple channels by consolidating disparate data sources and communicating with customers on their preferred channel.
A further step towards intense personalization has strengthened the typical customer Lifetime Value and touchpoints. Therefore, current retailers have been more inclined to collect and analyze data like Location, Social sentiment, Clickstream, etc.
Such a preference has led vendors in the market, to expand and launch platforms based on the capabilities mentioned above in lieu of gathering more data from customers. For instance, ShopperTrak (part of Johnson Controls), primarily being dependent on instore devices to count shoppers, leveraged mobile device detection and analytics. And, as of January 2020, Placer.ai, a location data analytics company, raised USD 12 million in funding to plow into research and development of new features to its platform and extend presence in the United States.
Major driver for retailers adopting analytics currently has been attributed to digital transformation initiatives taken. This refers to the deployment of sensors, trackers, cameras, etc. to physical spaces. As of January 2020, Microsoft’s survey across retail enterprise organizations reflected on the adoption of the IoT ecosystem in retail. In the US, IoT adoption in retail highlights a 65% vote towards security and store analytics as to the reason for the same. In Europe, 49% on store analytics and 43% on supply chain/store optimization are key uses.
The advent of ecommerce has rendered traditional growth avenues across brickandmortar store expansions as outdated. Online platforms, localized assortments, and international market expansions have transformed the way merchandising analytics was approached. Significant competition from the online platforms led retailers to enter that space and offered a clearer picture of assortment, pricing, promotions, sourcing, replenishment, and instore planning and execution.
As most companies started remote operations to avoid exposing their employees to the COVID19, the retail sales dropped globally, indicating a blockage of sales information to retailers’ data repositories. Since the objectives of a specific automated system or predictive model remain the same, the input data and the users’ issues have led the companies (vendors) to reevaluate how outputs could now be interpreted.
Additionally, as of May 2020, IRI, a data analytics solution provider, launched a proprietary CPG Inflation Tracker on its nocost and online COVID19 Data Dashboard. This tool allows CPG manufacturers and retailers to access realtime change in pricing of consumerpackaged goods, for instance, due to the pandemic’s supply chain and economic impacts for pivoting strategies.
[Key Market Trends]
Instore Operation Hold Major Share
Instoreoperationbased analytics has become an indispensable part of a brickandmortar retailer’s operating strategy. With benefits ranging from offering the right product to the right customer, further insight on loyal customers leads to the development of strategies to increase customer stickiness.
Also, a 2019 survey by Alteryx with 350 retailers and brand manufacturers suggested that almost 81% of respondents are gathering shopper insights. At the same time, 76% consider insights to be critical to their sales/revenue performance. However, the mere collection of data doesn’t suffice. According to the study, only 16% have been able to actively move onto data harnessing, while 24% and 60%, respectively, are yet to discover and have just started.
As per Jabil’s 2020 Future of Retail Technology, 90% of respondents expect spending on instore technology to increase in the coming years. And 94% responded to have been investing in analytics technology. Significant consideration has been skewed towards adding features and products to complement retail analytics.
Whereas, on the vendor front, recently, Microsoft announced new retail products related to its Microsoft Dynamics 365 line. This is in line with offering retail customers to improve instore operational efficiency and better measure saleable items whilst accurately determining who’s buying and how to get more buyers.
Quantzig, a data analytics and advisory firm, increased its instore sales through microtargeting and the profits by 12% for a fashion retailer based out of Germany. The retailer faced challenges focused on delivering insights to the right resource at the right time, lack of clearly articulated analytics strategy, and poor data quality.
[Europe to Hold Significant Share]
The European segment is strong, owing to the presence of large players like IBM Corporation and SAP SE, which are the leading providers of predictive analytics and advanced retail analytics software.
Moreover, more than six million companies are active in this region and employ more than 33 million people. Europe is home to many of the largescale retailers in the world, such as Tesco, Carrefour, Lidl, Metro AG, and Aldi.
Online shopping has emerged as one of the most popular internet activities. It provides a wide variety of products for consumers and a multiplicity of sales challenges for the ecommerce players.
Thus, the use of advanced analytics for making online shopping smarter and merging offline and online data can help retailers to customize their targeting, thus resulting in incremental increases in ecommerce revenues and contributing to the growth of the European segment of the market studied.
[Competitive Landscape]
The Retail Analytics Market is moderately competitive. The players in the market are innovating in providing strategic solutions to increase their market presence and customer base. This is enabling them to secure new contracts and tap new markets. Some of the key developments in the market are:
In Jan 2020 IBM launched “Store in the Cloud,” a partnerdriven effort from its Red Hat business. It is aligned to assist retailers in transforming businesses to serve the rapidly shifting way consumers shop.
[Reasons to Purchase this report]
The market estimate (ME) sheet in Excel format
3 months of analyst support
Please note: This publisher does offer titles that are created upon receipt of order. If you are purchasing a PDF Email Delivery option above, the report will take approximately 2 business days to prepare and deliver.
レポート目次1 INTRODUCTION
1.1 Study Assumptions and Market Definition
1.2 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET INSIGHTS
4.1 Market Overview
4.2 Industry Attractiveness – Porter’s Five Force Analysis
4.2.1 Bargaining Power of Suppliers
4.2.2 Bargaining Power of Buyers/Consumers
4.2.3 Threat of New Entrants
4.2.4 Intensity of Competitive Rivalry
4.2.5 Threat of Substitute Products
4.3 Industry Value Chain Analysis
4.4 Impact Of COVID-19 On the Industry
5 MARKET DYNAMICS
5.1 Market Drivers
5.1.1 Increasing Volumes of Data and Technological Advancements in AI and AR/VR
5.1.2 Increasing E-retail Sales
5.2 Market Challenges
5.2.1 Significant Reliance on Traditional Processes and Lack of Awareness and Expertise
6 MARKET SEGMENTATION
6.1 By Solution
6.1.1 Software
6.1.2 Service
6.2 By Deployment
6.2.1 Cloud
6.2.2 On-premise
6.3 By Function
6.3.1 Customer Management
6.3.2 In-store Operation (Inventory Management and Performance Management)
6.3.3 Supply Chain Management
6.3.4 Marketing and Merchandizing (Pricing and Yield Management)
6.3.5 Other Functions (Transportation Management, Order Management)
6.4 Geography
6.4.1 North America
6.4.1.1 United States
6.4.1.2 Canada
6.4.2 Europe
6.4.2.1 Germany
6.4.2.2 United Kingdom
6.4.2.3 France
6.4.2.4 Russia
6.4.2.5 Rest of Europe
6.4.3 Asia Pacific
6.4.3.1 China
6.4.3.2 Japan
6.4.3.3 India
6.4.3.4 Rest of Asia-Pacific
6.4.4 Latin America
6.4.5 Middle East & Africa
7 COMPETITIVE LANDSCAPE
7.1 Company Profiles
7.1.1 SAP SE
7.1.2 IBM Corporation
7.1.3 Alteryx Inc.
7.1.4 Salesforce.com Inc. (Tableau Software Inc.)
7.1.5 Oracle Corporation
7.1.6 Retail Next Inc.
7.1.7 SAS Institute Inc.
7.1.8 QlikTech International AB (Qlik)
7.1.9 Altair Engineering Inc.
7.1.10 Hitachi Vantara LLC
8 INVESTMENT ANALYSIS
9 FUTURE OF THE MARKET