매장 내 분석 시장 : 점유율 분석, 업계 동향과 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the in-store analytics market size is expected to increase from USD 5.29 billion in 2025 to USD 6.38 billion in 2026 and reach USD 15.98 billion by 2031, growing at a CAGR of 20.16% over 2026-2031.

This report is Segmented by Component (Software, and Services), Deployment (Cloud, and On-Premises), Organization Size (Large Enterprises, and Small and Medium Enterprises), Application (Customer Management, Risk and Compliance Management, Store Operations Management, Merchandise Management, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global In-store Analytics Market Trends and Insights

Cloud-Native and Edge-Enabled Deployments

Hyperscalers now expose shelf-compliance and planogram-verification APIs via simple REST calls, eliminating the need for in-house model training and shrinking deployment cycles from months to days. AWS Edge Manager for Retail supports over-the-air camera firmware updates, synchronizing inference results with centralized data lakes in near real time. Intel-optimized OpenVINO appliances process up to 30 video streams at <75 watts, balancing performance and energy consumption for European supermarkets. Serverless compute, lightweight containers, and 5G backhaul collectively democratize advanced analytics once reserved for Fortune 500 retailers. As retailers standardize on hybrid stacks, vendors able to orchestrate seamless edge-to-cloud workflows win a disproportionate share.

Need for Better Customer Service and Enhanced Shopping Experience

Automated shelf-gap detection reduces out-of-stock incidents by 30%, freeing associates to focus on high-value engagement that lifts comparable-store sales by 4%. Occupancy heatmaps integrated with queue-management algorithms trigger staff redeployment when wait times exceed three minutes, improving checkout throughput in more than 2,000 Japanese convenience stores. Video analytics also power hyper-personalized interactions; pilots dispatch associates armed with loyalty data whenever dwell time in front of a category exceeds pre-set thresholds. These use cases satisfy 68% of consumers who say knowledgeable staff is the primary reason to visit physical stores over e-commerce. By merging digital signals with in-store context, retailers elevate service without swelling payroll costs.

Lack of Personnel Skills to Operationalize Insights

Firms face AI-skills gaps, with retail analytics positions staying open 50% longer than general IT roles, hampering time-to-value for projects. Mid-market chains lacking in-house data scientists often struggle to translate terabytes of video data into merchandising actions. Vendors counter by embedding automated insight generation that surfaces prioritized recommendations without manual querying. Yet these tools still assume a baseline level of statistical competence, widening the performance gap between digital leaders and laggards.

Other drivers and restraints analyzed in the detailed report include:

1. Real-Time Computer Vision and Video Analytics Breakthroughs
2. Dynamic Pricing Models Driven by In-Store Data
3. High Up-Front Sensor and Camera Retrofit Costs

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Services are expanding at 28.40% CAGR through 2031, outpacing the overall in-store analytics market growth because retailers outsource integration and managed analytics to close internal talent shortages. Software retained 70.01% of 2025 revenue as SaaS platforms delivered vision APIs and dashboards via subscription, yet complexity in marrying these tools with ERP, point-of-sale, and supply-chain systems drives demand for professional services. Capgemini expanded retail-analytics headcount by 35% in 2025, reflecting rising turnkey project volumes. IBM consulting engagements incorporating watsonx governance averaged USD 2.5 million per client, underscoring the premium for compliance-ready architectures.

Software itself is bifurcating between horizontal platforms and vertical solutions optimized for specific store formats. Oracle's Retail AI Foundation embeds demand-forecasting and shrink-detection models directly into its cloud ERP, cutting deployment timelines from six months to six weeks for existing customers. Vendors offering vendor-agnostic integration layers enable retailers to combine best-of-breed components while averting lock-in, sustaining double-digit services revenue growth.

Cloud deployments commanded 64.83% of 2025 revenue and are growing at 29.70% CAGR as hyperscalers insert retail-specific AI models into infrastructure offerings, streamlining updates and central analytics. Yet latency-sensitive use cases like autonomous checkout or real-time theft detection still require on-premises inference engines. The pragmatic outcome is a hybrid topology where edge appliances process video locally to stay within sub-50 millisecond targets, while aggregated insights feed cloud data lakes for machine-learning retraining. AWS Outposts for Retail co-locate rack-mounted AWS servers in store backrooms, maintaining residency for sensitive biometric data while exposing the broader AWS service catalog.

Microsoft Azure's collaboration with Trax preprocesses shelf images on associate smartphones before cloud validation, cutting egress fees by 60% and cycling planogram feedback in under 90 seconds. Anticipated passage of the EU AI Act by 2027 amplifies demand for audit logs and region-resident infrastructure, cementing hybrid as the default architecture in regulated markets.

Complete Report Scope:

• By Component
  • Software
  • Services
• By Deployment
  • Cloud
  • On-Premises
• By Organization Size
  • Large Enterprises
  • Small and Medium Enterprises
• By Application
  • Customer Management
  • Risk and Compliance Management
  • Store Operations Management
  • Merchandise Management
  • Other Applications
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Europe
    • Germany
    • United Kingdom
    • France
    • Italy
    • Spain
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • South Korea
    • India
    • Australia
    • New Zealand
    • Rest of Asia-Pacific
  • Middle East and Africa
    • Middle East
      • United Arab Emirates
      • Saudi Arabia
      • Turkey
      • Rest of Middle East
    • Africa
      • South Africa
      • Nigeria
      • Kenya
      • Rest of Africa

Geography Analysis

North America contributed 38.32% of 2025 revenue as mature omnichannel infrastructures and high labor costs justify automation investments. Pilot deployments of autonomous-checkout models by chains like Amazon Fresh showcase near-term demand for sub-second inference, sustaining leadership in the in-store analytics market. Asia-Pacific is the fastest expanding region at 27.40% CAGR, underpinned by China's social-commerce fusion, India's Unified Payments Interface enabling digital-first store formats, and Japan's aging workforce driving robotics investment. These factors compound to accelerate the in-store analytics market size across APAC urban centers despite heterogeneous infrastructure baselines.

Europe faces GDPR-linked compliance overhead that initially slows adoption, yet premium grocers in Germany and the United Kingdom now deploy computer vision to curb food waste and meet ESG reporting mandates. Electronic shelf labels tied to dynamic pricing have already become mainstream among French supermarkets following the Directorate General's 2025 guidelines, illustrating how clear rules can unlock pent-up demand. South America shows growing uptake in modern-trade formats, while currency volatility and capital constraints limit pace among domestic chains.

Middle Eastern smart-city initiatives in Dubai and Riyadh mandate sensor-ready retail infrastructure, enabling malls to embed analytics at construction rather than retrofit stages. African adoption remains embryonic beyond South Africa and Nigeria due to power instability and bandwidth costs, though franchisees of global quick-service brands pilot low-power occupancy sensors to optimize staffing. Vendors tailoring deployment to regional regulatory and infrastructure realities will capture outsize share as emerging markets mature.

1. Capgemini SE
2. RetailNext Inc.
3. Happiest Minds Technologies Ltd.
4. Capillary Technologies Global Pte. Ltd.
5. Thinkinside SRL
6. Trax Technology Solutions Pte. Ltd.
7. Cloud4Wi Inc.
8. Amoobi SA
9. Hoxton Analytics Ltd.
10. Motionloft Inc.
11. SAP SE
12. Oracle Corporation
13. IBM Corporation
14. Cisco Systems Inc.
15. Zebra Technologies Corporation
16. Johnson Controls International plc (Sensormatic Solutions)
17. Scanalytics Inc.
18. Dor Technologies Inc.
19. ShopperTrak (Part of Sensormatic)
20. Pathr.ai Inc.

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Cloud-Native and Edge-Enabled Deployments
  • 4.2.2 Need for Better Customer Service & Enhanced Shopping Experience
  • 4.2.3 Real-Time Computer Vision and Video Analytics Breakthroughs
  • 4.2.4 Dynamic Pricing Models Driven by In-Store Data
  • 4.2.5 Integration of In-Store Analytics with Retail Media Networks
  • 4.2.6 On-Device AI Chips Powering Battery-Free Shelf Cameras
• 4.3 Market Restraints
  • 4.3.1 Lack of Personnel Skills to Operationalize Insights
  • 4.3.2 High Up-Front Sensor and Camera Retrofit Costs
  • 4.3.3 Retailer Data-Sovereignty Concerns Over Cloud Storage
  • 4.3.4 Rising Energy Costs of GPU-Edge Appliances
• 4.4 Industry Value-Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Porter's Five Forces Analysis
  • 4.7.1 Bargaining Power of Buyers
  • 4.7.2 Bargaining Power of Suppliers
  • 4.7.3 Threat of New Entrants
  • 4.7.4 Threat of Substitutes
  • 4.7.5 Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Component
  • 5.1.1 Software
  • 5.1.2 Services
• 5.2 By Deployment
  • 5.2.1 Cloud
  • 5.2.2 On-Premises
• 5.3 By Organization Size
  • 5.3.1 Large Enterprises
  • 5.3.2 Small and Medium Enterprises
• 5.4 By Application
  • 5.4.1 Customer Management
  • 5.4.2 Risk and Compliance Management
  • 5.4.3 Store Operations Management
  • 5.4.4 Merchandise Management
  • 5.4.5 Other Applications
• 5.5 By Geography
  • 5.5.1 North America
    • 5.5.1.1 United States
    • 5.5.1.2 Canada
    • 5.5.1.3 Mexico
  • 5.5.2 South America
    • 5.5.2.1 Brazil
    • 5.5.2.2 Argentina
    • 5.5.2.3 Rest of South America
  • 5.5.3 Europe
    • 5.5.3.1 Germany
    • 5.5.3.2 United Kingdom
    • 5.5.3.3 France
    • 5.5.3.4 Italy
    • 5.5.3.5 Spain
    • 5.5.3.6 Rest of Europe
  • 5.5.4 Asia Pacific
    • 5.5.4.1 China
    • 5.5.4.2 Japan
    • 5.5.4.3 South Korea
    • 5.5.4.4 India
    • 5.5.4.5 Australia
    • 5.5.4.6 New Zealand
    • 5.5.4.7 Rest of Asia-Pacific
  • 5.5.5 Middle East and Africa
    • 5.5.5.1 Middle East
      • 5.5.5.1.1 United Arab Emirates
      • 5.5.5.1.2 Saudi Arabia
      • 5.5.5.1.3 Turkey
      • 5.5.5.1.4 Rest of Middle East
    • 5.5.5.2 Africa
      • 5.5.5.2.1 South Africa
      • 5.5.5.2.2 Nigeria
      • 5.5.5.2.3 Kenya
      • 5.5.5.2.4 Rest of Africa

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Market Share Analysis
• 6.4 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share, Products and Services, Recent Developments)
  • 6.4.1 Capgemini SE
  • 6.4.2 RetailNext Inc.
  • 6.4.3 Happiest Minds Technologies Ltd.
  • 6.4.4 Capillary Technologies Global Pte. Ltd.
  • 6.4.5 Thinkinside SRL
  • 6.4.6 Trax Technology Solutions Pte. Ltd.
  • 6.4.7 Cloud4Wi Inc.
  • 6.4.8 Amoobi SA
  • 6.4.9 Hoxton Analytics Ltd.
  • 6.4.10 Motionloft Inc.
  • 6.4.11 SAP SE
  • 6.4.12 Oracle Corporation
  • 6.4.13 IBM Corporation
  • 6.4.14 Cisco Systems Inc.
  • 6.4.15 Zebra Technologies Corporation
  • 6.4.16 Johnson Controls International plc (Sensormatic Solutions)
  • 6.4.17 Scanalytics Inc.
  • 6.4.18 Dor Technologies Inc.
  • 6.4.19 ShopperTrak (Part of Sensormatic)
  • 6.4.20 Pathr.ai Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment