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. MIC Perspective
Appendix
List of Companies