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市场调查报告书
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零售预测分析市场按服务产品、资料类型、应用、最终用途和最终用途划分 - 2025-2030 年全球预测

Predictive Analytics for Retail Market by Offering, Data Type, Application, End-Use, Usage - Global Forecast 2025-2030
出版日期: | 出版商: 360iResearch | 英文 186 Pages | 商品交期: 最快1-2个工作天内

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零售预测分析市场预计在 2024 年价值为 14.7 亿美元，在 2025 年成长至 17.2 亿美元，到 2030 年达到 39.5 亿美元，复合年增长率为 17.90%。

主要市场统计数据
基准年 2024 年 14.7亿美元
预计 2025 年 17.2亿美元
预测年份 2030 39.5亿美元
复合年增长率（%） 17.90％

预测分析日益重要，正在重塑不断发展的零售格局。这项技术不仅改变了业务效率，也推动了整个零售业策略决策流程的变革。透过利用复杂的演算法、资料驱动的洞察力和机器学习模型，预测分析使零售商能够以前所未有的精度预测客户行为、优化库存和微调行销策略。近年来，这种方法已成为成熟市场领导和新兴创新者的竞争策略的核心。

零售商越来越意识到预测分析对于理解复杂的消费者模式所带来的价值。先进的技术可让您分析历史资料并预测未来趋势，以改善需求预测、个人化客户体验并改善定价策略。这种即时主动规划而非简单反应的能力为零售业务增加了关键的灵活性和效率。

此外，整合预测分析可以更深入地了解数位和实体管道的客户互动。透过将传统零售实践与创新资料科学技术相结合，公司能够更好地简化供应链、改善商店布局和改进商品行销方法。这些技术的采用为未来奠定了基础，分析和零售业务的交会将成为成功的基石。

分析零售预测分析领域的转型转变

近年来，资料科学与营运策略的融合推动了零售业的变革。在大量资料涌入的推动下，零售业正经历从直觉决策到分析预见的模式转移。这种转变正在彻底改变零售商在日益数位化的世界中管理库存、制定定价策略和与客户互动的方式。

技术的进步和先进工具的快速采用使得零售商能够从被动策略转变为主动的预测方法。随着技术无缝融入日常业务，该公司现在能够利用以前未开发的大量资料集来更深入地了解消费行为。因此，公司可以更有效地分配资源，优化供应链，并执行符合目标消费者人口统计的客製化行销宣传活动。

当今零售商面临的竞争环境是，快速适应不仅是一种优势，而且是一种必要。随着人工智慧和机器学习的不断发展，这些技术与预测分析的结合正在推动创新并带来更准确的预测和策略规划。这种转变也体现在改进的诈欺侦测机制和基于资料洞察的增强的商店布局设计上。结果是零售环境能够响应市场变化并更好地满足客户期望。

了解影响零售分析的关键细分洞察

在考虑零售业的预测分析时，关键细分洞察在映射多样化市场动态中发挥关键作用。考虑基于服务产品的细分，市场透过两个视角来检视－服务和解决方案，每个视角都为满足顾客需求贡献了独特的价值提案。基于资料类型的细分也同样重要。它透过资料和非结构化资料提供深入的市场分析，以提供利用传统资讯和细微见解的全面视图。

深入挖掘，基于应用程式的细分揭示了零售功能的详细故事，例如客户细分和定位、需求预测、诈欺检测和预防、库存管理、个人化行销、价格优化、销售和收益预测、创新商店布局和商品行销等。每个应用不仅完善了作战策略，而且还起到了催化剂的作用，弥合了资料分析和战术执行之间的差距。服装和时尚、电子和消费品、杂货和超级市场、健康和美容、家居和家具以及奢侈品等零售市场都以相同的深度和粒度进行分析。

最后，考虑基于使用情况的细分区分电子商务/线上零售商使用的平台和线下零售商使用的平台，突出每个管道面临的独特挑战和机会。这种综合的细分方法可以产生丰富的见解，使公司能够制定满足不同客户群细微需求的客製化策略。透过了解产品、资料类型、用途、最终用途和利用率等各个方面，零售决策者可以製定整体和微观细分策略，以确保在快速发展的市场中保持可持续的竞争优势。

目录

第 1 章 简介

第二章调查方法

第三章执行摘要

第四章 市场概况

第五章 市场洞察

  • 市场动态
    • 驱动程式
      • 电子商务平台和行动购物应用程式快速成长
      • 对个人化、以客户为中心的购物体验的需求日益增加
    • 限制因素
      • 先进分析工具高成本、技术复杂
    • 机会
      • 消费者资料可用性的提高将推动零售业采用预测分析
      • 人工智慧和机器学习的进步有助于实现准确的需求预测
    • 任务
      • 与预测分析相关的资料隐私和监管合规问题
  • 市场区隔分析
    • 优势：可自订性和快速适应市场变化的能力推动了该服务的使用率上升
    • 最终用途：被杂货店和超级市场广泛采用，以维持最佳存量基准、减少废弃物和个人化促销。
  • 波特五力分析
  • PESTEL 分析
    • 政治的
    • 经济
    • 社会
    • 技术的
    • 合法的
    • 环境

6. 零售预测分析市场（依产品分类）

  • 服务
  • 解决方案

7. 零售预测分析市场按资料类型划分

  • 结构化资料
  • 非结构化资料

第 8 章。

  • 客户细分与定位
  • 需求预测
  • 诈欺检测与预防
  • 库存管理
  • 个性化行销
  • 价格优化
  • 销售和收益预测
  • 商店布置和商品行销
  • 供应链优化

9. 零售预测分析市场（依最终用途）

  • 服装与时尚
  • 电子产品和消费品
  • 杂货店和超级市场
  • 健康与美容
  • 家居用品和家具
  • 奢侈品

第 10 章 零售预测分析市场（按应用）

  • 电子商务和线上零售商
  • 线下零售商

11. 美国零售市场预测分析

  • 阿根廷
  • 巴西
  • 加拿大
  • 墨西哥
  • 美国

12. 亚太地区零售预测分析市场

  • 澳洲
  • 中国
  • 印度
  • 印尼
  • 日本
  • 马来西亚
  • 菲律宾
  • 新加坡
  • 韩国
  • 台湾
  • 泰国
  • 越南

13. 欧洲、中东和非洲零售预测分析市场

  • 丹麦
  • 埃及
  • 芬兰
  • 法国
  • 德国
  • 以色列
  • 义大利
  • 荷兰
  • 奈及利亚
  • 挪威
  • 波兰
  • 卡达
  • 俄罗斯
  • 沙乌地阿拉伯
  • 南非
  • 西班牙
  • 瑞典
  • 瑞士
  • 土耳其
  • 阿拉伯聯合大公国
  • 英国

第十四章 竞争格局

  • 2024 年市场占有率分析
  • FPNV 定位矩阵，2024 年
  • 竞争情境分析
  • 战略分析与建议

公司列表

  • Alteryx, Inc.
  • Amazon.com, Inc.
  • C3.ai, Inc.
  • Cloudera, Inc.
  • Databricks, Inc.
  • Endava
  • Epic Systems Corporation
  • Hitachi Solutions
  • Honeywell International Inc.
  • IBM Corporation
  • Intel Corporation
  • KPMG International Limited
  • Manthan Systems Private Limited
  • Mastech InfoTrellis, Inc.
  • Microsoft Corporation
  • NVIDIA Corporation
  • Oracle Corporation
  • QlikTech International AB
  • Salesforce.com, Inc.
  • SAP SE
  • SAS Institute Inc.
  • Teradata Corporation
  • ThoughtSpot Inc.
  • TIBCO Software Inc.
  • Wipro Limited
Product Code: MRR-843943FD3AA1

The Predictive Analytics for Retail Market was valued at USD 1.47 billion in 2024 and is projected to grow to USD 1.72 billion in 2025, with a CAGR of 17.90%, reaching USD 3.95 billion by 2030.

KEY MARKET STATISTICS
Base Year [2024] USD 1.47 billion
Estimated Year [2025] USD 1.72 billion
Forecast Year [2030] USD 3.95 billion
CAGR (%) 17.90%

The evolving landscape of retail is being reshaped by the growing prominence of predictive analytics. This technology is not only transforming operational efficiencies, but it is also driving the evolution of strategic decision-making processes across the retail industry. Leveraging sophisticated algorithms, data-driven insights, and machine learning models, predictive analytics enables retailers to anticipate customer behaviors, optimize inventory, and fine-tune marketing strategies with unprecedented precision. Over the past few years, this approach has become central to the competitive strategies of both established market leaders and emerging innovators.

Retailers are increasingly recognizing the value that predictive analytics brings to understanding complex consumer patterns. Advanced methodologies allow for the analysis of historical data to forecast future trends, thereby improving demand forecasting, personalizing customer experiences, and refining pricing strategies. This real-time capability to not just react but also proactively plan is adding significant layers of agility and efficiency to retail operations.

Furthermore, the integration of predictive analytics catalyzes a deeper understanding of customer interactions across digital and physical channels. By bridging traditional retail practices with innovative data science techniques, businesses are better positioned to streamline their supply chain, enhance store layouts, and refine merchandising approaches. The adoption of these technologies is setting the stage for a future where the fusion of analytics and retail operations becomes the cornerstone of success.

Analyzing Transformative Shifts in Retail Predictive Analytics Landscape

Over recent years, transformative shifts in retail have been spurred by the convergence of data science and operational strategy. The retail sector, driven by an influx of rich data, has experienced a paradigm shift from intuition-based decision making to analytical foresight. This shift is profoundly changing the way retailers manage inventories, structure pricing strategies, and engage with customers in an increasingly digital world.

Technological advancements and the rapid adoption of advanced tools have allowed retailers to pivot from reactive strategies to proactive forecasting methods. Because of the seamless integration of technology with day-to-day operations, businesses have been able to harness extensive data sets that were previously untapped, enabling a more granular understanding of consumer behaviors. Consequently, organizations are able to allocate resources more efficiently, optimize supply chains, and implement customized marketing campaigns that resonate with targeted audience segments.

Retailers now face a competitive environment where quick adaptation is not just an advantage but a necessity. As artificial intelligence and machine learning continuously evolve, the integration of these technologies with predictive analytics is driving innovation, leading to more accurate forecasts and strategic planning. This transformation is also evident in improved fraud detection mechanisms and enhanced store layout designs that are informed by data insights. The result is a retail environment that is more responsive to market changes and better aligned with customer expectations.

In-Depth Key Segmentation Insights Shaping Retail Analytics

In exploring predictive analytics within the retail sector, key segmentation insights play a pivotal role in mapping diverse market dynamics. Considering the segmentation based on offering, the market is examined through the dual lenses of services and solutions, each contributing unique value propositions in addressing customer demands. Equally important is the segmentation based on data type, where the market is deeply analyzed through both structured data and unstructured data, providing a comprehensive view that leverages conventional information and nuanced insights alike.

Diving deeper, the segmentation based on application lays out a detailed narrative of retail functionalities such as customer segmentation and targeting, demand forecasting, fraud detection and prevention, inventory management, personalized marketing, pricing optimization, sales and revenue forecasting, and innovative store layout and merchandising. Each application not only refines the operational tactics but also acts as a catalyst in bridging data analytics with tactical execution. Alongside these applications comes the critical segmentation based on end-use, where retail markets such as apparel and fashion, electronics and consumer goods, groceries and supermarkets, health and beauty, home goods and furniture, and luxury goods are analyzed with equal depth and precision.

Finally, an examination of the segmentation based on usage distinguishes between platforms followed by e-commerce and online retailers versus offline retailers, thereby highlighting the unique challenges and opportunities inherent in each channel. This integrated approach to segmentation yields rich insights that enable businesses to formulate tailored strategies that cater to the nuanced needs of diverse customer bases. By understanding the various dimensions across offering, data type, application, end-use, and usage, retail decision-makers can devise strategies that are both holistic and finely segmented, ensuring sustained competitive advantage in a rapidly evolving market.

Based on Offering, market is studied across Services and Solution.

Based on Data Type, market is studied across Structured Data and Unstructured Data.

Based on Application, market is studied across Customer Segmentation & Targeting, Demand Forecasting, Fraud Detection & Prevention, Inventory Management, Personalized Marketing, Pricing Optimization, Sales & Revenue Forecasting, Store Layout & Merchandising, and Supply Chain Optimization.

Based on End-Use, market is studied across Apparel & Fashion, Electronics & Consumer Goods, Groceries & Supermarkets, Health & Beauty, Home Goods & Furniture, and Luxury Goods.

Based on Usage, market is studied across E-commerce & Online Retailers and Offline Retailers.

Regional Insights: Global Trends and Market Dynamics

Understanding the geographical contours of the market is essential for making informed strategic decisions in retail predictive analytics. The regional insights reveal that markets within the Americas are experiencing significant technological advancements driven by high consumer engagement and robust digital infrastructures. In parallel, regions covering Europe, the Middle East, and Africa are embracing digital transformation, with many retailers adopting predictive models to optimize operations in an increasingly competitive environment.

Additionally, the Asia-Pacific region stands out due to its rapid adoption of advanced analytics technologies, along with a booming e-commerce industry that continues to reshape traditional retail business models. This region is characterized by dynamic consumer behavior trends and a youthful demographic, which collectively drive the demand for innovative predictive solutions. As retailers in these regions seek to capitalize on their distinct market conditions, the regional insights provide a strategic roadmap for harnessing technology to drive growth and enhance operational efficiency. Each region, with its unique set of opportunities and challenges, contributes valuable lessons and benchmarks for the broader retail industry.

Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

Leading Innovators: Key Company Insights in Predictive Analytics

The role of key industry players cannot be understated in the evolution of predictive analytics within the retail environment. Companies such as Alteryx, Inc. and Amazon.com, Inc. have been at the forefront, pioneering innovations that integrate data analytics into diverse retail operations. Their technological contributions complement the innovative strategies developed by industry frontrunners like C3.ai, Inc., Cloudera, Inc., and Databricks, Inc., who continue to set the benchmark for how analytics drive business intelligence.

Further, organizations including Endava, Epic Systems Corporation, and Hitachi Solutions are rapidly scaling their analytical capabilities, while global conglomerates such as Honeywell International Inc., IBM Corporation, and Intel Corporation bring extensive domain expertise to bear. Professional services firms like KPMG International Limited, along with dedicated technology providers such as Manthan Systems Private Limited and Mastech InfoTrellis, Inc., have also deepened market maturity by integrating high-value data solutions. In addition, the influence of major corporations such as Microsoft Corporation, NVIDIA Corporation, Oracle Corporation, QlikTech International AB, Salesforce.com, Inc., SAP SE, SAS Institute Inc., Teradata Corporation, ThoughtSpot Inc., TIBCO Software Inc., and Wipro Limited is evident in the market. These players collectively harness innovation to refine predictive models that are vital for transforming retail strategies on a global scale.

The report delves into recent significant developments in the Predictive Analytics for Retail Market, highlighting leading vendors and their innovative profiles. These include Alteryx, Inc., Amazon.com, Inc., C3.ai, Inc., Cloudera, Inc., Databricks, Inc., Endava, Epic Systems Corporation, Hitachi Solutions, Honeywell International Inc., IBM Corporation, Intel Corporation, KPMG International Limited, Manthan Systems Private Limited, Mastech InfoTrellis, Inc., Microsoft Corporation, NVIDIA Corporation, Oracle Corporation, QlikTech International AB, Salesforce.com, Inc., SAP SE, SAS Institute Inc., Teradata Corporation, ThoughtSpot Inc., TIBCO Software Inc., and Wipro Limited. Actionable Recommendations for Retail Industry Leaders

Industry leaders are encouraged to leverage the insights from predictive analytics to create forward-thinking strategies that cultivate sustainable growth. Firstly, investing in advanced data management platforms is critical, as it enables a comprehensive approach to integrating structured and unstructured data from various sources. Such investments pave the way for more accurate forecasting and streamlined operations.

In addition, developing cross-functional teams that bridge technical expertise with strategic vision can propel an organization's ability to harness the full potential of analytics. Embracing agile methodologies and continuous learning will also ensure that teams remain at the cutting edge of technological advances. By fostering a culture of innovation, industry leaders can capitalize on emerging tools and techniques, thereby establishing a competitive edge in an evolving market.

Moreover, aligning technology initiatives with customer-centric strategies will help integrate predictive insights into the core of retail operations. This means targeting personalized marketing efforts, optimizing inventory management, and refining pricing strategies based on robust demand forecasting. Each initiative should be tailored to specific market segments, ensuring that every decision is data-driven. Those at the helm are advised to maintain a clear focus on both operational efficiency and customer engagement, empowering them to navigate complexities and maximize return on investment in a rapidly shifting landscape.

Conclusion: Summarizing the Strategic Roadmap for Retail Predictive Analytics

Bringing all the insights together, it becomes evident that predictive analytics is not merely an operational tool but a strategic imperative for the modern retail landscape. The integration of advanced segmentation, regional dynamics, and the innovation propelled by key industry players frames a comprehensive roadmap for retail success. By synthesizing these multifaceted aspects, companies are better positioned to negotiate global market challenges and capitalize on emerging opportunities.

In essence, the journey towards leveraging predictive analytics effectively is a continuous process of adaptation and refinement. Success depends on a relentless commitment to harnessing deep data insights, fostering innovation, and maintaining an agile approach to market changes. This strategic roadmap paves the way for retail entities to not only survive but thrive in the digital age.

Table of Contents

1. Preface

  • 1.1. Objectives of the Study
  • 1.2. Market Segmentation & Coverage
  • 1.3. Years Considered for the Study
  • 1.4. Currency & Pricing
  • 1.5. Language
  • 1.6. Stakeholders

2. Research Methodology

  • 2.1. Define: Research Objective
  • 2.2. Determine: Research Design
  • 2.3. Prepare: Research Instrument
  • 2.4. Collect: Data Source
  • 2.5. Analyze: Data Interpretation
  • 2.6. Formulate: Data Verification
  • 2.7. Publish: Research Report
  • 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

  • 5.1. Market Dynamics
    • 5.1.1. Drivers
      • 5.1.1.1. Rapid growth in e-commerce platforms and mobile shopping applications
      • 5.1.1.2. Rising demand for personalized and customer-centric shopping experiences
    • 5.1.2. Restraints
      • 5.1.2.1. High costs and technical complexity of advanced analytics tools
    • 5.1.3. Opportunities
      • 5.1.3.1. Increasing availability of consumer data drives the adoption of predictive analytics in retail
      • 5.1.3.2. Advancements in artificial intelligence and machine learning for precise demand forecasting
    • 5.1.4. Challenges
      • 5.1.4.1. Concerns over data privacy and regulatory compliance associated with predictive analytics
  • 5.2. Market Segmentation Analysis
    • 5.2.1. Offering: Customization potential and capacity to adjust to immediate market shifts increases usage of services
    • 5.2.2. End-Use: Widespread adoption in groceries & supermarkets to maintain optimal inventory levels, reduce waste, and personalize promotions
  • 5.3. Porter's Five Forces Analysis
    • 5.3.1. Threat of New Entrants
    • 5.3.2. Threat of Substitutes
    • 5.3.3. Bargaining Power of Customers
    • 5.3.4. Bargaining Power of Suppliers
    • 5.3.5. Industry Rivalry
  • 5.4. PESTLE Analysis
    • 5.4.1. Political
    • 5.4.2. Economic
    • 5.4.3. Social
    • 5.4.4. Technological
    • 5.4.5. Legal
    • 5.4.6. Environmental

6. Predictive Analytics for Retail Market, by Offering

  • 6.1. Introduction
  • 6.2. Services
  • 6.3. Solution

7. Predictive Analytics for Retail Market, by Data Type

  • 7.1. Introduction
  • 7.2. Structured Data
  • 7.3. Unstructured Data

8. Predictive Analytics for Retail Market, by Application

  • 8.1. Introduction
  • 8.2. Customer Segmentation & Targeting
  • 8.3. Demand Forecasting
  • 8.4. Fraud Detection & Prevention
  • 8.5. Inventory Management
  • 8.6. Personalized Marketing
  • 8.7. Pricing Optimization
  • 8.8. Sales & Revenue Forecasting
  • 8.9. Store Layout & Merchandising
  • 8.10. Supply Chain Optimization

9. Predictive Analytics for Retail Market, by End-Use

  • 9.1. Introduction
  • 9.2. Apparel & Fashion
  • 9.3. Electronics & Consumer Goods
  • 9.4. Groceries & Supermarkets
  • 9.5. Health & Beauty
  • 9.6. Home Goods & Furniture
  • 9.7. Luxury Goods

10. Predictive Analytics for Retail Market, by Usage

  • 10.1. Introduction
  • 10.2. E-commerce & Online Retailers
  • 10.3. Offline Retailers

11. Americas Predictive Analytics for Retail Market

  • 11.1. Introduction
  • 11.2. Argentina
  • 11.3. Brazil
  • 11.4. Canada
  • 11.5. Mexico
  • 11.6. United States

12. Asia-Pacific Predictive Analytics for Retail Market

  • 12.1. Introduction
  • 12.2. Australia
  • 12.3. China
  • 12.4. India
  • 12.5. Indonesia
  • 12.6. Japan
  • 12.7. Malaysia
  • 12.8. Philippines
  • 12.9. Singapore
  • 12.10. South Korea
  • 12.11. Taiwan
  • 12.12. Thailand
  • 12.13. Vietnam

13. Europe, Middle East & Africa Predictive Analytics for Retail Market

  • 13.1. Introduction
  • 13.2. Denmark
  • 13.3. Egypt
  • 13.4. Finland
  • 13.5. France
  • 13.6. Germany
  • 13.7. Israel
  • 13.8. Italy
  • 13.9. Netherlands
  • 13.10. Nigeria
  • 13.11. Norway
  • 13.12. Poland
  • 13.13. Qatar
  • 13.14. Russia
  • 13.15. Saudi Arabia
  • 13.16. South Africa
  • 13.17. Spain
  • 13.18. Sweden
  • 13.19. Switzerland
  • 13.20. Turkey
  • 13.21. United Arab Emirates
  • 13.22. United Kingdom

14. Competitive Landscape

  • 14.1. Market Share Analysis, 2024
  • 14.2. FPNV Positioning Matrix, 2024
  • 14.3. Competitive Scenario Analysis
    • 14.3.1. Mallcomm launches AI-powered platform for real-time sales and operational insights that drive enhanced retail asset management strategies
    • 14.3.2. Green Street launches Retail Analytics Pro
    • 14.3.3. Microsoft unveils new generative AI and data solutions across the shopper journey
  • 14.4. Strategy Analysis & Recommendation

Companies Mentioned

  • 1. Alteryx, Inc.
  • 2. Amazon.com, Inc.
  • 3. C3.ai, Inc.
  • 4. Cloudera, Inc.
  • 5. Databricks, Inc.
  • 6. Endava
  • 7. Epic Systems Corporation
  • 8. Hitachi Solutions
  • 9. Honeywell International Inc.
  • 10. IBM Corporation
  • 11. Intel Corporation
  • 12. KPMG International Limited
  • 13. Manthan Systems Private Limited
  • 14. Mastech InfoTrellis, Inc.
  • 15. Microsoft Corporation
  • 16. NVIDIA Corporation
  • 17. Oracle Corporation
  • 18. QlikTech International AB
  • 19. Salesforce.com, Inc.
  • 20. SAP SE
  • 21. SAS Institute Inc.
  • 22. Teradata Corporation
  • 23. ThoughtSpot Inc.
  • 24. TIBCO Software Inc.
  • 25. Wipro Limited

LIST OF FIGURES

  • FIGURE 1. PREDICTIVE ANALYTICS FOR RETAIL MARKET MULTI-CURRENCY
  • FIGURE 2. PREDICTIVE ANALYTICS FOR RETAIL MARKET MULTI-LANGUAGE
  • FIGURE 3. PREDICTIVE ANALYTICS FOR RETAIL MARKET RESEARCH PROCESS
  • FIGURE 4. PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, 2024 VS 2030
  • FIGURE 5. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, 2018-2030 (USD MILLION)
  • FIGURE 6. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY REGION, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 7. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 8. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2024 VS 2030 (%)
  • FIGURE 9. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 10. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2024 VS 2030 (%)
  • FIGURE 11. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 12. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2024 VS 2030 (%)
  • FIGURE 13. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 14. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2024 VS 2030 (%)
  • FIGURE 15. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 16. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2024 VS 2030 (%)
  • FIGURE 17. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 18. AMERICAS PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY COUNTRY, 2024 VS 2030 (%)
  • FIGURE 19. AMERICAS PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 20. UNITED STATES PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY STATE, 2024 VS 2030 (%)
  • FIGURE 21. UNITED STATES PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY STATE, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 22. ASIA-PACIFIC PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY COUNTRY, 2024 VS 2030 (%)
  • FIGURE 23. ASIA-PACIFIC PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 24. EUROPE, MIDDLE EAST & AFRICA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY COUNTRY, 2024 VS 2030 (%)
  • FIGURE 25. EUROPE, MIDDLE EAST & AFRICA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 26. PREDICTIVE ANALYTICS FOR RETAIL MARKET SHARE, BY KEY PLAYER, 2024
  • FIGURE 27. PREDICTIVE ANALYTICS FOR RETAIL MARKET, FPNV POSITIONING MATRIX, 2024

LIST OF TABLES

  • TABLE 1. PREDICTIVE ANALYTICS FOR RETAIL MARKET SEGMENTATION & COVERAGE
  • TABLE 2. UNITED STATES DOLLAR EXCHANGE RATE, 2018-2024
  • TABLE 3. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, 2018-2030 (USD MILLION)
  • TABLE 4. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 5. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 6. PREDICTIVE ANALYTICS FOR RETAIL MARKET DYNAMICS
  • TABLE 7. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 8. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY SERVICES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 9. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY SOLUTION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 10. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 11. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY STRUCTURED DATA, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 12. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY UNSTRUCTURED DATA, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 13. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 14. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY CUSTOMER SEGMENTATION & TARGETING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 15. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DEMAND FORECASTING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 16. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY FRAUD DETECTION & PREVENTION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 17. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY INVENTORY MANAGEMENT, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 18. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY PERSONALIZED MARKETING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 19. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY PRICING OPTIMIZATION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 20. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY SALES & REVENUE FORECASTING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 21. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY STORE LAYOUT & MERCHANDISING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 22. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY SUPPLY CHAIN OPTIMIZATION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 23. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 24. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPAREL & FASHION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 25. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY ELECTRONICS & CONSUMER GOODS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 26. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY GROCERIES & SUPERMARKETS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 27. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY HEALTH & BEAUTY, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 28. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY HOME GOODS & FURNITURE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 29. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY LUXURY GOODS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 30. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 31. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY E-COMMERCE & ONLINE RETAILERS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 32. GLOBAL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFLINE RETAILERS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 33. AMERICAS PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 34. AMERICAS PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 35. AMERICAS PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 36. AMERICAS PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 37. AMERICAS PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 38. AMERICAS PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 39. ARGENTINA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 40. ARGENTINA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 41. ARGENTINA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 42. ARGENTINA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 43. ARGENTINA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 44. BRAZIL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 45. BRAZIL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 46. BRAZIL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 47. BRAZIL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 48. BRAZIL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 49. CANADA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 50. CANADA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 51. CANADA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 52. CANADA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 53. CANADA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 54. MEXICO PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 55. MEXICO PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 56. MEXICO PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 57. MEXICO PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 58. MEXICO PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 59. UNITED STATES PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 60. UNITED STATES PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 61. UNITED STATES PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 62. UNITED STATES PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 63. UNITED STATES PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 64. UNITED STATES PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY STATE, 2018-2030 (USD MILLION)
  • TABLE 65. ASIA-PACIFIC PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 66. ASIA-PACIFIC PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 67. ASIA-PACIFIC PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 68. ASIA-PACIFIC PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 69. ASIA-PACIFIC PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 70. ASIA-PACIFIC PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 71. AUSTRALIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 72. AUSTRALIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 73. AUSTRALIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 74. AUSTRALIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 75. AUSTRALIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 76. CHINA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 77. CHINA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 78. CHINA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 79. CHINA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 80. CHINA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 81. INDIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 82. INDIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 83. INDIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 84. INDIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 85. INDIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 86. INDONESIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 87. INDONESIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 88. INDONESIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 89. INDONESIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 90. INDONESIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 91. JAPAN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 92. JAPAN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 93. JAPAN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 94. JAPAN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 95. JAPAN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 96. MALAYSIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 97. MALAYSIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 98. MALAYSIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 99. MALAYSIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 100. MALAYSIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 101. PHILIPPINES PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 102. PHILIPPINES PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 103. PHILIPPINES PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 104. PHILIPPINES PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 105. PHILIPPINES PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 106. SINGAPORE PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 107. SINGAPORE PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 108. SINGAPORE PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 109. SINGAPORE PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 110. SINGAPORE PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 111. SOUTH KOREA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 112. SOUTH KOREA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 113. SOUTH KOREA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 114. SOUTH KOREA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 115. SOUTH KOREA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 116. TAIWAN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 117. TAIWAN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 118. TAIWAN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 119. TAIWAN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 120. TAIWAN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 121. THAILAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 122. THAILAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 123. THAILAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 124. THAILAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 125. THAILAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 126. VIETNAM PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 127. VIETNAM PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 128. VIETNAM PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 129. VIETNAM PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 130. VIETNAM PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 131. EUROPE, MIDDLE EAST & AFRICA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 132. EUROPE, MIDDLE EAST & AFRICA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 133. EUROPE, MIDDLE EAST & AFRICA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 134. EUROPE, MIDDLE EAST & AFRICA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 135. EUROPE, MIDDLE EAST & AFRICA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 136. EUROPE, MIDDLE EAST & AFRICA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 137. DENMARK PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 138. DENMARK PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 139. DENMARK PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 140. DENMARK PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 141. DENMARK PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 142. EGYPT PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 143. EGYPT PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 144. EGYPT PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 145. EGYPT PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 146. EGYPT PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 147. FINLAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 148. FINLAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 149. FINLAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 150. FINLAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 151. FINLAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 152. FRANCE PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 153. FRANCE PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 154. FRANCE PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 155. FRANCE PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 156. FRANCE PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 157. GERMANY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 158. GERMANY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 159. GERMANY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 160. GERMANY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 161. GERMANY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 162. ISRAEL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 163. ISRAEL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 164. ISRAEL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 165. ISRAEL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 166. ISRAEL PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 167. ITALY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 168. ITALY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 169. ITALY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 170. ITALY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 171. ITALY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 172. NETHERLANDS PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 173. NETHERLANDS PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 174. NETHERLANDS PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 175. NETHERLANDS PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 176. NETHERLANDS PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 177. NIGERIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 178. NIGERIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 179. NIGERIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 180. NIGERIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 181. NIGERIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 182. NORWAY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 183. NORWAY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 184. NORWAY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 185. NORWAY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 186. NORWAY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 187. POLAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 188. POLAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 189. POLAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 190. POLAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 191. POLAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 192. QATAR PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 193. QATAR PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 194. QATAR PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 195. QATAR PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 196. QATAR PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 197. RUSSIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 198. RUSSIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 199. RUSSIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 200. RUSSIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 201. RUSSIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 202. SAUDI ARABIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 203. SAUDI ARABIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 204. SAUDI ARABIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 205. SAUDI ARABIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 206. SAUDI ARABIA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 207. SOUTH AFRICA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 208. SOUTH AFRICA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 209. SOUTH AFRICA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 210. SOUTH AFRICA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 211. SOUTH AFRICA PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 212. SPAIN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 213. SPAIN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 214. SPAIN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 215. SPAIN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 216. SPAIN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 217. SWEDEN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 218. SWEDEN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 219. SWEDEN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 220. SWEDEN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 221. SWEDEN PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 222. SWITZERLAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 223. SWITZERLAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 224. SWITZERLAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 225. SWITZERLAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 226. SWITZERLAND PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 227. TURKEY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 228. TURKEY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 229. TURKEY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 230. TURKEY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 231. TURKEY PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 232. UNITED ARAB EMIRATES PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 233. UNITED ARAB EMIRATES PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 234. UNITED ARAB EMIRATES PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 235. UNITED ARAB EMIRATES PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 236. UNITED ARAB EMIRATES PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 237. UNITED KINGDOM PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY OFFERING, 2018-2030 (USD MILLION)
  • TABLE 238. UNITED KINGDOM PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY DATA TYPE, 2018-2030 (USD MILLION)
  • TABLE 239. UNITED KINGDOM PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 240. UNITED KINGDOM PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY END-USE, 2018-2030 (USD MILLION)
  • TABLE 241. UNITED KINGDOM PREDICTIVE ANALYTICS FOR RETAIL MARKET SIZE, BY USAGE, 2018-2030 (USD MILLION)
  • TABLE 242. PREDICTIVE ANALYTICS FOR RETAIL MARKET SHARE, BY KEY PLAYER, 2024
  • TABLE 243. PREDICTIVE ANALYTICS FOR RETAIL MARKET, FPNV POSITIONING MATRIX, 2024