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市場調查報告書
商品編碼
393878

零售業分析的全球市場:成長,趨勢,及預測(2019年∼2024年)

Retail Analytics Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022 - 2027)

出版日期: | 出版商: Mordor Intelligence Pvt Ltd | 英文 120 Pages | 商品交期: 2-3個工作天內

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  • 全貌
  • 簡介
  • 目錄
簡介

全球零售業分析市場在2019年∼2024年間,預測將以超過19%的年複合成長率成長。

本報告提供全球零售業分析市場的相關調查,市場機會和未來趨勢,成長及阻礙因素,各解決方案、安裝、功能、地區的市場分析,競爭情形,主要企業的簡介等資訊。

目錄

第1章 簡介

  • 調查的成果
  • 調查的假設
  • 調查範圍

第2章 調查方法

第3章 摘要整理

第4章 市場動態

  • 市場概況
  • 市場成長及阻礙因素概要
  • 成長要素
    • E零售銷售的增加
    • 預測分析的需求高漲
    • AI及AR / VR的技術進步
  • 阻礙因素
    • 缺乏一般認識和專門知識
  • 產業的魅力:波特的五力分析
    • 新加入廠商的威脅
    • 買主/消費者談判力
    • 供應商談判力
    • 替代產品的威脅
    • 產業內的競爭

第5章 技術概要

第6章 市場區隔

  • 各解決方案
    • 軟體
    • 服務
  • 各安裝
    • 雲端
    • 內部部署
  • 各功能
    • 客戶管理
    • 店內營運
    • 策略及計劃
    • 供應鏈管理
    • 行銷及商品營銷
    • 其他
  • 各地區
    • 北美
    • 歐洲
    • 亞太地區
    • 南美
    • 中東及非洲地區

第7章 競爭情形

  • 企業簡介
    • SAP SE
    • IBM Corporation
    • Alteryx Inc.
    • Tableau Software Inc.
    • Oracle Corporation
    • Retail Next Inc.
    • SAS Institute Inc.
    • 富士通株式會社
    • Angoss Software Corporation
    • Hitachi, Ltd.

第8章 投資分析

第9章 市場機會及未來趨勢

目錄
Product Code: 52446

The Retail Analytics market was valued at USD 5.29 billion in 2020 and is expected to reach USD 15.03 billion by 2026, at a CAGR of 19% over the forecast period 2021 - 2026. Retail data analytics follows analyzing historical data to enable smarter decisions, improving operations, and increasing sales. Both end-user data and back-end processes, such as supply chain and inventory management, have been primary sources for data analytics.

Key Highlights

  • 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 in-store 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 e-commerce has rendered traditional growth avenues across brick-and-mortar 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 in-store planning and execution.
  • As most companies started remote operations to avoid exposing their employees to the COVID-19, 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 re-evaluate 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 no-cost and online COVID-19 Data Dashboard. This tool allows CPG manufacturers and retailers to access real-time change in pricing of consumer-packaged goods, for instance, due to the pandemic's supply chain and economic impacts for pivoting strategies.

Key Market Trends

In-store Operation Hold Major Share

  • In-store-operation-based analytics has become an indispensable part of a brick-and-mortar 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 in-store 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 in-store 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 in-store sales through micro-targeting 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 large-scale 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 e-commerce 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 e-commerce 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 partner-driven effort from its Red Hat business. It is aligned to assist retailers in transforming businesses to serve the rapidly shifting way consumers shop.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

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