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In-store Analytics Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2024 to 2032
Market Report I 2024-10-11 I 180 Pages I Global Market Insights
The Global In-Store Analytics Market was valued at USD 3.3 billion in 2023 and is expected to grow significantly, with a compound annual growth rate (CAGR) of 21.3% projected from 2024 to 2032. The rapid growth of Internet of Things (IoT) technologies and interconnected devices in retail help in driving this expansion. With innovations like RFID tags, beacons, smart shelves, and video analytics cameras, retailers gain real-time insights into both store operations and customer behavior. These technologies generate vast amounts of data, which require sophisticated analytics for effective processing and understanding. One of the primary factors propelling the in-store analytics market is the increasing demand for efficient inventory management.
Retailers face constant pressure to optimize stock levels while minimizing costs and waste, all while ensuring product availability. In-store analytics provide vital real-time information regarding inventory levels, product movement, and demand trends, enabling informed decision-making. Additionally, retail analytics tools enhance necessity forecasting, help detect slow-moving items, and rationalize restocking processes. As retailers adapt to supply chain challenges and changing consumer preferences, investments in advanced analytics tools for inventory management are becoming more prevalent.
In terms of market components, the software segment dominated in 2023, accounting for over 70% of the total market share, and projected to exceed USD 12 billion by 2032. The increasing need for modern in-store analytics software arises from its seamless integration capabilities with existing retail management systems. Retailers are looking for solutions that can easily connect with their point-of-sale (POS) systems, inventory management platforms, and customer relationship management (CRM) tools. As businesses strive to eliminate data silos and foster unified analytics environments, the demand for these integrated solutions drives significant investments in compatible software. The cloud-based deployment model is also gaining traction, with projections indicating it will exceed USD 13 billion by 2032. Retailers are increasingly adopting cloud solutions for in-store analytics due to their scalability and cost-effectiveness.
These cloud services often utilize pay-as-you-go pricing models, allowing businesses to enhance their analytics capabilities without incurring large upfront costs. This flexibility is particularly beneficial for retail chains experiencing seasonal fluctuations or rapid growth, enabling them to adapt their analytics capacity to meet demand. Furthermore, cloud solutions minimize hardware maintenance costs and facilitate the rapid rollout of new analytics features across various locations. In the United States, the in-store analytics market accounted for more than 75% of total revenue in 2023. Retailers in this region are leveraging AI-driven predictive analytics to refine inventory management, utilizing historical sales data and trends to optimize stock levels.
This approach improves profit margins and reduces waste, ultimately leading to a more efficient and responsive supply chain that can adjust to anticipated demand changes.
Report Content
Chapter 1 Methodology & Scope
1.1 Research design
1.1.1 Research approach
1.1.2 Data collection methods
1.2 Base estimates and calculations
1.2.1 Base year calculation
1.2.2 Key trends for market estimates
1.3 Forecast model
1.4 Primary research & validation
1.4.1 Primary sources
1.4.2 Data mining sources
1.5 Market definitions
Chapter 2 Executive Summary
2.1 Industry 360synopsis, 2021 - 2032
Chapter 3 Industry Insights
3.1 Industry ecosystem analysis
3.2 Supplier landscape
3.2.1 Software providers
3.2.2 Cloud service providers
3.2.3 IT platform providers
3.2.4 Technology integrators
3.2.5 End users
3.3 Profit margin analysis
3.4 Technology differentiators
3.4.1 Advanced AI & machine learning algorithms
3.4.2 Computer vision and image recognition
3.4.3 IoT sensors and RFID integration
3.4.4 Omnichannel data integration
3.4.5 Others
3.5 Key news & initiatives
3.6 Regulatory landscape
3.7 Impact forces
3.7.1 Growth drivers
3.7.1.1 Rising demand for enhanced customer experience
3.7.1.2 Growth of connected devices in the retail sector
3.7.1.3 Increasing focus on inventory optimization
3.7.1.4 Growing competition from E-commerce platforms
3.7.2 Industry pitfalls & challenges
3.7.2.1 High initial implementation costs
3.7.2.2 Integration complexity with legacy systems
3.8 Growth potential analysis
3.9 Porter's analysis
3.10 PESTEL analysis
Chapter 4 Competitive Landscape, 2023
4.1 Introduction
4.2 Company market share analysis
4.3 Competitive positioning matrix
4.4 Strategic outlook matrix
Chapter 5 Market Estimates & Forecast, By Component, 2021 - 2032 ($Bn)
5.1 Key trends
5.2 Software
5.2.1 Data analytics platforms
5.2.2 Virtualization tools
5.2.3 Others
5.3 Services
5.3.1 Professional services
5.3.2 Managed services
Chapter 6 Market Estimates & Forecast, By Deployment Mode, 2021 - 2032 ($Bn)
6.1 Key trends
6.2 Cloud-based
6.3 On-premises
Chapter 7 Market Estimates & Forecast, By Organization Size, 2021 - 2032 ($Bn)
7.1 Key trends
7.2 SME
7.3 Large enterprises
Chapter 8 Market Estimates & Forecast, By Application, 2021 - 2032 ($Bn)
8.1 Key trends
8.2 Marketing management
8.3 Customer behavior analysis
8.4 Merchandising analysis
8.5 Store operations
8.6 Security & loss prevention
8.7 Others
Chapter 9 Market Estimates & Forecast, By End Use, 2021 - 2032 ($Bn)
9.1 Key trends
9.2 Retail
9.3 Hospitality
9.4 Healthcare
9.5 Others
Chapter 10 Market Estimates & Forecast, By Region, 2021 - 2032 ($Bn)
10.1 Key trends
10.2 North America
10.2.1 U.S.
10.2.2 Canada
10.3 Europe
10.3.1 UK
10.3.2 Germany
10.3.3 France
10.3.4 Spain
10.3.5 Italy
10.3.6 Russia
10.3.7 Nordics
10.4 Asia Pacific
10.4.1 China
10.4.2 India
10.4.3 Japan
10.4.4 South Korea
10.4.5 ANZ
10.4.6 Southeast Asia
10.5 Latin America
10.5.1 Brazil
10.5.2 Mexico
10.5.3 Argentina
10.6 MEA
10.6.1 UAE
10.6.2 South Africa
10.6.3 Saudi Arabia
Chapter 11 Company Profiles
11.1 Capgemini
11.2 Capillary Technologies
11.3 Cloud4WI
11.4 CountBox
11.5 Happiest Minds
11.6 Kepler Analytics
11.7 Mindtree
11.8 Microsoft
11.9 Quividi
11.10 RetailNext
11.11 Scanalytics
11.12 sensalytics
11.13 Sensormatic (Johnson Controls)
11.14 Sisense
11.15 SmartConnect
11.16 Thinkin
11.17 Trax Technology Solutions
11.18 V-Count
11.19 Vispera
11.20 Walkbase
11.21 Zebra Technologies
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