查看購物車
  • Simplified Chinese
  • English
  • Japanese
封面
市場調查報告書
商品編碼
1776784

2032 年零售分析市場預測：按解決方案、部署、零售店類型、現場群眾外包、應用程式和地區進行的全球分析

Retail Analytics Market Forecasts to 2032 - Global Analysis By Solution (Software and Service), Deployment, Retail Store Type, Field Crowdsourcing, Application and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球零售分析市場預計在 2025 年達到 51 億美元，到 2032 年將達到 204 億美元，預測期內的複合年成長率為 21.7%。

零售分析涉及運用數據和定量方法來洞察客戶行為、銷售趨勢和零售業務效率。這包括分析銷售點數據、存量基準、客戶屬性、行銷宣傳活動成效、供應鏈績效等。利用商業智慧平台和機器學習等工具，零售商可以最佳化定價策略、個人化客戶體驗、預測需求、更有效率地管理庫存，並做出數據主導的決策，進而提高盈利和競爭力。

根據Google的零時真相 (ZMOT) 研究，70% 的消費者在店內購物前會先在網路上進行研究。

透過各種管道傳播數據

零售分析市場由線上、店內和行動通路產生的數據爆炸性成長所驅動，從而實現數據主導的決策。與電商平台和社群媒體的互動為客戶行為分析提供了豐富的資料集。物聯網設備在零售環境中的整合可以捕獲庫存和客流量的即時數據。消費者對個人化購物體驗的需求日益成長，推動了分析工具的採用。零售商正在利用這些洞察來最佳化定價、促銷和供應鏈營運。

與舊有系統整合的挑戰

許多零售商在將現代分析平台與過時的舊有系統整合時面臨困難，這阻礙了其應用。將大型資料集遷移到雲端基礎的解決方案的複雜性增加了實施成本。不同舊有系統之間資料格式不一致導致分析流程效率低落。中小企業通常缺乏管理整合的技術專業知識，從而限制了市場成長。對客製化整合解決方案的需求進一步增加了零售商的成本。這些挑戰減緩了傳統零售業對高階分析工具的採用。

人工智慧和機器學習（ML）的進步

人工智慧和機器學習在零售分析中的融合，為增強預測模型和客戶細分提供了機會。人工智慧主導的工具可以實現即時需求預測並最佳化庫存管理。機器學習演算法改進了建議引擎，提升了客戶參與和銷售量。雲端基礎人工智慧平台的日益普及，讓即使是小型零售商也能輕鬆掌握高階分析技術。這些進步有望開闢新的收益來源並提高業務效率。

數據孤島和品質低下

跨部門資料孤島阻礙零售商獲得統一的客戶和業務資料視圖。數據品質低（包括不完整或不準確的資料集）導致分析洞察不可靠。缺乏標準化的資料管治實踐使資料整合工作變得複雜。零售商面臨基於不一致或過時資訊做出錯誤決策的風險。高昂的資料清理和管理成本給中小企業帶來了挑戰。這些問題威脅著分析解決方案的有效性和市場成長。

COVID-19的影響：

新冠疫情加速了零售分析的應用，零售商紛紛轉向線上和全通路策略。封鎖措施增加了對電商的依賴，推動了追蹤線上消費行為的分析需求。供應鏈中斷促使零售商轉向分析，以最佳化庫存和預測需求。然而，商店客流量的減少最初限制了實體通路的資料收集。疫情過後，對個人化客戶體驗的關注將持續刺激市場擴張。

預計預測期內軟體部分將實現最大幅度成長。

受用於處理全通路資料的高階分析平台需求不斷成長的推動，軟體領域預計將在預測期內佔據最大的市場佔有率。 Tableau 和 Power BI 等工具可讓零售商視覺化並有效分析複雜的資料集。可擴展的雲端基礎平台讓各種規模的零售商都能輕鬆取得分析數據。對即時洞察以最佳化定價和促銷活動的需求正在推動軟體的採用。持續的更新以及與電商平台的整合進一步鞏固了該領域的主導地位。

預計在預測期內，文件和彙報部分將以最高的複合年成長率成長。

預計文件和彙報細分市場將在預測期內實現最高成長率，這得益於人工智慧和機器學習在預測消費者趨勢方面的日益普及。預測分析與 CRM 系統的整合為個人化行銷策略提供了支援。巨量資料技術投資的不斷成長支持了高級預測模型的開發。零售商正在利用這些洞察來最佳化供應鏈並提高客戶維繫。在競爭激烈的市場中，對競爭差異化的需求進一步推動了該細分市場的成長。

佔比最大的地區：

預計亞太地區將在預測期內佔據最大的市場佔有率，這得益於中國和印度等國家快速數位化和電子商務的擴張。不斷壯大的中階和智慧型手機的廣泛普及正在推動線上零售的成長。該地區的零售商正在採用分析技術來改善客戶體驗並最佳化業務。該地區精通技術的新興企業的崛起正在推動對經濟高效的分析解決方案的需求。高水準的網路連線和雲端運算的採用將進一步推動市場成長。

複合年成長率最高的地區：

預計北美將在預測期內實現最高的複合年成長率，這得益於先進的技術基礎設施和分析解決方案的廣泛應用。 IBM 和微軟等主要參與者的參與正在推動零售分析領域的創新。該地區（尤其是美國）強勁的零售業正在支持分析平台的快速普及。對雲端運算和巨量資料技術的投資正在提高解決方案的擴充性。對全通路策略和數據主導決策的關注將推動市場成長。

免費客製化服務：

訂閱此報告的客戶可享有以下免費自訂選項之一：

  • 公司簡介
    • 對其他市場公司（最多 3 家公司）進行全面分析
    • 主要企業的SWOT分析（最多3家公司）
  • 地理細分
    • 根據客戶興趣對主要國家市場進行估計、預測和複合年成長率（註：基於可行性檢查）
  • 競爭基準化分析
    • 根據產品系列、地理分佈和策略聯盟對主要企業基準化分析

目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 研究範圍
  • 調查方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 研究途徑
  • 研究材料
    • 主要研究資料
    • 次級研究資訊來源
    • 先決條件

第3章市場走勢分析

  • 驅動程式
  • 抑制因素
  • 機會
  • 威脅
  • 應用分析
  • 新興市場
  • COVID-19的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買家的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

第5章 全球零售分析市場（按解決方案）

  • 軟體
    • 軟體分析
    • 部署模式
  • 服務
    • 培訓和諮詢
    • 整合與部署
    • 託管服務

第6章 全球零售分析市場（依部署）

  • 本地
  • 雲

7. 全球零售分析市場（依零售店類型）

  • 大賣場和超級市場
  • 零售連鎖

8. 全球零售分析市場（Field Crowdsourcing）

  • 可用性
  • 文件和報告
  • 促銷宣傳活動管理
  • 客戶洞察

第9章全球零售分析市場（按應用）

  • 客戶管理
  • 店舖管理
  • 策略與規劃
  • 供應鏈管理
  • 行銷和商品行銷
  • 其他用途

第10章全球零售分析市場（按地區）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第11章 重大進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第12章 公司概況

  • SAP SE
  • IBM Corporation
  • Oracle Corporation
  • Salesforce Inc.（Tableau）
  • SAS Institute Inc.
  • QlikTech International AB
  • Microsoft Corp.（Power BI, Dynamics 365）
  • Amazon Web Services Inc.（QuickSight）
  • Google LLC（Looker）
  • Blue Yonder Inc.
  • Dunnhumby Ltd.
  • Teradata Corp.
  • RetailNext Inc.
  • Zebra Technologies Corp.
  • Altair Engineering Inc.
  • Alteryx Inc.
  • MicroStrategy Inc.
  • ThoughtSpot Inc.
  • Infor Inc.
Product Code: SMRC30115

According to Stratistics MRC, the Global Retail Analytics Market is accounted for $5.1 billion in 2025 and is expected to reach $20.4 billion by 2032 growing at a CAGR of 21.7% during the forecast period. Retail Analytics involves the use of data and quantitative methods to gain insights into customer behavior, sales trends, and operational efficiency within the retail sector. It encompasses analyzing point-of-sale data, inventory levels, customer demographics, marketing campaign effectiveness, and supply chain performance. By leveraging tools like business intelligence platforms and machine learning, retailers can optimize pricing strategies, personalize customer experiences, forecast demand, manage stock more efficiently, and make data-driven decisions to boost profitability and competitiveness.

According to Google's Zero Moment Of Truth (ZMOT) research, 70% of consumers research online before purchasing in-store.

Market Dynamics:

Driver:

Proliferation of data from diverse channels

The retail analytics market is propelled by the explosion of data generated from online, in-store, and mobile channels, enabling data-driven decision-making. E-commerce platforms and social media interactions provide rich datasets for customer behavior analysis. The integration of IoT devices in retail environments captures real-time data on inventory and foot traffic. Growing consumer demand for personalized shopping experiences drives the adoption of analytics tools. Retailers leverage these insights to optimize pricing, promotions, and supply chain operations.

Restraint:

Integration challenges with legacy systems

Many retailers face difficulties integrating modern analytics platforms with outdated legacy systems, hindering adoption. The complexity of migrating large datasets to cloud-based solutions increases implementation costs. Inconsistent data formats across legacy systems lead to inefficiencies in analytics processes. SMEs often lack the technical expertise to manage integration, limiting market growth. The need for customized integration solutions further escalates expenses for retailers. These challenges slow the deployment of advanced analytics tools in traditional retail settings.

Opportunity:

Advancements in AI and machine learning (ML)

The integration of AI and ML in retail analytics offers opportunities to enhance predictive modeling and customer segmentation. AI-driven tools enable real-time demand forecasting, optimizing inventory management. Machine learning algorithms improve recommendation engines, boosting customer engagement and sales. The growing availability of cloud-based AI platforms makes advanced analytics accessible to smaller retailers. These advancements are expected to create new revenue streams and enhance operational efficiency.

Threat:

Data silos and poor data quality

Data silos across departments prevent retailers from achieving a unified view of customer and operational data. Poor data quality, such as incomplete or inaccurate datasets, undermines the reliability of analytics insights. The lack of standardized data governance practices complicates data integration efforts. Retailers risk making flawed decisions based on inconsistent or outdated information. The high cost of data cleansing and management poses challenges for smaller firms. These issues threaten the effectiveness of analytics solutions and market growth.

Covid-19 Impact:

The COVID-19 pandemic accelerated the adoption of retail analytics as retailers pivoted to online and omnichannel strategies. Lockdowns increased reliance on e-commerce, driving demand for analytics to track online consumer behavior. Supply chain disruptions prompted retailers to use analytics for inventory optimization and demand forecasting. However, reduced in-store traffic initially limited data collection from physical channels. Post-pandemic, the focus on personalized customer experiences continues to fuel market expansion.

The software segment is expected to be the largest during the forecast period

The software segment is expected to account for the largest market share during the forecast period propelled by the growing demand for advanced analytics platforms to process omnichannel data. Tools like Tableau and Power BI enable retailers to visualize and analyze complex datasets effectively. Scalable cloud-based platforms make analytics accessible to retailers of all sizes. The need for real-time insights to optimize pricing and promotions drives software adoption. Continuous updates and integrations with e-commerce platforms further boost this segment's dominance.

The documentation & reporting segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the documentation & reporting segment is predicted to witness the highest growth rate, influenced by the increasing use of AI and ML for forecasting consumer trends. The integration of predictive analytics with CRM systems enhances personalized marketing strategies. Growing investments in big data technologies support the development of advanced predictive models. Retailers are leveraging these insights to optimize supply chains and improve customer retention. The segment's growth is further driven by the need for competitive differentiation in a crowded market.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share, fueled by rapid digitalization and the expansion of e-commerce in countries like China and India. The growing middle class and increasing smartphone penetration drive online retail growth. Retailers in the region are adopting analytics to enhance customer experiences and optimize operations. The rise of tech-savvy startups in the region fuels demand for cost-effective analytics solutions. High internet connectivity and cloud adoption further accelerate market growth.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR, driven by its advanced technological infrastructure and widespread adoption of analytics solutions. The presence of major players like IBM and Microsoft fosters innovation in retail analytics. The region's strong retail sector, particularly in the U.S., supports rapid adoption of analytics platforms. Investments in cloud computing and big data technologies enhance the scalability of solutions. The focus on omnichannel strategies and data-driven decision-making accelerates market growth.

Key players in the market

Some of the key players in Retail Analytics Market include SAP SE, IBM Corporation, Oracle Corporation, Salesforce Inc. (Tableau), SAS Institute Inc., QlikTech International AB, Microsoft Corp. (Power BI, Dynamics 365), Amazon Web Services Inc. (QuickSight), Google LLC (Looker), Blue Yonder Inc., Dunnhumby Ltd., Teradata Corp., RetailNext Inc., Zebra Technologies Corp., Altair Engineering Inc., Alteryx Inc., MicroStrategy Inc., ThoughtSpot Inc., and Infor Inc.

Key Developments:

In June 2025, SAP SE launched SAP Retail Cloud Insights, a real-time analytics dashboard offering AI-driven demand sensing and dynamic pricing tools for omnichannel retailers.

In May 2025, Salesforce Inc. (Tableau) announced native integration of Einstein AI within Tableau to enhance predictive analytics for inventory and customer engagement.

In April 2025, Microsoft Corp. expanded Power BI retail templates for supply chain visibility and in-store analytics, optimized for Dynamics 365 users.

In March 2025, QlikTech International AB introduced Qlik AutoML for retailers, helping non-technical users build and deploy machine learning models to optimize shelf placement and promotions.

Solutions Covered:

  • Software
  • Service

Deployments Covered:

  • On-Premise
  • Cloud

Retail Store Types Covered:

  • Hypermarkets & Supermarkets
  • Retail Chains

Field Crowdsourcings Covered:

  • On-shelf Availability
  • Documentation & Reporting
  • Promotion Campaign Management
  • Customer Insights

Applications Covered:

  • Customer Management
  • In-store Operation
  • Strategy & Planning
  • Supply Chain Management
  • Marketing & Merchandizing
  • Other Applications

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 Emerging Markets
  • 3.8 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Retail Analytics Market, By Solution

  • 5.1 Introduction
  • 5.2 Software
    • 5.2.1 Software Analytics
    • 5.2.2 Deployment Mode
  • 5.3 Service
    • 5.3.1 Training & Consulting
    • 5.3.2 Integration & deployment
    • 5.3.3 Managed Service

6 Global Retail Analytics Market, By Deployment

  • 6.1 Introduction
  • 6.2 On-Premise
  • 6.3 Cloud

7 Global Retail Analytics Market, By Retail Store Type

  • 7.1 Introduction
  • 7.2 Hypermarkets & Supermarkets
  • 7.3 Retail Chains

8 Global Retail Analytics Market, By Field Crowdsourcing

  • 8.1 Introduction
  • 8.2 On-shelf Availability
  • 8.3 Documentation & Reporting
  • 8.4 Promotion Campaign Management
  • 8.5 Customer Insights

9 Global Retail Analytics Market, By Application

  • 9.1 Introduction
  • 9.2 Customer Management
  • 9.3 In-store Operation
  • 9.4 Strategy & Planning
  • 9.5 Supply Chain Management
  • 9.6 Marketing & Merchandizing
  • 9.7 Other Applications

10 Global Retail Analytics Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 SAP SE
  • 12.2 IBM Corporation
  • 12.3 Oracle Corporation
  • 12.4 Salesforce Inc. (Tableau)
  • 12.5 SAS Institute Inc.
  • 12.6 QlikTech International AB
  • 12.7 Microsoft Corp. (Power BI, Dynamics 365)
  • 12.8 Amazon Web Services Inc. (QuickSight)
  • 12.9 Google LLC (Looker)
  • 12.10 Blue Yonder Inc.
  • 12.11 Dunnhumby Ltd.
  • 12.12 Teradata Corp.
  • 12.13 RetailNext Inc.
  • 12.14 Zebra Technologies Corp.
  • 12.15 Altair Engineering Inc.
  • 12.16 Alteryx Inc.
  • 12.17 MicroStrategy Inc.
  • 12.18 ThoughtSpot Inc.
  • 12.19 Infor Inc.

List of Tables

  • Table 1 Global Retail Analytics Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Retail Analytics Market Outlook, By Solution (2024-2032) ($MN)
  • Table 3 Global Retail Analytics Market Outlook, By Software (2024-2032) ($MN)
  • Table 4 Global Retail Analytics Market Outlook, By Software Analytics (2024-2032) ($MN)
  • Table 5 Global Retail Analytics Market Outlook, By Deployment Mode (2024-2032) ($MN)
  • Table 6 Global Retail Analytics Market Outlook, By Service (2024-2032) ($MN)
  • Table 7 Global Retail Analytics Market Outlook, By Training & Consulting (2024-2032) ($MN)
  • Table 8 Global Retail Analytics Market Outlook, By Integration & deployment (2024-2032) ($MN)
  • Table 9 Global Retail Analytics Market Outlook, By Managed Service (2024-2032) ($MN)
  • Table 10 Global Retail Analytics Market Outlook, By Deployment (2024-2032) ($MN)
  • Table 11 Global Retail Analytics Market Outlook, By On-Premise (2024-2032) ($MN)
  • Table 12 Global Retail Analytics Market Outlook, By Cloud (2024-2032) ($MN)
  • Table 13 Global Retail Analytics Market Outlook, By Retail Store Type (2024-2032) ($MN)
  • Table 14 Global Retail Analytics Market Outlook, By Hypermarkets & Supermarkets (2024-2032) ($MN)
  • Table 15 Global Retail Analytics Market Outlook, By Retail Chains (2024-2032) ($MN)
  • Table 16 Global Retail Analytics Market Outlook, By Field Crowdsourcing (2024-2032) ($MN)
  • Table 17 Global Retail Analytics Market Outlook, By On-shelf Availability (2024-2032) ($MN)
  • Table 18 Global Retail Analytics Market Outlook, By Documentation & Reporting (2024-2032) ($MN)
  • Table 19 Global Retail Analytics Market Outlook, By Promotion Campaign Management (2024-2032) ($MN)
  • Table 20 Global Retail Analytics Market Outlook, By Customer Insights (2024-2032) ($MN)
  • Table 21 Global Retail Analytics Market Outlook, By Application (2024-2032) ($MN)
  • Table 22 Global Retail Analytics Market Outlook, By Customer Management (2024-2032) ($MN)
  • Table 23 Global Retail Analytics Market Outlook, By In-store Operation (2024-2032) ($MN)
  • Table 24 Global Retail Analytics Market Outlook, By Strategy & Planning (2024-2032) ($MN)
  • Table 25 Global Retail Analytics Market Outlook, By Supply Chain Management (2024-2032) ($MN)
  • Table 26 Global Retail Analytics Market Outlook, By Marketing & Merchandizing (2024-2032) ($MN)
  • Table 27 Global Retail Analytics Market Outlook, By Other Applications (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.