Internet Of Things In Retail Market By Component
Internet Of Things In Retail Market By Technology
Internet Of Things In Retail Market By Deployment
Internet Of Things In Retail Market By Application
Internet Of Things In Retail Market By Region-
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global Internet Of Things In Retail Market Snapshot
Chapter 4. Global Internet Of Things In Retail Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis
Chapter 5. Market Segmentation 1: by Application Estimates & Trend Analysis
5.1. by Application & Market Share, 2019 & 2031
5.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Application:
5.2.1. Operations Management
5.2.1.1. Inventory Management
5.2.1.2. Supply Chain Automation
5.2.1.3. Workforce Management
5.2.1.4. Security & Safety
5.2.2. Customer Management
5.2.2.1. Smart Vending Machine
5.2.2.2. Smart Shelves
5.2.2.3. Queue Management
5.2.2.4. Automated Checkout
5.2.3. Asset Management
5.2.3.1.1. Asset Tracking
5.2.3.1.2. Predictive Maintenance
5.2.4. Advertising and Marketing
5.2.4.1. Smart Digital Signage
5.2.4.2. Geomarketing
5.2.4.3. Others
Chapter 6. Market Segmentation 2: by Component Estimates & Trend Analysis
6.1. by Component & Market Share, 2019 & 2031
6.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Component:
6.2.1. Hardware
6.2.1.1. Beacons
6.2.1.2. RFID Tags
6.2.1.3. Sensors
6.2.1.4. Wearables
6.2.2. Platform
6.2.2.1. Connectivity Management
6.2.2.2. Application Management
6.2.2.3. Device Management
6.2.3. Services
6.2.3.1. Professional Services
6.2.3.2. Managed Services
Chapter 7. Market Segmentation 3: By Technology Estimates & Trend Analysis
7.1. By Technology & Market Share, 2019 & 2031
7.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following By Technology:
7.2.1. Bluetooth Low Energy
7.2.2. Near Field Communication
7.2.3. Zigbee
7.2.4. Others
Chapter 8. Market Segmentation 4: By Deployment Estimates & Trend Analysis
8.1. By Deployment & Market Share, 2019 & 2031
8.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following By Deployment:
8.2.1. On-premise
8.2.2. Cloud
Chapter 9. Internet Of Things In Retail Market Segmentation 5: Regional Estimates & Trend Analysis
9.1. North America
9.1.1. North America Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.1.2. North America Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts by Component, 2024-2031
9.1.3. North America Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts By Technology, 2024-2031
9.1.4. North America Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts By Deployment, 2024-2031
9.1.5. North America Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.2. Europe
9.2.1. Europe Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.2.2. Europe Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts by Component, 2024-2031
9.2.3. Europe Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts By Technology, 2024-2031
9.2.4. Europe Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts By Deployment, 2024-2031
9.2.5. Europe Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.3. Asia Pacific
9.3.1. Asia Pacific Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.3.2. Asia Pacific Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts by Component, 2024-2031
9.3.3. Asia-Pacific Thermal Cyclers Asia-Pacific Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts By Technology, 2024-2031
9.3.4. Asia-Pacific Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts By Deployment, 2024-2031
9.3.5. Asia Pacific Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.4. Latin America
9.4.1. Latin America Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.4.2. Latin America Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts by Component, 2024-2031
9.4.3. Latin America Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts By Technology, 2024-2031
9.4.4. Latin America Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts By Deployment, 2024-2031
9.4.5. Latin America Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.5. Middle East & Africa
9.5.1. Middle East & Africa Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.5.2. Middle East & Africa Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts by Component, 2024-2031
9.5.3. Middle East & Africa Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts By Technology, 2024-2031
9.5.4. Middle East & Africa Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts By Deployment, 2024-2031
9.5.5. Middle East & Africa Internet Of Things In Retail Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
Chapter 10. Competitive Landscape
10.1. Major Mergers and Acquisitions/Strategic Alliances
10.2. Company Profiles
10.2.1. Accenture
10.2.2. Allerin Tech Pvt Ltd
10.2.3. Amazon Web Services
10.2.4. Arm Limited
10.2.5. AT&T
10.2.6. Bosch.IO GmBH
10.2.7. Cisco Systems Inc.
10.2.8. Google LLC
10.2.9. Happiest Minds Technologies
10.2.10. Huawei Enterprise
10.2.11. IBM Corporation
10.2.12. Intel Corporation
10.2.13. Losant IoT
10.2.14. Microsoft Corporation
10.2.15. NEC Corporation
10.2.16. NXP Semiconductors
10.2.17. Oracle
10.2.18. PTC Inc.
10.2.19. RetailNext, Inc.
10.2.20. SAP SE
10.2.21. Sierra Wireless
10.2.22. Software AG
10.2.23. Softweb Solutions Inc.
10.2.24. Telit Cinterion
10.2.25. Verizon Communications Inc.
10.2.26. Vodafone
10.2.27. Zebra Technologies Corporation
This study employed a multi-step, mixed-method research approach that integrates:
This approach ensures a balanced and validated understanding of both macro- and micro-level market factors influencing the market.
Secondary research for this study involved the collection, review, and analysis of publicly available and paid data sources to build the initial fact base, understand historical market behaviour, identify data gaps, and refine the hypotheses for primary research.
Secondary data for the market study was gathered from multiple credible sources, including:
These sources were used to compile historical data, market volumes/prices, industry trends, technological developments, and competitive insights.
Primary research was conducted to validate secondary data, understand real-time market dynamics, capture price points and adoption trends, and verify the assumptions used in the market modelling.
Primary interviews for this study involved:
Interviews were conducted via:
Primary insights were incorporated into demand modelling, pricing analysis, technology evaluation, and market share estimation.
All collected data were processed and normalized to ensure consistency and comparability across regions and time frames.
The data validation process included:
This ensured that the dataset used for modelling was clean, robust, and reliable.
The bottom-up approach involved aggregating segment-level data, such as:
This method was primarily used when detailed micro-level market data were available.
The top-down approach used macro-level indicators:
This approach was used for segments where granular data were limited or inconsistent.
To ensure accuracy, a triangulated hybrid model was used. This included:
This multi-angle validation yielded the final market size.
Market forecasts were developed using a combination of time-series modelling, adoption curve analysis, and driver-based forecasting tools.
Given inherent uncertainties, three scenarios were constructed:
Sensitivity testing was conducted on key variables, including pricing, demand elasticity, and regional adoption.