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Digital Twin Strategies in Global Retail: Key Developments and Strategies

  • Report

  • 19 Pages
  • March 2025
  • Region: Global
  • Market Intelligence & Consulting Institute (MIC)
  • ID: 6057279
As digital twin technology matures, its application in the retail sector is expected to reach nearly USD 10 billion by 2030. By bridging physical and virtual environments through spatial computing, digital twins enhance decision-making efficiency and operational quality.

This report analyzes the strategic approaches of leading global players in digital twin retail applications, offering insights for companies seeking entry points into this emerging field.

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Table of Contents

1. Global Trends in Digital Twin Adoption in Retail
1.1 The Path to Omnichannel: Opportunities for Digital Twin Applications in Retail
1.1.1 Integration Challenges: The Complexity of Holistic Customer Profiling
1.1.2 Simulation Capabilities: Reimagining Store Management and Customer Experience
1.1.3 Predictive Insights: Balancing Customer Experience and Operational Efficiency
1.2 The Three Stages of Digital Twin Platform Development: Modeling, Integration, and Predictive Analytics
1.3 Key Applications of Digital Twins in Retail
1.3.1 Application Focus #1: Strengthening the Decision-Making Foundation in Retail
1.3.2 Application Focus #2: Enhancing Omnichannel Customer Experience
1.4 The Global Digital Twin Retail Ecosystem Is Taking Shape
1.4.1 The Rise of Digital Twin Retail: A Global Submarket Collaboration Approach
1.4.2 Key Players with Market Potential in Digital Twin Retail
2. Strategies of Leading Industry Players
2.1 Product Strategy
2.1.1 Basic Platform: Customization, 3D Modeling & AI Expansion
2.1.2 Value-Added Services: VR/AR Integration & Retail Connectivity
2.2 Data Integration Strategies
2.2.1 Basic Platform: Features Unified 3D Data Formats and AI-Integrated Development
2.2.2 Value-Added Services: Focuses on Integrating And Analyzing Retail Commerce Data
3. Key Case Studies on Digital Twin Adoption in Retail
3.1 Case 1: Nvidia Uses a Customized Platform and Retail Data for Diverse Simulations
3.2 Case 2: Matterport Integrates AI Multimodal Tech to Speed Up Data Processing
3.3 Case 3: Treedis Utilizes VR and AR to Create an Intuitive Interface, Reducing Planning Time
3.4 Case 4: Treedis Integrates Commerce Tools to Enhance the Online Shopping Experience
4. The Analyst's PerspectiveAppendixList of Companies
List of Tables
Table 1: Key Players in the Global Digital Twin Retail Ecosystem
Table 2. Potential Data Requirements for Digital Twin Applications in Retail
Table 3: Comparative Analysis of Key Cases
List of Figures
Figure 1: Global Digital Twin Retail Market Size, 2023-2030
Figure 2: The Three Phases of Digital Twin Platform Evolution
Figure 3: Global Digital Twin Retail: The Three Key Submarket Divisions
Figure 4: Product Strategy Comparison of Key Players in the Basic Platform Sector
Figure 5: Product Strategy Comparison of Key Players in the Value-Added Services Sector
Figure 6: Implementation Results at Lowe's (USA)
Figure 7: Implementation Results at Tsuen Wan Plaza (Hong Kong)
Figure 8: Implementation Results at Trax Retail (Singapore)
Figure 9: Implementation Results at Optical Center

Companies Mentioned (Partial List)

A selection of companies mentioned in this report includes, but is not limited to:

  • Activeloop
  • Alibaba
  • Amazon
  • AT&T
  • AWM
  • AWS
  • Azure
  • Baidu
  • China Mobile
  • China Telecom
  • China Unicom
  • Cisco
  • CoStar Group
  • Dassault Systemes
  • DeepBrain AI
  • Delve AI
  • Dôr
  • Future-Shape
  • Gemini
  • Google Cloud
  • Huawei
  • JET BI
  • KDDI
  • Kepler Analytics
  • Lowe’s
  • Magentaverse
  • Matterport
  • Mawari Network
  • MOKOBlue
  • Multi-Tech Systems
  • Nanomade
  • Neoalto
  • NTT Docomo
  • Nvidia
  • Oracle
  • Peak
  • ReadySet
  • Relex
  • Resonai
  • RetailNext
  • SK telecom
  • Sturfee
  • SymphonyAI
  • Telefonica
  • Tencent
  • Trax Retail
  • Treedis
  • T-Systems
  • Unity
  • Vodafone
  • Walmart
  • Xovis

Methodology

Primary research with a holistic, cross-domain approach

The exhaustive primary research methods are central to the value that the analyst delivers. A combination of questionnaires and on-site visits to the major manufacturers provides a first view of the latest data and trends. Information is subsequently validated by interviews with the manufacturers' suppliers and customers, covering a holistic industry value chain. This process is backed up by a cross-domain team-based approach, creating an interlaced network across numerous interrelated components and system-level devices to ensure statistical integrity and provide in-depth insight.

Complementing primary research is a running database and secondary research of industry and market information. Dedicated research into the macro-environmental trends shaping the ICT industry also allows the analyst to forecast future development trends and generate foresight perspectives. With more than 20 years of experience and endeavors in research, the methods and methodologies include:

Method

  • Component supplier interviews
  • System supplier interviews
  • User interviews
  • Channel interviews
  • IPO interviews
  • Focus groups
  • Consumer surveys
  • Production databases
  • Financial data
  • Custom databases

Methodology

  • Technology forecasting and assessment
  • Product assessment and selection
  • Product life cycles
  • Added value analysis
  • Market trends
  • Scenario analysis
  • Competitor analysis

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