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市場調查報告書
商品編碼
1800915

2025 年至 2033 年零售分析市場報告（按功能、組件、部署模式、最終用戶和地區）

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個工作天內

價格

2024年，全球零售分析市場規模達104億美元。展望未來， IMARC Group預計到2033年，該市場規模將達到452億美元，2025-2033年期間的複合年成長率（CAGR）為16.92%。得益於先進的技術基礎設施和主要零售企業的強大影響力，北美引領市場。零售分析市場正在經歷顯著成長，這得益於企業數位化程度的不斷提升、雲端零售分析解決方案的使用日益增多，以及消費者為了節省時間和金錢而逐漸養成的線上購物習慣。

零售分析產業正在經歷巨大的變革，其動力源於企業對資料在策略選擇和業務流程改進方面的日益依賴。永續性正迅速成為主流零售策略，而分析技術正助力環境監測和報告。零售商正在量化碳足跡、報告能源消耗，並評估供應鏈合作夥伴的永續性。分析技術也支援諸如減少浪費、推薦綠色產品和道德採購等措施。透過將分析技術與永續發展目標相結合，零售商正在創造更強大的品牌聲譽，並滿足客戶對負責任經營的期望。

零售分析市場趨勢：

對個人化客戶體驗的需求日益成長

零售商不斷強調為客戶提供高度個人化的體驗，這極大地推動了零售分析解決方案的應用。因此，許多公司正在推出個人化零售解決方案。例如，蘋果公司於2025年在印度推出了「影片專家購物」（Shop with a Specialist over Video）服務，用戶可以在蘋果商店線上購買蘋果產品。透過收集來自多種來源的資訊，例如在線瀏覽歷史、購買習慣、忠誠度計劃和社交媒體使用情況，企業正在製定高度客製化的行銷方案。零售分析解決方案正在幫助零售商更有效地細分購物者，預測他們的喜好，並據此提供個人化的產品推薦和優惠。隨著顧客對個人化購物的期望不斷提高，零售商正在使用先進的分析解決方案來提高參與度和滿意度。即時個人化正成為競爭優勢，企業利用動態定價和個人化優惠來提升銷售量。零售商還將人工智慧和機器學習嵌入到分析平台中，以提高準確性並實現決策自動化。隨著全通路零售的蓬勃發展，這一趨勢正在加速發展，分析平台不斷收集實體和數位管道的資料，以最佳化客戶旅程。

電子商務和數位管道的突然繁榮

線上零售和數位通路的持續成長產生了大量資料，促使零售商採用高級分析技術來解讀這些數據。隨著越來越多的客戶轉向線上購物，零售商正在收集有關客戶行為的豐富資訊，例如點擊率、購物車放棄率、會話時長和重複訪問次數。零售分析軟體現在被用於即時監控這些線上互動，以便公司可以改善網站設計、提高產品曝光度並改善用戶體驗。隨著行動購物和基於應用程式的零售業的興起，分析潛力在各種數位平台上不斷擴大。零售商正在利用資料洞察來增強客戶獲取、提高留存率並改善他們的數位行銷活動。在這種不斷變化的情況下，即時分析開始成為追蹤關鍵績效指標 (KPI)、識別市場趨勢和提前對客戶行為做出反應的必需品。 IMARCIMARC Group預測，到 2033 年，全球電子商務市場規模預計將達到 214.5 兆美元。

人工智慧 (AI) 和機器學習 (ML) 的進步

人工智慧 (AI) 和機器學習 (ML) 技術正在徹底改變零售分析產業，幫助企業獲得更深入的洞察並實現複雜流程的自動化。零售商正積極運用基於 AI 的分析解決方案來預測需求、識別詐欺行為並精準識別新興趨勢。 ML 演算法持續處理巨量資料集，以識別潛在模式、最佳化定價策略並即時推薦產品。這些技術還透過智慧聊天機器人和虛擬助理改變客戶服務，它們基於數據驅動的洞察來回答客戶問題並促成購買。零售商正在利用 AI 預測庫存需求並減少浪費，從而增強庫存管理。此外，由 AI 支援的規範分析能夠根據預測結果推薦最佳行動方案，從而促進更具策略性的決策。隨著這些技術的不斷發展，零售商正在投資 AI 驅動的分析技術，以在瞬息萬變的市場格局中保持競爭力和敏捷性。 Standard AI 於 2025 年推出了 Vision Analytics，透過對個人、產品和互動的清晰洞察，為零售商和品牌提供消費者行為、產品有效性和門市營運方面的洞察。

零售分析市場成長動力：

全通路零售策略整合

零售商正在積極採用全通路零售策略，而數據分析是他們跨不同接觸點提供無縫客戶體驗的核心。顧客在多通路環境中與品牌互動，包括實體店互動、網站互動、智慧型手機應用互動和社群媒體互動。零售商正在從所有這些來源收集資料，以建立客戶體驗的綜合視圖。零售分析解決方案使企業能夠監控跨通路行為，確定客戶流失點，並最大限度地提高通路績效。例如，在線上瀏覽的顧客隨後會進入實體店進行購買，分析平台正在監控此類行為，以影響行銷和銷售工作。商店還利用全通路分析來協調促銷活動、進行跨通路庫存管理並最佳化訂單履行效率。這種方法使企業能夠協調其行銷、營運和客戶服務計劃，最終最大限度地提高品牌一致性和消費者滿意度。隨著數位零售和實體零售這兩個領域的不斷融合，全通路分析的應用正在穩步加速。

供應鏈最佳化和有效庫存管理

零售商不斷應用分析技術，以更好地最佳化供應鏈營運和庫存管理，這是市場的另一個關鍵驅動力。在客戶對快速準確地交付產品的期望不斷提高的時代，即時資料洞察被用於預測需求、審查庫存數量並更有效地管理物流。零售分析軟體正在監控倉庫和門市之間的產品流動，幫助企業減少庫存積壓、最大限度地減少缺貨並提高補貨準確性。預測模型被用於根據過往業績和季節性模式確定最佳訂單規模和配送計劃。零售商還利用地理空間分析技術，透過最佳化倉庫位置和配送路線來最大限度地降低運輸成本並最大限度地提高服務水準。分析技術也被用於追蹤供應商的績效、監控交貨時間並評估供應鏈中的風險。透過在採購和庫存計劃中進行數據驅動的決策，零售商正在提高營運效率和獲利能力。在全球消費者需求不斷變化和供應鏈中斷的環境下，這些能力變得越來越必要。

擴大使用基於雲端的分析解決方案

零售商擴大使用基於雲端的分析平台，因為它們具有可擴展、靈活且經濟高效的特性。這些平台使公司無需繁重的內部部署基礎架構即可擷取、處理和分析大量資料。基於雲端的零售分析解決方案提供即時洞察、更快部署以及與當前企業系統更簡單的整合。公司正在使用這些解決方案進行跨部門協作、遠端存取資料並確保報告的一致性。遷移到雲端也加強了資料安全性和合規性，因為頂級供應商提供高強度加密並遵守全球資料隱私法規。雲端平台還透過以使用付費的方式提供高階運算功能，使使用 AI 和 ML 變得容易。零售商從基於訂閱的選項中獲益，這些選項可以最大限度地減少初始投資，並提高擴展靈活性。隨著數位轉型的步伐加快，基於雲端的分析正在成為零售業創新和競爭差異化的關鍵驅動力。

零售分析市場細分：

按功能分類：

  • 客戶管理
  • 店內營運
  • 策略與規劃
  • 供應鏈管理
  • 行銷和行銷
  • 其他

客戶管理佔據大部分市場佔有率

由於個人化客戶體驗的需求日益成長，以及在競爭激烈的零售環境中客戶忠誠度和保留率的戰略意義，客戶管理在零售分析市場中佔據主導地位。零售商可以透過分析深入了解客戶行為、偏好和購買習慣，從而提供客製化行銷、改善客戶互動並擴展服務範圍。例如，美國人口普查局的資料展現了零售額和電商趨勢的重要洞察，這對於零售分析中的客戶管理至關重要。此外，年度零售貿易調查提供了各零售業的詳細年度銷售額、電商銷售額和庫存數據。這可以幫助企業了解消費者的購買模式，並據此調整客戶管理策略。這種數據驅動的策略有助於識別有價值的客戶，預測他們未來的購買模式，並制定有效的忠誠度計劃。此外，透過促進即時決策和預測分析，人工智慧 (AI) 和機器學習等技術的結合，進一步增強了這些技術的有效性。

按組件細分：

  • 軟體
  • 服務

軟體佔產業最大佔有率

軟體在零售分析行業中佔據主導地位，因為它對於將大量資料轉化為可付諸實踐的洞察至關重要，從而幫助零售商做出更明智的決策。美國人口普查局報告稱，2021年第一季度，電子商務銷售額佔總銷售額的近13%，凸顯了分析在最大化線上銷售策略方面的重要性。在當今數據驅動的市場環境下，零售分析軟體為客戶行為監控、庫存管理和銷售預測提供了廣泛的解決方案。美國勞工統計局指出，零售業數位化營運的應用日益廣泛，這需要先進的分析解決方案來管理當代零售營運的範圍和複雜性。

依部署模式分類：

  • 本地
  • 基於雲端

基於雲端的代表領先的細分市場

基於雲端的解決方案具備可擴展性、靈活性和經濟實惠的優勢——這些對於管理當代零售營運產生的大量資料至關重要——因此對零售分析行業的前景產生了積極的影響。零售商能夠有效率地應對購物高峰期，因為他們可以根據需要靈活地增加或減少資源。美國小型企業管理局的一項調查指出，由於雲端運算可以降低IT管理費用並提高營運效率，中小型企業正在以越來越快的速度採用雲端運算。這種變化對零售業尤其重要，因為市場環境的變化需要即時資料處理和分析。雲端系統透過提供資料儲存和複雜的分析功能，無需大量的初始資金投入，實現了這一點。

按最終用戶分類：

  • 中小企業
  • 大型企業

大型企業市場主導地位明顯

由於其龐大的營運範圍和其所監管的複雜資料環境，大型組織在終端用戶零售分析市場中佔據主導地位。這些公司擁有投資尖端零售分析解決方案的基礎設施和財力，這對於管理眾多通路和地區產生的大量資料至關重要。大型企業可以透過整合和分析這些資料來深入了解市場趨勢、供應鏈效率和消費者行為。策略規劃、國際市場競爭力和營運最佳化都取決於這種程度的分析。大型企業還可以經常使用更高級的分析方法，例如人工智慧驅動的工具和預測模型，以刺激創新並提升消費者體驗。

按地區分類：

  • 北美洲
    • 美國
    • 加拿大
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 其他
  • 歐洲
    • 德國
    • 法國
    • 英國
    • 義大利
    • 西班牙
    • 俄羅斯
    • 其他
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 其他
  • 中東和非洲

北美引領市場，佔據最大的零售分析市場佔有率

該報告還對所有主要區域市場進行了全面分析，包括北美（美國和加拿大）；亞太地區（中國、日本、印度、韓國、澳洲、印尼等）；歐洲（德國、法國、英國、義大利、西班牙、俄羅斯等）；拉丁美洲（巴西、墨西哥等）；以及中東和非洲。報告指出，北美是零售分析領域中最大的市場。

北美憑藉其先進的技術基礎設施、巨量資料解決方案的廣泛應用以及對人工智慧 (AI) 和機器學習的大量投資，在零售分析市場佔據主導地位。美國商務部報告稱，2019 年北美零售電商銷售額較 2020 年成長 32.4%，顯示該行業正在快速擴張，對高階分析的需求也日益成長。大型數位組織和新創公司專注於提供零售分析解決方案，以提升客戶體驗和營運效率，並將這一地區視為大本營。美國經濟分析局的數據顯示，零售業的數位轉型推動了對用於了解消費者行為、管理庫存和改善供應鏈的分析需求。這進一步催化了零售分析市場的成長。

（請注意，這只是關鍵參與者的部分列表，完整列表在報告中提供。）

  • 零售分析領域的一些領先公司，例如微軟公司、富士通有限公司、Flir Systems Inc.、Altair Engineering Inc.、Adobe Inc. 和 1010data Inc.，都在不斷改進其產品，以提高零售分析市場的價值。 1010data Inc. 是一家基於雲端的分析供應商，非常重視零售營運最佳化。 Adobe Inc. 透過其先進的 Adob​​e Analytics 平台提供客製化的數位行銷解決方案。零售商可以在將分析融入產品設計的 Altair Engineering Inc. 的幫助下加強供應鏈和庫存管理。 Flir Systems Inc. 使用尖端的熱成像技術來深入了解客戶行為和安全性。富士通有限公司提供完整的零售解決方案，例如數據驅動的銷售點系統。微軟公司正在利用尖端的人工智慧和基於雲端的技術來提高客戶參與度，從而推進購物體驗的個人化。總的來說，這些企業正在為複雜的數據驅動零售策略鋪路。例如，Adobe Experience Platform 提供了客戶旅程分析等新工具，零售商現在可以利用 AI 來偵測不良體驗（或發現新的商機）。此次更新將異常檢測擴展到了網站之外（此前，網站是其主要應用領域），並允許品牌在購物者跨管道購物時發現問題所在。

本報告回答的關鍵問題

  • 2024 年全球零售分析市場規模是多少
  • 2025-2033年全球零售分析市場的預期成長率是多少
  • 推動全球零售分析市場的關鍵因素有哪些
  • COVID-19 對全球零售分析市場有何影響
  • 根據功能，全球零售分析市場如何分類
  • 根據組成部分，全球零售分析市場如何分類
  • 根據部署模式，全球零售分析市場如何分類
  • 根據最終用戶，全球零售分析市場如何分類
  • 全球零售分析市場的主要區域有哪些
  • 10. 全球零售分析市場的主要參與者/公司有哪些？

本報告回答的關鍵問題

  • 2024年全球零售分析市場規模？ 2025-2033年全球零售分析市場的預期成長率是多少？
  • 推動全球零售分析市場發展的關鍵因素有哪些？
  • COVID-19 對全球零售分析市場有何影響？
  • 根據功能，全球零售分析市場是如何分類的？
  • 根據組成部分，全球零售分析市場是如何分類的？
  • 根據部署模式，全球零售分析市場如何分類？
  • 根據最終用戶，全球零售分析市場是如何分類的？
  • 全球零售分析市場的關鍵區域有哪些？
  • 全球零售分析市場的主要參與者/公司有哪些？

目錄

第1章：前言

第2章：範圍與方法

  • 研究目標
  • 利害關係人
  • 資料來源
    • 主要來源
    • 次要來源
  • 市場評估
    • 自下而上的方法
    • 自上而下的方法
  • 預測方法

第3章：執行摘要

第4章：簡介

第5章：全球零售分析市場

  • 市場概覽
  • 市場表現
  • COVID-19的影響
  • 市場預測

第6章：市場區隔：依功能

  • 客戶管理
  • 店內營運
  • 策略與規劃
  • 供應鏈管理
  • 行銷和行銷
  • 其他

第7章：市場區隔：依組成部分

  • 軟體
  • 服務

第8章：市場區隔：依部署模式

  • 本地
  • 基於雲端

第9章：市場區隔：依最終用戶

  • 中小企業
  • 大型企業

第10章：市場細分：按地區

  • 北美洲
    • 美國
    • 加拿大
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 其他
  • 歐洲
    • 德國
    • 法國
    • 英國
    • 義大利
    • 西班牙
    • 俄羅斯
    • 其他
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 其他
  • 中東和非洲

第 11 章：SWOT 分析

第 12 章：價值鏈分析

第 13 章：波特五力分析

第 14 章：價格分析

第 15 章：競爭格局

  • 市場結構
  • 關鍵參與者
  • 關鍵參與者簡介
    • 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