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封面
市场调查报告书
商品编码
1800915

2025 年至 2033 年零售分析市场报告（按功能、组件、部署模式、最终用户和地区）

Retail Analytics Market Report by Function, Component, Deployment Mode, End User, and Region 2025-2033
出版日期: | 出版商: IMARC | 英文 147 Pages | 商品交期: 2-3个工作天内

价格

2024年，全球零售分析市场规模达104亿美元。展望未来， IMARC Group预计到2033年，该市场规模将达到452亿美元，2025-2033年期间的复合年增长率（CAGR）为16.92%。得益于先进的技术基础设施和主要零售企业的强大影响力，北美引领市场。零售分析市场正在经历显着成长，这得益于企业数位化程度的不断提升、云端零售分析解决方案的使用日益增多，以及消费者为了节省时间和金钱而逐渐养成的线上购物习惯。

零售分析产业正在经历巨大的变革，其动力源于企业对资料在策略选择和业务流程改进方面的日益依赖。永续性正迅速成为主流零售策略，而分析技术正助力环境监测和报告。零售商正在量化碳足迹、报告能源消耗，并评估供应链合作伙伴的可持续性。分析技术也支援诸如减少浪费、推荐绿色产品和道德采购等措施。透过将分析技术与永续发展目标相结合，零售商正在创造更强大的品牌声誉，并满足客户对负责任经营的期望。

零售分析市场趋势：

对个人化客户体验的需求日益增长

零售商不断强调为客户提供高度个人化的体验，这极大地推动了零售分析解决方案的应用。因此，许多公司正在推出个人化零售解决方案。例如，苹果公司于2025年在印度推出了「影片专家购物」（Shop with a Specialist over Video）服务，用户可以在苹果商店线上购买苹果产品。透过收集来自多种来源的信息，例如在线浏览历史、购买习惯、忠诚度计划和社交媒体使用情况，企业正在製定高度客製化的行销方案。零售分析解决方案正在帮助零售商更有效地细分购物者，预测他们的喜好，并据此提供个人化的产品推荐和优惠。随着顾客对个人化购物的期望不断提高，零售商正在使用先进的分析解决方案来提高参与度和满意度。即时个人化正成为竞争优势，企业利用动态定价和个人化优惠来提升销售量。零售商还将人工智慧和机器学习嵌入到分析平台中，以提高准确性并实现决策自动化。随着全通路零售的蓬勃发展，这一趋势正在加速发展，分析平台不断收集实体和数位管道的资料，以优化客户旅程。

电子商务和数位管道的突然繁荣

线上零售和数位通路的持续成长产生了大量资料，促使零售商采用高级分析技术来解读这些数据。随着越来越多的客户转向线上购物，零售商正在收集有关客户行为的丰富信息，例如点击率、购物车放弃率、会话时长和重复访问次数。零售分析软体现在被用于即时监控这些线上互动，以便公司可以改善网站设计、提高产品曝光度并改善用户体验。随着行动购物和基于应用程式的零售业的兴起，分析潜力在各种数位平台上不断扩大。零售商正在利用资料洞察来增强客户获取、提高留存率并改善他们的数位行销活动。在这种不断变化的情况下，即时分析开始成为追踪关键绩效指标 (KPI)、识别市场趋势和提前对客户行为做出反应的必需品。 IMARCIMARC Group预测，到 2033 年，全球电子商务市场规模预计将达到 214.5 兆美元。

人工智慧 (AI) 和机器学习 (ML) 的进步

人工智慧 (AI) 和机器学习 (ML) 技术正在彻底改变零售分析产业，帮助企业获得更深入的洞察并实现复杂流程的自动化。零售商正积极运用基于 AI 的分析解决方案来预测需求、识别诈欺行为并精准识别新兴趋势。 ML 演算法持续处理巨量资料集，以识别潜在模式、最佳化定价策略并即时推荐产品。这些技术还透过智慧聊天机器人和虚拟助理改变客户服务，它们基于数据驱动的洞察来回答客户问题并促成购买。零售商正在利用 AI 预测库存需求并减少浪费，从而增强库存管理。此外，由 AI 支援的规范分析能够根据预测结果推荐最佳行动方案，从而促进更具策略性的决策。随着这些技术的不断发展，零售商正在投资 AI 驱动的分析技术，以在瞬息万变的市场格局中保持竞争力和敏捷性。 Standard AI 于 2025 年推出了 Vision Analytics，透过对个人、产品和互动的清晰洞察，为零售商和品牌提供消费者行为、产品有效性和门市营运方面的洞察。

零售分析市场成长动力：

全通路零售策略整合

零售商正在积极采用全通路零售策略，而数据分析是他们跨不同接触点提供无缝客户体验的核心。顾客在多通路环境中与品牌互动，包括实体店互动、网站互动、智慧型手机应用互动和社群媒体互动。零售商正在从所有这些来源收集资料，以建立客户体验的综合视图。零售分析解决方案使企业能够监控跨通路行为，确定客户流失点，并最大限度地提高通路绩效。例如，在线上浏览的顾客随后会进入实体店进行购买，分析平台正在监控此类行为，以影响行销和销售工作。商店还利用全通路分析来协调促销活动、进行跨通路库存管理并优化订单履行效率。这种方法使企业能够协调其行销、营运和客户服务计划，最终最大限度地提高品牌一致性和消费者满意度。随着数位零售和实体零售这两个领域的不断融合，全通路分析的应用正在稳步加速。

供应链优化和有效库存管理

零售商不断应用分析技术，以更好地优化供应链营运和库存管理，这是市场的另一个关键驱动力。在客户对快速准确地交付产品的期望不断提高的时代，即时资料洞察被用于预测需求、审查库存数量并更有效地管理物流。零售分析软体正在监控仓库和门市之间的产品流动，帮助企业减少库存积压、最大限度地减少缺货并提高补货准确性。预测模型被用于根据过往业绩和季节性模式确定最佳订单规模和配送计划。零售商还利用地理空间分析技术，透过优化仓库位置和配送路线来最大限度地降低运输成本并最大限度地提高服务水准。分析技术也被用于追踪供应商的绩效、监控交货时间并评估供应链中的风险。透过在采购和库存计划中进行数据驱动的决策，零售商正在提高营运效率和获利能力。在全球消费者需求不断变化和供应链中断的环境下，这些能力变得越来越必要。

越来越多地使用基于云端的分析解决方案

零售商越来越多地使用基于云端的分析平台，因为它们具有可扩展、灵活且经济高效的特性。这些平台使公司无需繁重的内部部署基础架构即可撷取、处理和分析大量资料。基于云端的零售分析解决方案提供即时洞察、更快部署以及与当前企业系统更简单的整合。公司正在使用这些解决方案进行跨部门协作、远端存取资料并确保报告的一致性。迁移到云端也加强了资料安全性和合规性，因为顶级供应商提供高强度加密并遵守全球资料隐私法规。云端平台还透过以使用付费的方式提供高阶运算功能，使使用 AI 和 ML 变得容易。零售商从基于订阅的选项中获益，这些选项可以最大限度地减少初始投资，并提高扩展灵活性。随着数位转型的步伐加快，基于云端的分析正在成为零售业创新和竞争差异化的关键驱动力。

零售分析市场细分：

按功能分类：

  • 客户管理
  • 店内营运
  • 策略与规划
  • 供应链管理
  • 行销和行销
  • 其他的

客户管理占据大部分市场份额

由于个人化客户体验的需求日益增长，以及在竞争激烈的零售环境中客户忠诚度和保留率的战略意义，客户管理在零售分析市场中占据主导地位。零售商可以透过分析深入了解客户行为、偏好和购买习惯，从而提供客製化行销、改善客户互动并扩展服务范围。例如，美国人口普查局的资料展现了零售额和电商趋势的重要洞察，这对于零售分析中的客户管理至关重要。此外，年度零售贸易调查提供了各零售业的详细年度销售额、电商销售额和库存数据。这可以帮助企业了解消费者的购买模式，并据此调整客户管理策略。这种数据驱动的策略有助于识别有价值的客户，预测他们未来的购买模式，并制定有效的忠诚度计划。此外，透过促进即时决策和预测分析，人工智慧 (AI) 和机器学习等技术的结合，进一步增强了这些技术的有效性。

按组件细分：

  • 软体
  • 服务

软体占产业最大份额

软体在零售分析行业中占据主导地位，因为它对于将大量资料转化为可付诸实践的洞察至关重要，从而帮助零售商做出更明智的决策。美国人口普查局报告称，2021年第一季度，电子商务销售额占总销售额的近13%，凸显了分析在最大化线上销售策略方面的重要性。在当今数据驱动的市场环境下，零售分析软体为客户行为监控、库存管理和销售预测提供了广泛的解决方案。美国劳工统计局指出，零售业数位化营运的应用日益广泛，这需要先进的分析解决方案来管理当代零售营运的范围和复杂性。

依部署模式分类：

  • 本地
  • 基于云端

基于云端的代表领先的细分市场

基于云端的解决方案具备可扩展性、灵活性和经济实惠的优势——这些对于管理当代零售营运产生的大量资料至关重要——因此对零售分析行业的前景产生了积极的影响。零售商能够有效率地应对购物高峰期，因为他们可以根据需要灵活地增加或减少资源。美国小型企业管理局的一项调查指出，由于云端运算可以降低IT管理费用并提高营运效率，中小型企业正在以越来越快的速度采用云端运算。这种变化对零售业尤其重要，因为市场环境的变化需要即时资料处理和分析。云端系统透过提供资料储存和复杂的分析功能，无需大量的初始资金投入，实现了这一点。

按最终用户分类：

  • 中小企业
  • 大型企业

大型企业市场主导地位明显

由于其庞大的营运范围和其所监管的复杂资料环境，大型组织在终端用户零售分析市场中占据主导地位。这些公司拥有投资尖端零售分析解决方案的基础设施和财力，这对于管理众多通路和地区产生的大量资料至关重要。大型企业可以透过整合和分析这些资料来深入了解市场趋势、供应链效率和消费者行为。策略规划、国际市场竞争力和营运优化都取决于这种程度的分析。大型企业还可以经常使用更高级的分析方法，例如人工智慧驱动的工具和预测模型，以刺激创新并提升消费者体验。

按地区划分：

  • 北美洲
    • 美国
    • 加拿大
  • 亚太地区
    • 中国
    • 日本
    • 印度
    • 韩国
    • 澳洲
    • 印尼
    • 其他的
  • 欧洲
    • 德国
    • 法国
    • 英国
    • 义大利
    • 西班牙
    • 俄罗斯
    • 其他的
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 其他的
  • 中东和非洲

北美引领市场，占据最大的零售分析市场份额

该报告还对所有主要区域市场进行了全面分析，包括北美（美国和加拿大）；亚太地区（中国、日本、印度、韩国、澳洲、印尼等）；欧洲（德国、法国、英国、义大利、西班牙、俄罗斯等）；拉丁美洲（巴西、墨西哥等）；以及中东和非洲。报告指出，北美是零售分析领域中最大的市场。

北美凭藉其先进的技术基础设施、巨量资料解决方案的广泛应用以及对人工智慧 (AI) 和机器学习的大量投资，在零售分析市场占据主导地位。美国商务部报告称，2019 年北美零售电商销售额较 2020 年增长 32.4%，显示该行业正在快速扩张，对高阶分析的需求也日益增长。大型数位组织和新创公司专注于提供零售分析解决方案，以提升客户体验和营运效率，并将这一地区视为大本营。美国经济分析局的数据显示，零售业的数位转型推动了对用于了解消费者行为、管理库存和改善供应链的分析需求。这进一步催化了零售分析市场的成长。

（请注意，这只是关键参与者的部分列表，完整列表在报告中提供。）

  • 零售分析领域的一些领先公司，例如微软公司、富士通有限公司、Flir Systems Inc.、Altair Engineering Inc.、Adobe Inc. 和 1010data Inc.，都在不断改进其产品，以提高零售分析市场的价值。 1010data Inc. 是一家基于云端的分析供应商，非常重视零售营运优化。 Adobe Inc. 透过其先进的 Adob​​e Analytics 平台提供客製化的数位行销解决方案。零售商可以在将分析融入产品设计的 Altair Engineering Inc. 的帮助下加强供应链和库存管理。 Flir Systems Inc. 使用尖端的热成像技术来深入了解客户行为和安全性。富士通有限公司提供完整的零售解决方案，例如数据驱动的销售点系统。微软公司正在利用尖端的人工智慧和基于云端的技术来提高客户参与度，从而推进购物体验的个人化。总的来说，这些企业正在为复杂的数据驱动零售策略铺路。例如，Adobe Experience Platform 提供了客户旅程分析等新工具，零售商现在可以利用 AI 来侦测不良体验（或发现新的商机）。此次更新将异常检测扩展到了网站之外（此前，网站是其主要应用领域），并允许品牌在购物者跨渠道购物时发现问题所在。

本报告回答的关键问题

  • 2024 年全球零售分析市场规模是多少
  • 2025-2033年全球零售分析市场的预期成长率是多少
  • 推动全球零售分析市场的关键因素有哪些
  • COVID-19 对全球零售分析市场有何影响
  • 根据功能，全球零售分析市场如何划分
  • 根据组成部分，全球零售分析市场如何划分
  • 根据部署模式，全球零售分析市场如何划分
  • 根据最终用户，全球零售分析市场如何划分
  • 全球零售分析市场的主要区域有哪些
  • 10. 全球零售分析市场的主要参与者/公司有哪些？

本报告回答的关键问题

  • 2024年全球零售分析市场规模？ 2025-2033年全球零售分析市场的预期成长率是多少？
  • 推动全球零售分析市场发展的关键因素有哪些？
  • COVID-19 对全球零售分析市场有何影响？
  • 根据功能，全球零售分析市场是如何分類的？
  • 根据组成部分，全球零售分析市场是如何分類的？
  • 根据部署模式，全球零售分析市场如何划分？
  • 根据最终用户，全球零售分析市场是如何分類的？
  • 全球零售分析市场的关键区域有哪些？
  • 全球零售分析市场的主要参与者/公司有哪些？

目录

第一章：前言

第二章：范围与方法

  • 研究目标
  • 利害关係人
  • 资料来源
    • 主要来源
    • 次要来源
  • 市场评估
    • 自下而上的方法
    • 自上而下的方法
  • 预测方法

第三章：执行摘要

第四章：简介

第五章：全球零售分析市场

  • 市场概览
  • 市场表现
  • COVID-19的影响
  • 市场预测

第六章：市场区隔：依功能

  • 客户管理
  • 店内营运
  • 策略与规划
  • 供应链管理
  • 行销和行销
  • 其他的

第七章：市场区隔：依组成部分

  • 软体
  • 服务

第八章：市场区隔：依部署模式

  • 本地
  • 基于云端

第九章：市场区隔：依最终用户

  • 中小企业
  • 大型企业

第十章：市场细分：按地区

  • 北美洲
    • 美国
    • 加拿大
  • 亚太地区
    • 中国
    • 日本
    • 印度
    • 韩国
    • 澳洲
    • 印尼
    • 其他的
  • 欧洲
    • 德国
    • 法国
    • 英国
    • 义大利
    • 西班牙
    • 俄罗斯
    • 其他的
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 其他的
  • 中东和非洲

第 11 章：SWOT 分析

第 12 章：价值链分析

第 13 章：波特五力分析

第 14 章：价格分析

第 15 章：竞争格局

  • 市场结构
  • 关键参与者
  • 关键参与者简介
    • 1010data Inc. (Advance Publications Inc.)
    • Adobe Inc.
    • Altair Engineering Inc.
    • Flir Systems Inc.
    • Fujitsu Limited
    • International Business Machines Corporation
    • Information Builders Inc.
    • Microsoft Corporation
    • Microstrategy Incorporated
    • Oracle Corporation
    • Qlik Technologies Inc. (Thoma Bravo LLC)
    • SAP SE
    • SAS Institute Inc.
    • Tableau Software LLC (Salesforce.com Inc.)
    • Tibco Software Inc.
Product Code: SR112025A2372

The global retail analytics market size reached USD 10.4 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 45.2 Billion by 2033, exhibiting a growth rate (CAGR) of 16.92% during 2025-2033. North America leads the market, driven by advanced technology infrastructure and the strong presence of major retail players. The retail analytics market is experiencing significant growth driven by the expanding digitization in organizations, rising use of cloud-based retail analytics solutions, and growing online shopping habits of consumers looking to save time and money.

The retail analytics industry is experiencing strong change, fueled by growing dependence on data for strategic choice and business process improvement. Sustainability is fast becoming mainstream retail strategy, and analytics is helping to monitor and report on the environment. Retailers are quantifying carbon footprints, reporting on energy consumption, and assessing the sustainability of supply chain partners. Analytics is also backing efforts like waste reduction, green product recommendations, and ethical sourcing. By integrating analytics with sustainable objectives, retailers are building a stronger brand reputation as well as addressing customer expectations for responsible business.

Retail Analytics Market Trends:

Growing Need for Personalized Customer Experience

Retailers are constantly emphasizing providing customers with very personalized experiences, and this is greatly pushing the usage of retail analytics solutions. As a result, a lot of companies are launching personalized retail solutions. For example, in 2025, Apple introduced Shop with a Specialist over Video in India, where people can shop online for apple products on the Apple Store. By gathering information from multiple sources like online surfing history, buying habits, loyalty schemes, and social media usage, companies are creating highly tailored marketing programs. Retail analytics solutions are assisting retailers to segment shoppers more efficiently, forecast tastes, and personalize product suggestions and offers based on that. With rising expectations for personalized shopping among customers, retailers are using sophisticated analytics solutions to drive engagement and satisfaction. Real-time personalization is emerging as a competitive advantage, with companies leveraging dynamic pricing and personalized offers to boost sales. Retailers are also embedding AI and ML into analytics platforms to improve accuracy and automate decision-making. The trend is speeding up as omnichannel retail gains momentum, with analytics platforms constantly gathering data both in physical and digital channels to optimize the customer journey.

Sudden Boom in E-Commerce and Digital Channels

The continuing growth of online retailing and digital channels is creating vast amounts of data, leading retailers to embrace advanced analytics to decipher it. With customers increasingly turning to online shopping, retailers are gathering rich information about customer behavior, such as click-through rates, cart abandonment, session length, and repeat visits. Retail analytics software is now being employed to monitor these online interactions in real-time so that companies can enhance website designs, enhance product exposure, and make user experience even better. With mobile shopping and app-based retailing also increasing, the analytics potential is expanding on various digital platforms. Retailers are utilizing data insights to enhance customer acquisition, increase retention rates, and refine their digital marketing campaigns. In this changing scenario, real-time analytics is starting to become a necessity to track key performance indicators (KPIs), identify market trends, and react in advance to customer behavior. IMARC Group predicts that the global e-commerce market is projected to attain USD 214.5 Trillion by 2033.

Artificial Intelligence (AI) and Machine Learning (ML) advancements

Artificial intelligence (AI) and machine learning (ML) technologies are revolutionizing the retail analytics industry, helping businesses gain deeper insights and automate intricate processes. Retailers are using AI-based analytics solutions actively to predict demand, identify fraud, and recognize emerging trends with great accuracy. ML algorithms are constantly working on big data sets to identify underlying patterns, refine pricing strategies, and suggest products in real-time. These technologies are also changing customer service with smart chatbots and virtual assistants, which are answering customer questions and facilitating purchases based on data-driven insights. Retailers are using AI to enhance inventory management by forecasting stock needs and reducing waste. Also, prescriptive analytics enabled by AI is facilitating more strategic decision-making by recommending the optimal course of action based on predictive outcomes. As these technologies proceed to advance, retailers are investing in AI-powered analytics to remain competitive and agile in an ever-changing market landscape. In 2025, Standard AI launched Vision Analytics empowers retailers and brands with insights into consumer behavior, product effectiveness, and store operations obtained through unmatched clarity of individuals, products, and interactions.

Retail Analytics Market Growth Drivers:

Omnichannel Retail Strategies Integration

Omnichannel retail strategies are being picked up by retailers in earnest, and analytics is at the center of their ability to provide seamless customer experiences across various touch points. Customers are interacting with brands in a multichannel environment combining physical interaction, website interaction, smartphone app interaction, and social media interaction, and retailers are gathering data from all these sources to build an integrated view of the customer experience. Retail analytics solutions are allowing companies to monitor behavior across channels, determine drop-off points, and maximize channel performance. For instance, a customer who is browsing online will subsequently come into a store to make a purchase, and analytics platforms are monitoring such behaviors to influence marketing and sales efforts. Stores are also leveraging omnichannel analytics for coordinating promotions, for cross-channel inventory management, and optimizing the efficiency of fulfillment. Such an approach is allowing companies to align their marketing, operations, and customer service initiatives to ultimately maximize brand consistency and consumer satisfaction. As the two worlds of digital and physical retail continue to merge, adoption of omnichannel analytics continues to gain speed steadily.

Supply Chain Optimization and Effective Inventory Management

Retailers are continuously applying analytics for better optimization of supply chain operations and inventory management, which is another key driver of the market. In an era of rising customer expectations to speedily and accurately deliver products, real-time data insights are being used to forecast demand, review stock quantities, and manage logistics more efficiently. Retail analytics software is monitoring product flow between warehouses and stores, allowing companies to cut overstocking, minimize stockouts, and improve replenishment accuracy. Predictive models are being used to determine the best order sizes and distribution schedules based on past performance and seasonal patterns. Geospatial analytics are also being employed by retailers to minimize transportation expenses and maximize service levels by optimizing warehouse positions and delivery routes. Analytics is also being utilised to track performance of suppliers, monitor lead times, and assess risks in supply chains. Through data-driven decision-making in procurement and inventory planning, retailers are enhancing operational effectiveness as well as profitability. These capabilities are becoming more of a necessity in an environment of changing consumer demand and supply chain disruptions across the world.

Increasing Use of Cloud-Based Analytics Solutions

Retailers are increasingly using cloud-based analytics platforms because they are scalable, flexible, and cost-effective. These platforms are allowing companies to capture, process, and analyze huge amounts of data without the need for heavy on-premise infrastructure. Cloud-based retail analytics solutions are giving real-time insights, quicker deployment, and simpler integration with current enterprise systems. Companies are using these solutions to work inter-departmentally, get remote access to data, and ensure consistency of reports. The move to cloud is also tightening data security and compliance because top vendors provide high-strength encryption and follow global data privacy regulations. Cloud platforms are also making it easy to use AI and ML by providing high-end computing capabilities on a pay-as-you-use basis. Retailers are gaining from subscription-based options that minimize initial investment and enable more agility in scaling up. As digital transformation gathers pace, cloud-based analytics is emerging as a key driver of innovation and competitive differentiation in retail.

Retail Analytics Market Segmentation:

Breakup by Function:

  • Customer Management
  • In-store Operation
  • Strategy and Planning
  • Supply Chain Management
  • Marketing and Merchandizing
  • Others

Customer management accounts for the majority of the market share

Due to the growing demand for individualized customer experiences and the strategic significance of customer loyalty and retention in a cutthroat retail environment, customer management leads the retail analytics market by function. Retailers may deliver customized marketing, improve customer interactions, and expand their service offerings by using analytics to obtain deep insights into customer behaviors, preferences, and purchasing habits. For instance, the Census Bureau data shows significant insights into retail sales and e-commerce trends which are crucial for customer management in retail analytics. In addition, the Annual Retail Trade Survey provides detailed annual sales, e-commerce sales, and inventories across various retail sectors. This can help businesses understand consumer buying patterns and adapt their customer management strategies accordingly. This data-driven strategy aids in the identification of valuable clients, forecasting their future purchasing patterns and putting in place efficient loyalty schemes. Furthermore, by facilitating real-time decision-making and predictive analytics, the incorporation of technologies like artificial intelligence (AI) and machine learning further augments the efficacy of these techniques.

Breakup by Component:

  • Software
  • Services

Software holds the largest share of the industry

Software dominates the retail analytics industry as it is crucial to turning massive volumes of data into insights that can be put into practice, which helps retailers make better decisions. The U.S. Census Bureau reports that in Q12021, e-commerce sales made up almost 13% of overall sales, highlighting the significance of analytics in maximizing online sales tactics. In today's data-driven market climate, retail analytics software offers extensive solutions for customer behavior monitoring, inventory management, and sales forecasting. The growing use of digital operations in retail, as noted by the Bureau of Labor Statistics, calls for advanced analytics solutions to manage the scope and intricacy of contemporary retail operations.

Breakup by Deployment Mode:

  • On-premises
  • Cloud-based

Cloud-based represents the leading market segment

Due to their scalability, flexibility, and affordability-all of which are critical for managing the enormous volumes of data created by contemporary retail operations-cloud-based solutions provide a positive impact on the retail analytics industry outlook. Retailers are able to efficiently handle peak shopping periods because they have the flexibility to scale resources up or down as needed. A U.S. Small Business Administration survey states that as cloud computing can lower IT overhead expenses and increase operational efficiency, small and medium-sized firms are adopting it at an increasing rate. This change is particularly important for the retail industry, where real-time data processing and analytics are required due to changing market conditions. Cloud systems make this possible by offering data storage and sophisticated analysis capabilities without requiring a substantial initial outlay of funds.

Breakup by End User:

  • Small and Medium Enterprises
  • Large Enterprises

Large enterprises exhibit a clear dominance in the market

Due to their vast operational scope and the intricate data environments, they oversee, large organizations hold a dominant position in the end-user retail analytics market. These companies possess the infrastructure and financial means to invest in cutting-edge retail analytics solutions, which are essential for managing the enormous volumes of data produced across numerous channels and regions. Large businesses may learn a great deal about market trends, supply chain efficiency, and consumer behavior by integrating and analyzing this data. Strategic planning, competitiveness in international markets, and operational optimization all depend on this degree of analytics. Large businesses can also frequently use more advanced analytics, such as AI-driven tools and predictive modeling, to spur innovation and enhance consumer experiences.

Breakup By Region:

  • North America
    • United States
    • Canada
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Others
  • Europe
    • Germany
    • France
    • United Kingdom
    • Italy
    • Spain
    • Russia
    • Others
  • Latin America
    • Brazil
    • Mexico
    • Others
  • Middle East and Africa

North America leads the market, accounting for the largest retail analytics market share

The report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America represented the largest market for retail analytics.

North America dominates the retail analytics market due to its sophisticated technological infrastructure, there has been a widespread use of big data solutions, and large investments in artificial intelligence (AI) and machine learning. The U.S. Department of Commerce reports that North American retail e-commerce sales increased 32.4% in 2019 compared to 2020, indicating the sector's rapid expansion and the growing demand for advanced analytics. Large digital organizations and startups that specialize in retail analytics solutions to improve customer experiences and operational efficiency call this region home. According to the U.S. Bureau of Economic Analysis, the demand for analytics to comprehend consumer behavior, manage inventory, and improve supply chains is driven by the digital transformation in retail. This is further catalyzing the retail analytics market growth.

Competitive Landscape:

  • The retail analytics market research report has also provided a comprehensive analysis of the competitive landscape in the market. Detailed profiles of all major companies have also been provided. Some of the major market players in the retail analytics industry include 1010data Inc. (Advance Publications Inc.), Adobe Inc., Altair Engineering Inc., Flir Systems Inc., Fujitsu Limited, International Business Machines Corporation, Information Builders Inc., Microsoft Corporation, Microstrategy Incorporated, Oracle Corporation, Qlik Technologies Inc. (Thoma Bravo LLC), SAP SE, SAS Institute Inc., Tableau Software LLC (Salesforce.com Inc.), Tibco Software Inc, etc.

(Please note that this is only a partial list of the key players, and the complete list is provided in the report.)

  • Some of the leading companies in the retail analytics space, such as Microsoft Corporation, Fujitsu Limited, Flir Systems Inc., Altair Engineering Inc., Adobe Inc., and 1010data Inc., are constantly improving their products to increase the retail analytics market value. 1010data Inc. is a cloud-based analytics provider with a strong emphasis on retail operations optimization. Adobe Inc. provides customized digital marketing solutions through its advanced Adobe Analytics platform. Retailers can enhance supply chain and inventory management with the assistance of Altair Engineering Inc., which incorporates analytics into product design. Flir Systems Inc. uses cutting-edge thermal imaging technology to gain insights into customer behavior and security. Complete retail solutions, such as data-driven point-of-sale systems, are provided by Fujitsu Limited. Microsoft Corporation, is advancing the personalization of shopping experiences by leveraging cutting-edge AI and cloud-based technologies to improve customer engagement. Collectively, these businesses are paving the way for sophisticated, data-driven retail strategy. For instance, Adobe Experience Platform delivered new tools such as customer journey analytics with which retailers can now leverage AI to detect broken experiences (or to uncover new opportunities). This update takes anomaly detection beyond the website - where it has been predominantly used - and allows brands to see where issues arise as shoppers move between channels.

Key Questions Answered in This Report

  • 1.What was the size of the global retail analytics market in 2024?
  • 2.What is the expected growth rate of the global retail analytics market during 2025-2033?
  • 3.What are the key factors driving the global retail analytics market?
  • 4.What has been the impact of COVID-19 on the global retail analytics market?
  • 5.What is the breakup of the global retail analytics market based on the function?
  • 6.What is the breakup of the global retail analytics market based on the component?
  • 7.What is the breakup of the global retail analytics market based on the deployment mode?
  • 8.What is the breakup of the global retail analytics market based on the end user?
  • 9.What are the key regions in the global retail analytics market?
  • 10.Who are the key players/companies in the global retail analytics market?

Table of Contents

1 Preface

2 Scope and Methodology

  • 2.1 Objectives of the Study
  • 2.2 Stakeholders
  • 2.3 Data Sources
    • 2.3.1 Primary Sources
    • 2.3.2 Secondary Sources
  • 2.4 Market Estimation
    • 2.4.1 Bottom-Up Approach
    • 2.4.2 Top-Down Approach
  • 2.5 Forecasting Methodology

3 Executive Summary

4 Introduction

  • 4.1 Overview
  • 4.2 Key Industry Trends

5 Global Retail Analytics Market

  • 5.1 Market Overview
  • 5.2 Market Performance
  • 5.3 Impact of COVID-19
  • 5.4 Market Forecast

6 Market Breakup by Function

  • 6.1 Customer Management
    • 6.1.1 Market Trends
    • 6.1.2 Market Forecast
  • 6.2 In-store Operation
    • 6.2.1 Market Trends
    • 6.2.2 Market Forecast
  • 6.3 Strategy and Planning
    • 6.3.1 Market Trends
    • 6.3.2 Market Forecast
  • 6.4 Supply Chain Management
    • 6.4.1 Market Trends
    • 6.4.2 Market Forecast
  • 6.5 Marketing and Merchandizing
    • 6.5.1 Market Trends
    • 6.5.2 Market Forecast
  • 6.6 Others
    • 6.6.1 Market Trends
    • 6.6.2 Market Forecast

7 Market Breakup by Component

  • 7.1 Software
    • 7.1.1 Market Trends
    • 7.1.2 Market Forecast
  • 7.2 Services
    • 7.2.1 Market Trends
    • 7.2.2 Market Forecast

8 Market Breakup by Deployment Mode

  • 8.1 On-premises
    • 8.1.1 Market Trends
    • 8.1.2 Market Forecast
  • 8.2 Cloud-based
    • 8.2.1 Market Trends
    • 8.2.2 Market Forecast

9 Market Breakup by End User

  • 9.1 Small and Medium Enterprises
    • 9.1.1 Market Trends
    • 9.1.2 Market Forecast
  • 9.2 Large Enterprises
    • 9.2.1 Market Trends
    • 9.2.2 Market Forecast

10 Market Breakup by Region

  • 10.1 North America
    • 10.1.1 United States
      • 10.1.1.1 Market Trends
      • 10.1.1.2 Market Forecast
    • 10.1.2 Canada
      • 10.1.2.1 Market Trends
      • 10.1.2.2 Market Forecast
  • 10.2 Asia Pacific
    • 10.2.1 China
      • 10.2.1.1 Market Trends
      • 10.2.1.2 Market Forecast
    • 10.2.2 Japan
      • 10.2.2.1 Market Trends
      • 10.2.2.2 Market Forecast
    • 10.2.3 India
      • 10.2.3.1 Market Trends
      • 10.2.3.2 Market Forecast
    • 10.2.4 South Korea
      • 10.2.4.1 Market Trends
      • 10.2.4.2 Market Forecast
    • 10.2.5 Australia
      • 10.2.5.1 Market Trends
      • 10.2.5.2 Market Forecast
    • 10.2.6 Indonesia
      • 10.2.6.1 Market Trends
      • 10.2.6.2 Market Forecast
    • 10.2.7 Others
      • 10.2.7.1 Market Trends
      • 10.2.7.2 Market Forecast
  • 10.3 Europe
    • 10.3.1 Germany
      • 10.3.1.1 Market Trends
      • 10.3.1.2 Market Forecast
    • 10.3.2 France
      • 10.3.2.1 Market Trends
      • 10.3.2.2 Market Forecast
    • 10.3.3 United Kingdom
      • 10.3.3.1 Market Trends
      • 10.3.3.2 Market Forecast
    • 10.3.4 Italy
      • 10.3.4.1 Market Trends
      • 10.3.4.2 Market Forecast
    • 10.3.5 Spain
      • 10.3.5.1 Market Trends
      • 10.3.5.2 Market Forecast
    • 10.3.6 Russia
      • 10.3.6.1 Market Trends
      • 10.3.6.2 Market Forecast
    • 10.3.7 Others
      • 10.3.7.1 Market Trends
      • 10.3.7.2 Market Forecast
  • 10.4 Latin America
    • 10.4.1 Brazil
      • 10.4.1.1 Market Trends
      • 10.4.1.2 Market Forecast
    • 10.4.2 Mexico
      • 10.4.2.1 Market Trends
      • 10.4.2.2 Market Forecast
    • 10.4.3 Others
      • 10.4.3.1 Market Trends
      • 10.4.3.2 Market Forecast
  • 10.5 Middle East and Africa
    • 10.5.1 Market Trends
    • 10.5.2 Market Breakup by Country
    • 10.5.3 Market Forecast

11 SWOT Analysis

  • 11.1 Overview
  • 11.2 Strengths
  • 11.3 Weaknesses
  • 11.4 Opportunities
  • 11.5 Threats

12 Value Chain Analysis

13 Porters Five Forces Analysis

  • 13.1 Overview
  • 13.2 Bargaining Power of Buyers
  • 13.3 Bargaining Power of Suppliers
  • 13.4 Degree of Competition
  • 13.5 Threat of New Entrants
  • 13.6 Threat of Substitutes

14 Price Analysis

15 Competitive Landscape

  • 15.1 Market Structure
  • 15.2 Key Players
  • 15.3 Profiles of Key Players
    • 15.3.1 1010data Inc. (Advance Publications Inc.)
      • 15.3.1.1 Company Overview
      • 15.3.1.2 Product Portfolio
    • 15.3.2 Adobe Inc.
      • 15.3.2.1 Company Overview
      • 15.3.2.2 Product Portfolio
      • 15.3.2.3 Financials
      • 15.3.2.4 SWOT Analysis
    • 15.3.3 Altair Engineering Inc.
      • 15.3.3.1 Company Overview
      • 15.3.3.2 Product Portfolio
      • 15.3.3.3 Financials
    • 15.3.4 Flir Systems Inc.
      • 15.3.4.1 Company Overview
      • 15.3.4.2 Product Portfolio
      • 15.3.4.3 Financials
      • 15.3.4.4 SWOT Analysis
    • 15.3.5 Fujitsu Limited
      • 15.3.5.1 Company Overview
      • 15.3.5.2 Product Portfolio
      • 15.3.5.3 Financials
      • 15.3.5.4 SWOT Analysis
    • 15.3.6 International Business Machines Corporation
      • 15.3.6.1 Company Overview
      • 15.3.6.2 Product Portfolio
      • 15.3.6.3 Financials
      • 15.3.6.4 SWOT Analysis
    • 15.3.7 Information Builders Inc.
      • 15.3.7.1 Company Overview
      • 15.3.7.2 Product Portfolio
    • 15.3.8 Microsoft Corporation
      • 15.3.8.1 Company Overview
      • 15.3.8.2 Product Portfolio
      • 15.3.8.3 Financials
      • 15.3.8.4 SWOT Analysis
    • 15.3.9 Microstrategy Incorporated
      • 15.3.9.1 Company Overview
      • 15.3.9.2 Product Portfolio
      • 15.3.9.3 Financials
      • 15.3.9.4 SWOT Analysis
    • 15.3.10 Oracle Corporation
      • 15.3.10.1 Company Overview
      • 15.3.10.2 Product Portfolio
      • 15.3.10.3 Financials
      • 15.3.10.4 SWOT Analysis
    • 15.3.11 Qlik Technologies Inc. (Thoma Bravo LLC)
      • 15.3.11.1 Company Overview
      • 15.3.11.2 Product Portfolio
    • 15.3.12 SAP SE
      • 15.3.12.1 Company Overview
      • 15.3.12.2 Product Portfolio
      • 15.3.12.3 Financials
      • 15.3.12.4 SWOT Analysis
    • 15.3.13 SAS Institute Inc.
      • 15.3.13.1 Company Overview
      • 15.3.13.2 Product Portfolio
      • 15.3.13.3 SWOT Analysis
    • 15.3.14 Tableau Software LLC (Salesforce.com Inc.)
      • 15.3.14.1 Company Overview
      • 15.3.14.2 Product Portfolio
    • 15.3.15 Tibco Software Inc.
      • 15.3.15.1 Company Overview
      • 15.3.15.2 Product Portfolio
      • 15.3.15.3 SWOT Analysis

List of Figures

  • Figure 1: Global: Retail Analytics Market: Major Drivers and Challenges
  • Figure 2: Global: Retail Analytics Market: Sales Value (in Billion USD), 2019-2024
  • Figure 3: Global: Retail Analytics Market: Breakup by Function (in %), 2024
  • Figure 4: Global: Retail Analytics Market: Breakup by Component (in %), 2024
  • Figure 5: Global: Retail Analytics Market: Breakup by Deployment Mode (in %), 2024
  • Figure 6: Global: Retail Analytics Market: Breakup by End User (in %), 2024
  • Figure 7: Global: Retail Analytics Market: Breakup by Region (in %), 2024
  • Figure 8: Global: Retail Analytics Market Forecast: Sales Value (in Billion USD), 2025-2033
  • Figure 9: Global: Retail Analytics (Customer Management) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 10: Global: Retail Analytics (Customer Management) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 11: Global: Retail Analytics (In-store Operation) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 12: Global: Retail Analytics (In-store Operation) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 13: Global: Retail Analytics (Strategy and Planning) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 14: Global: Retail Analytics (Strategy and Planning) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 15: Global: Retail Analytics (Supply Chain Management) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 16: Global: Retail Analytics (Supply Chain Management) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 17: Global: Retail Analytics (Marketing and Merchandizing) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 18: Global: Retail Analytics (Marketing and Merchandizing) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 19: Global: Retail Analytics (Other Functions) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 20: Global: Retail Analytics (Other Functions) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 21: Global: Retail Analytics (Software) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 22: Global: Retail Analytics (Software) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 23: Global: Retail Analytics (Services) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 24: Global: Retail Analytics (Services) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 25: Global: Retail Analytics (On-premises) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 26: Global: Retail Analytics (On-premises) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 27: Global: Retail Analytics (Cloud-based) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 28: Global: Retail Analytics (Cloud-based) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 29: Global: Retail Analytics (Small and Medium Enterprises) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 30: Global: Retail Analytics (Small and Medium Enterprises) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 31: Global: Retail Analytics (Large Enterprises) Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 32: Global: Retail Analytics (Large Enterprises) Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 33: North America: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 34: North America: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 35: United States: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 36: United States: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 37: Canada: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 38: Canada: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 39: Asia Pacific: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 40: Asia Pacific: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 41: China: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 42: China: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 43: Japan: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 44: Japan: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 45: India: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 46: India: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 47: South Korea: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 48: South Korea: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 49: Australia: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 50: Australia: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 51: Indonesia: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 52: Indonesia: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 53: Others: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 54: Others: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 55: Europe: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 56: Europe: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 57: Germany: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 58: Germany: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 59: France: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 60: France: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 61: United Kingdom: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 62: United Kingdom: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 63: Italy: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 64: Italy: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 65: Spain: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 66: Spain: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 67: Russia: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 68: Russia: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 69: Others: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 70: Others: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 71: Latin America: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 72: Latin America: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 73: Brazil: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 74: Brazil: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 75: Mexico: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 76: Mexico: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 77: Others: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 78: Others: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 79: Middle East and Africa: Retail Analytics Market: Sales Value (in Million USD), 2019 & 2024
  • Figure 80: Middle East and Africa: Retail Analytics Market Forecast: Breakup by Country (in %), 2024
  • Figure 81: Middle East and Africa: Retail Analytics Market Forecast: Sales Value (in Million USD), 2025-2033
  • Figure 82: Global: Retail Analytics Industry: SWOT Analysis
  • Figure 83: Global: Retail Analytics Industry: Value Chain Analysis
  • Figure 84: Global: Retail Analytics Industry: Porter's Five Forces Analysis

List of Tables

  • Table 1: Global: Retail Analytics Market: Key Industry Highlights, 2024 and 2033
  • Table 2: Global: Retail Analytics Market Forecast: Breakup by Function (in Million USD), 2025-2033
  • Table 3: Global: Retail Analytics Market Forecast: Breakup by Component (in Million USD), 2025-2033
  • Table 4: Global: Retail Analytics Market Forecast: Breakup by Deployment Mode (in Million USD), 2025-2033
  • Table 5: Global: Retail Analytics Market Forecast: Breakup by End User (in Million USD), 2025-2033
  • Table 6: Global: Retail Analytics Market Forecast: Breakup by Region (in Million USD), 2025-2033
  • Table 7: Global: Retail Analytics Market Structure
  • Table 8: Global: Retail Analytics Market: Key Players