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1640511

零售業巨量資料分析 -市場佔有率分析、產業趨勢與統計、成長預測（2025-2030 年）

Big Data Analytics in Retail - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2025 - 2030)
出版日期: | 出版商: Mordor Intelligence | 英文 100 Pages | 商品交期: 2-3個工作天內

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簡介目錄

2025 年零售巨量資料分析市場規模估計為 77.3 億美元，預計到 2030 年將達到 202.2 億美元，預測期內（2025-2030 年）的複合年成長率為 21.2%。

零售巨量資料分析-市場-IMG1

先進的分析和巨量資料技術正在深刻改變零售業。隨著電子商務和網路購物的成長以及客戶忠誠度競爭的加劇，零售商開始轉向巨量資料分析以保持市場競爭力。

關鍵亮點

  • 零售業正穩步採用雲端、人工智慧和相關技術，被認為是成長最快的產業之一。根據 NASSCOM 的調查，70% 的企業致力於利用人工智慧來增加收益並增加支出。例如，全球最大的零售商之一沃爾瑪正在進行數位轉型。目前，該公司正在建置全球最大的私有雲端系統，預計每小時可管理Petabyte的資料。
  • 預測分析是一種主動方法，零售商使用歷史資料來預測由於消費者行為和市場趨勢的變化而導致的預期銷售成長。這使零售商能夠保持領先地位，有效競爭，並顯著提高市場佔有率。為了與客戶建立永續的關係，越來越傾向於重視預測分析，以幫助提高促銷效果並促進交叉銷售。
  • 零售商正在尋找創新的方法，從不斷增加的結構化和非結構化消費行為資訊中提取見解。透過在零售流程的每個階段（包括線下和線上）應用巨量資料分析，零售商可以了解客戶的購買行為，將其映射到產品上，並制定行銷策略來銷售產品。資料為先的策略來推動利潤。引入 IPS 系統、自助結帳的商店自動化、機器人技術和零售自動化等創新方法正在推動零售市場對巨量資料分析的需求。
  • 資料整合挑戰可能會限制市場發展，包括資料管治、可擴展性以及從多個來源獲取資料所帶來的資料重複和轉換規則問題。但是，可以透過制定適當的系統規則來緩解這些問題。
  • 由於工廠和製造廠關閉、物價上漲、嚴格封鎖以及人們被迫回家導致的供應鏈中斷，COVID-19 疫情對區域和國家零售市場產生了重大影響。然而，疫情過後，考慮到人類的基本需求，巨量資料正在透過有針對性的廣告、產品推薦和定價來幫助零售商以更個人化的方式服務客戶。

零售業巨量資料分析的市場趨勢

商品行銷和供應鏈分析領域預計將佔據大部分市場佔有率

  • 電子商務已經影響了傳統的實體零售業，降低了其重要性並引發了零售業的資料主導革命。高效率的供應鏈（即貨物從供應商到倉庫、商店到客戶的最佳運輸）對任何企業都至關重要。這就是巨量資料分析成為零售供應鏈變革的核心的原因。 i. 即時追蹤產品流和庫存水平，使用客戶資料預測購買模式，甚至使用機器人在龐大的自動化倉庫中不知疲倦地完成訂單。
  • 隨著零售業隨著商品行銷、分析和數位解決方案的整合而不斷發展，零售商必須保持領先地位並快速回應客戶需求。在英國，零售業的供應鏈巨量資料分析預計將在預測期內大幅成長，其次是製造業和能源產業。此外，預測分析和機器學習人工智慧有望徹底改變零售供應鏈。
  • 事實證明，先進的商品行銷分析可以幫助零售商克服全通路零售世界中取得成功的挑戰。根據《麻省理工技術評論》巨量資料分析洞察調查，該調查以全球消費品和零售業案例，48% 的消費品和零售業受訪者認為引進人工智慧將改善客戶服務。的是品管（ 47%）、庫存管理（47%）、產品個人化、定價和詐欺檢測被認為有用。
  • 隨著全球經濟變得更加互聯和複雜，企業發現很難滿足客戶的期望。公司需要更快、更果斷、更準確地做出供應鏈決策，並且能夠快速、透明地實施這些決策。綜合需求計劃對於在當今市場保持競爭力至關重要。此外，為了實現按時全額交貨 (OTIF)，公司需要端到端供應鏈可視性，即時平衡供需，并快速有效地交付正確的產品。提高客戶滿意度、最佳化存量基準和分銷網路、縮短上市時間以實現銷售額最大化都證明了該領域對巨量資料分析的必要性。

預計北美將佔最大佔有率

  • 零售業的巨量資料分析可幫助公司根據顧客的購買歷史提出產品推薦。其結果是提高了提供客製化購物體驗和增強客戶服務的能力。這些資料集數量龐大，可以幫助您預測趨勢並做出以資料為主導的策略決策。北美零售市場巨量資料分析的成長是由零售分析工具的需求不斷成長以及物聯網在零售流程中的使用所推動的，從而提高了零售企業的生產力和效率。
  • 該地區大型零售商的銷售額正在成長。美國零售聯合會（NRF）預計，受消費者信心高漲、失業率低和工資上漲的推動，去年美國零售額將超過4.44兆美元，成長6%徵兆8%。有彈性的經濟。
  • 此外，北美在巨量資料分析應用方面一直處於創新領先地位並處於先驅地位。該地區擁有強大的巨量資料分析供應商隊伍，進一步促進了市場的成長。範例包括 IBM Corporation、SAS Institute Inc.、Alteryx Inc. 和 Microstrategy Incorporated。由於資料生產和零售消費的增加以及相應的銷售額的成長，巨量資料分析硬體、軟體和服務正在推動支出的增加。
  • 零售業越來越多採用工業 4.0 是推動市場成長的主要方面之一。零售 4.0 已經實現了多項零售業務和流程的數位化和自動化，包括庫存管理、客戶服務、客戶帳戶、供應鏈管理和商品管理活動。預計預測期內將進一步推動北美零售大巨量資料分析市場的成長。

零售業巨量資料分析概述

零售市場的巨量資料分析處於中度至高度分散的狀態。電子商務和網路購物的成長以及對客戶忠誠度的激烈競爭為零售市場的巨量資料分析提供了有利可圖的機會。整體來看，現有競爭對手之間的競爭非常激烈。未來，大公司的各種創新策略將有效推動市場成長。

2022 年 8 月，明訊收購了馬來西亞零售分析新興企業ComeBy 的股權，擴大了技術和網路的覆蓋範圍，幫助推動該國的零售創新和數位化。

此外，2022廣告宣傳8 月，人工智慧驅動的品牌分析解決方案公司 DataWeave 宣布已成為亞馬遜廣告合作夥伴網路的審查合作夥伴，幫助品牌透過可操作的資料洞察 支援最佳化。亞馬遜廣告合作夥伴網路和新的合作夥伴目錄使品牌能夠接觸到由代理商和工具提供商組成的全球社區，他們可以幫助廣告商使用亞馬遜廣告產品實現其業務目標。

其他福利

  • Excel 格式的市場預測 (ME) 表
  • 3 個月的分析師支持

目錄

第 1 章 簡介

  • 研究假設和市場定義
  • 研究範圍

第2章調查方法

第3章執行摘要

第4章 市場動態

  • 市場概況
  • 市場促進因素
    • 更重視預測分析
    • 商品行銷和供應鏈分析領域預計將佔據大部分市場佔有率
  • 市場限制
    • 從不同系統收集和整理資料的複雜性
  • 產業價值鏈分析
  • 產業吸引力-波特五力模型
    • 新進入者的威脅
    • 購買者/消費者的議價能力
    • 供應商的議價能力
    • 替代品的威脅
    • 競爭對手之間的競爭強度
  • COVID-19 對市場的影響

第5章 市場區隔

  • 按應用
    • 商品行銷與供應鏈分析
    • 社群媒體分析
    • 客戶分析
    • 營運情報
    • 其他
  • 依業務類型
    • 中小型企業
    • 大型組織
  • 按地區
    • 北美洲
    • 歐洲
    • 亞太地區
    • 其他

第6章 競爭格局

  • 公司簡介
    • SAP SE
    • Oracle Corporation
    • Qlik Technologies Inc.
    • Zoho Corporation
    • IBM Corporation
    • Retail Next Inc.
    • Alteryx Inc.
    • Salesforce.com Inc.（Tableau Software Inc.）
    • Adobe Systems Incorporated
    • Microstrategy Inc.
    • Hitachi Vantara Corporation
    • Fuzzy Logix LLC

第7章投資分析

第8章 市場機會與未來趨勢

簡介目錄
Product Code: 53994

The Big Data Analytics in Retail Market size is estimated at USD 7.73 billion in 2025, and is expected to reach USD 20.22 billion by 2030, at a CAGR of 21.2% during the forecast period (2025-2030).

Big Data Analytics in Retail - Market - IMG1

The retail industry is witnessing a major transformation through advanced analytics and Big Data technologies. With the growth of e-commerce, online shopping, and high competition for customer loyalty, retailers are utilizing Big Data analytics to stay competitive in the market.

Key Highlights

  • The retail industry witnessed a steady adoption of cloud, AI, and related technologies and is considered one of the top sectors in terms of growth. According to a survey by NASSCOM, 70 percent of the companies said they focus on revenue growth by leveraging AI and increasing their spending. For Example, Walmart, one of the largest retailers in the world, is undergoing a digital transformation. It is in the process of building the world's largest private cloud system, which is expected to have the capacity to manage 2.5 petabytes of data every hour.
  • Predictive analytics is a proactive approach whereby retailers can use data from the past to predict expected sales growth due to changes in consumer behaviors and market trends. It can help retailers stay ahead of the curve, compete effectively, and gain considerable market share. Increased Emphasis on Predictive Analytics which can help increase promotional effectiveness, drive cross-selling, and much more to build sustainable relationships with the customers.
  • Retailers attempt to find innovative ways to draw insights from the ever-increasing amount of structured and unstructured information about consumer behavior. Retailers, both offline and online, are adopting the data-first strategy toward understanding their customers' buying behavior, mapping them to products, and planning marketing strategies to sell their products to increase profits by applying Big Data Analytics at every step of the retail process. Innovative ways such as Implementing IPS systems, Store Automation with self check out, Robots, and Automation in retail, etc., drive the need for Big data analytics in the retail market.
  • Data integration challenges could restrain the market, including data governance, scalability, and problems associated with getting data from multiple sources to have data duplication and transformation rules. However, these can be reduced with the proper systematic set of rules.
  • The COVID-19 pandemic hugely impacted retail markets at the regional and country level due to the shutdown of factories, and manufacturing plants, increase in prices, strict lockdowns, and supply chain disruptions as people's mobility were confirmed to their homes. However, post-pandemic considering the inherent human needs, Big Data is helping retailers to cater to customers in a more personalized way via targeted advertising, product recommendations, and pricing; the retailers increasingly prefer the technology.

Big Data Analytics in Retail Market Trends

Merchandising and Supply Chain Analytics Segment Expected to Hold Significant Share

  • E-commerce has impacted traditional brick-and-mortar retailers, reducing their significance and marking the data-driven revolution in the retail sector. An efficient supply chain, the optimized movement of goods from supplier to warehouse to store to the customer, is critical to every business. Therefore, big data analytics is at the core of revolutionizing the retail supply chain, i.e., tracking and tracing product flow and stock levels in real-time, leveraging customer data to predict buying patterns, and even using robots to fulfill orders in vast automated warehouses tirelessly.
  • Retailers must stay proactive and quickly fulfill customer needs as the retail industry continues to evolve with the integration of merchandising analytics and digital solutions. In the United Kingdom, the supply chain Big Data analytics for retail is expected to grow significantly over the forecast period, following the manufacturing and energy sector. It is further expected that predictive analytics and machine learning AI will revolutionize the retail supply chain.
  • Leveraging advanced merchandising analytics is proven to help retailers overcome the challenges to thrive in an omnichannel retail world. According to the survey conducted by MIT Technology Review Insights for Big Data Analytics using cases in the consumer goods and retail industry worldwide predicts that 48 percent of respondents from the consumer goods and retail industry state that deployment of artificial intelligence can help improve customer care, followed by Quality control (47%), Inventory Management(47%), personalization of products, pricing, and fraud detection.
  • As the global economy becomes interconnected and complex, companies find it challenging to meet customer expectations. They must make supply chain decisions faster, more decisive, and more accurate and can implement those decisions rapidly and transparently. Integrated demand planning is necessary to remain competitive in today's marketplace. Further, to achieve OTIF (On-Time-In-Full), a company must have end-to-end supply chain visibility and be able to balance demand and supply in real-time to make the right decisions quickly and effectively. Improving customer satisfaction, optimizing inventory levels and distribution networks, and achieving a faster time to market for sales maximization prove the need for big data Analytics in this sector.

North America Region Expected to Hold the Largest Share

  • Big data analytics in retail helps companies to generate customer recommendations based on their purchase history. It results in an improved ability to offer customized shopping experiences and enhanced customer service. These data sets are available in massive volumes and aid in forecasting trends and making strategic decisions guided by data. The growth of North America's big data analytics in the retail market is driven by the rising demand for retail analytics tools and the usage of the IoT in retail processes, enhancing the productivity and efficiency of the retail industry.
  • The region's massive retail industry is experiencing growth in sales. In the United States, according to the National Retail Federation (NRF), retail sales are expected in between 6% to 8% to more than USD 4.44 trillion in the last year, citing high consumer confidence, low unemployment, and rising wages and clear signs of a strong and resilient economy.
  • Besides, North America is among the leading innovators and pioneers, in terms of the adoption, of Big Data analytics. The region boasts a strong foothold of Big Data analytics vendors, which further contributes to the market's growth. Some include IBM Corporation, SAS Institute Inc., Alteryx Inc., and Microstrategy Incorporated. Big data analytics hardware, software, and services need more significant expenditures due to the rise in data production and retail consumption with corresponding sales increases.
  • The increasing adoption of industry 4.0 across the retail sector is one of the primary aspects encouraging market growth. In retail 4.0, several operations and processes in the retail industry, like inventory management, customer service, customer accounts, supply chain management, and merchandising management activities, became digitized and automated. It is further expected to bolster the growth of North America's big data analytics in the retail market during the forecast period.

Big Data Analytics in Retail Industry Overview

Big data analytics in the retail market is moderately to highly fragmented. The growth of e-commerce, online shopping, and high competition for customer loyalty provides lucrative opportunities in big data analytics in the retail market. Overall, the competitive rivalry among existing competitors is high. Moving forward, different kinds of innovation strategies of large companies boost market growth effectively.

In August 2022, Maxis took a significant stake in Malaysian-based retail analytics startup, ComeBy, to empower innovation and digitalization in the retail industry with greater access to technology and the human network to create more economic multipliers for the country.

Also, in August 2022, DataWeave, an AI-powered Brand Analytics solution company, announced its status as a vetted partner in the Amazon Advertising Partner Network to support brands in optimizing their digital advertising campaigns with actionable data insights. The Amazon Advertising Partner Network, and new Partner Directory, provide brands access to a global community of agencies and tool providers that can help advertisers achieve their business goals using Amazon Ads products.

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 DYNAMICS

  • 4.1 Market Overview
  • 4.2 Market Drivers
    • 4.2.1 Increased Emphasis on Predictive Analytics
    • 4.2.2 Merchandising and Supply Chain Analytics Segment Expected to Hold Significant Share
  • 4.3 Market Restraints
    • 4.3.1 Complexities in Collecting and Collating the Data From Disparate Systems
  • 4.4 Industry Value Chain Analysis
  • 4.5 Industry Attractiveness - Porter Five Forces
    • 4.5.1 Threat of New Entrants
    • 4.5.2 Bargaining Power of Buyers/Consumers
    • 4.5.3 Bargaining Power of Suppliers
    • 4.5.4 Threat of Substitute Products
    • 4.5.5 Intensity of Competitive Rivalry
  • 4.6 Impact of COVID-19 on the Market

5 MARKET SEGMENTATION

  • 5.1 By Application
    • 5.1.1 Merchandising and Supply Chain Analytics
    • 5.1.2 Social Media Analytics
    • 5.1.3 Customer Analytics
    • 5.1.4 Operational Intelligence
    • 5.1.5 Other Applications
  • 5.2 By Business Type
    • 5.2.1 Small and Medium Enterprises
    • 5.2.2 Large-scale Organizations
  • 5.3 Geography
    • 5.3.1 North America
    • 5.3.2 Europe
    • 5.3.3 Asia-Pacific
    • 5.3.4 Rest of the World

6 COMPETITIVE LANDSCAPE

  • 6.1 Company Profiles
    • 6.1.1 SAP SE
    • 6.1.2 Oracle Corporation
    • 6.1.3 Qlik Technologies Inc.
    • 6.1.4 Zoho Corporation
    • 6.1.5 IBM Corporation
    • 6.1.6 Retail Next Inc.
    • 6.1.7 Alteryx Inc.
    • 6.1.8 Salesforce.com Inc. (Tableau Software Inc.)
    • 6.1.9 Adobe Systems Incorporated
    • 6.1.10 Microstrategy Inc.
    • 6.1.11 Hitachi Vantara Corporation
    • 6.1.12 Fuzzy Logix LLC

7 INVESTMENT ANALYSIS

8 MARKET OPPORTUNITIES AND FUTURE TRENDS