Analytical Study of On-shelf Availability Solution in Korea from 2024 to 2034

The utilization of on-shelf availability solution in Korea is estimated to display a promising CAGR of 8.3% through 2034. The sales of on-shelf availability solution in Korea are expected to jump from US$ 179.8 million in 2024 to US$ 397.6 million by 2034.

In recent years, digital innovations in eCommerce have transformed the face of the retail sector as well as customer expectations. To match the present expectation of an optimum shopping experience, retailers are adopting technological solutions like on-shelf availability (OSA) solutions to digitize their physical stores. Several players are presenting on-shelf availability solution integrated with artificial intelligence (AI) and image recognition (IR) to maximize store efficiency.

OSA solutions are increasingly being deployed by leading retailers in Korea. The chief reason behind OSA usage is to boost sales by diagnosing and fixing shelf and supply issues. By preventing out-of-stock incidents, retailers can sustain their customers and long-term sales.

Key providers of on-shelf availability solution in Korea are driven by the surging execution of new digital infrastructure like 5G networks. Cases of supply chain disruptions are also boosting the application of OSA solutions and software. These solutions empower end-users with automatic inventory monitoring by deploying technologies like cameras, sensors, and RFID. End-users also employ precise data to allow them to switch suppliers if supply chain disruptions are predicted.

Increasing investments in AI research and development are also expected to result in the advancement of OSA solutions. Forecasting future dynamics, retailer businesses are starting to prepare their employees for AI adoption.

Attributes Details
Industry size of On-shelf Availability Solution in Korea in 2024 US$ 179.8 million
Expected Industry Size of On-shelf Availability Solution in Korea by 2034 US$ 397.6 million
Forecast CAGR between 2024 to 2034 8.3%

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Deployment Analysis of On-shelf Availability Solution in Korea

  • Use of RFID technology and Internet of Things (IoT)-based sensors drives advancement in on-shelf availability solution.
  • The surging distribution of these solutions in the retail sector aims to maximize profits by identifying out-of-stock situations and improving inventory upkeep. Commonly, they are used by community-based hypermarkets and high-traffic retail stores.
  • Retailers in Korea are awakening to the importance of employing progressive technologies. Till now, machine learning (ML), artificial intelligence (AI), and virtual and augmented reality (VR/AR) have proved to be resourceful. Their use in these solutions spans demand forecasting, inventory planning, customer relationship management, logistics, etc.
  • The increasing supply of consumer goods and a robust retail sector in Korea is projected to dictate demand for advanced on-shelf availability solution.

Category-wise Insights

Software Segment to Take the Lead

Leading Component Software
Value Share % (2024) 55.60%

The software segment, as per estimations by our analysts, is anticipated to account for a value share of 55.60% in 2024. A key factor advancing the growth of this segment is the ongoing development of connective technology, which is based on on-shelf availability solution.

The increasing use of OSA software by store owners to implement corrective strategies is inducing the segment’s growth. Apart from this, the software helps predict upcoming inventory conditions like new product execution, distribution voids, and store compliance.

Potential Risk Analysis Holding a Prominent Percentage in the Application Category

Leading Application Potential Risk Analysis
Value Share % (2024) 32.20%

The potential risk analysis segment is projected to account for a share of 32.20% in 2024. OSA solutions are significantly employed by retailers to mitigate potential risks that may impact sales and profitability. The requirement for potential risk analysis is increasing to avoid situations like missed sales, out-of-stock products, and customer dissatisfaction.

Potential risk analysis is crucial during promotional periods. By using OSA solutions, retailers can make the most of sales opportunities by proactively replenishing stocked-out items. Furthermore, OSA data can help assess the performance of new product launches or identify any availability issues. Accordingly, brands can modify their marketing or promotion plans. Overall, by employing OSA solutions, end-users are elevating their operational efficiency, customer satisfaction, and boosting sales.

Sudip Saha
Sudip Saha

Principal Consultant

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Players Reaching for Higher Sales of On-shelf Availability Solution in Korea

Key players are focusing on research and development to lead in product innovations. Companies are expanding their portfolios to include OSA solutions like data analytics, real-time inventory tracking, predictive remodeling, etc. Additionally, they can be seen partnering with other players to develop advanced versions of on-shelf availability solution. Competitors are also using their resources to upgrade their existing solutions to align well with today's challenging demands. Apart from this, players are focusing on acquisitions, mergers, and expansion strategies to drive growth.

Profiles of Leading Players of On-shelf Availability Solution in Korea

Company Name Company Particulars
Panasonic Corporation Panasonic provides an extensive range of technology solutions. The on-shelf availability solution offered by the company are empowered by technologies like AI, RFID, and IR, to deliver real-time insights about product availability. These solutions help with category management and diminished revenue losses.
IBM Corporation IBM Corporation is leading provider of various technological solutions, such as on-shelf availability solution. These solutions are integrated with various latest technologies like RFID, artificial intelligence, and image recognition. In the past, company partnered with SAP to co-create solutions for consumer and retail packaged goods. The company is also investing in the development of retail transformation tools.
Impinj, Inc The company provides on-shelf availability solution that utilize RFID tags to locate the products and present real-time data on product availability. The wide-area RFID system completely automates inventory process by eliminating the requirement for hand-held readers. Retailers are planning to deploy OSA solutions across Korea.
Retail Solutions, Inc. The company provides on-shelf availability solution that combine image recognition, RFID, and sensor technology to offer real-time data on product availability. These solutions are utilized by various retailers across Korea, including supermarkets, convenience stores, and department stores. These solutions help manage retail sales across product portfolio by maximizing on-shelf availability and increasing sales.
Mindtree Ltd. The company offers digital transformation and technological services. The company provides OSA solutions, that help recapture money lost in sales and improve shopper satisfaction and retention.

Key Players Providing On-shelf Availability Solution in Korea

  • IBM Corporation
  • Panasonic Corporation
  • Impinj, Inc.
  • Verix
  • Mindtree Ltd.
  • eBest IOT
  • Retail Solutions, Inc.
  • Frontier Field Marketing
  • Lokad
  • Others

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Scope of Korea On-shelf Availability Solution Industry Report

Attribute Details
Estimated Industry Size of On-shelf Availability Solution in Korea in 2024 US$ 179.8 million
Projected Industry Size by 2034 US$ 397.6 million
Anticipated CAGR between 2024 to 2034 8.3% CAGR
Historical Analysis of Demand for On-shelf Availability Solution in Korea 2019 to 2023
Demand Forecast for On-shelf Availability Solution in Korea 2024 to 2034
By Component Software, Service
By Application Historical Data Analysis, Response Time Analysis, Vendor Pattern Analysis, Potential Risk Analysis
By Deployment Type On-premises, SaaS
By End User CPG Manufacturers, Retailers, Online Retailers, Suppliers, Warehouses
Report Coverage Industry Size, Industry Trends, Analysis of Key Factors Influencing On-shelf Availability Solution Deployment in Korea, Insights on Korea Players and their Industry Strategy in Korea, Ecosystem Analysis of Local and Regional Korea Providers
Key Companies Profiled for On-shelf Availability Solution in Korea IBM Corporation; Panasonic Corporation; Impinj, Inc.; Verix; Mindtree Ltd.; eBest IOT; Retail Solutions, Inc.; Frontier Field Marketing; Lokad; Others

Segments Covered in Korea On-shelf Availability Solution Industry Analysis

By Component:

  • Software
  • Service

By Application:

  • Historical Data Analysis
  • Response Time Analysis
  • Vendor Pattern Analysis
  • Potential Risk Analysis

By Deployment Type:

  • On-premises
  • SaaS

By End User:

  • CPG Manufacturers
  • Retailers
  • Online Retailers
  • Suppliers
  • Warehouses

By Province:

  • South Gyeongsang
  • North Jeolla
  • South Jeolla
  • Jeju

Frequently Asked Questions

At What Rate is the Adoption of On-shelf Availability Solution in Korea Growing?

The anticipated CAGR through 2034 is 8.3%.

How Big will the On-shelf Availability Solution Industry be in Korea?

Demand for on-shelf availability solution in Korea is expected to be US$ 397.6 million by 2034.

What is the Key Strategy that Providers in Korea Adopting?

Research and development is expected to be a default strategy for players.

Which Component is Highly Deployed?

Software component is a highly deployed on-shelf availability solution.

Which Application Takes Up Significant Share?

Potential risk analysis is a significant application segment for on-shelf availability solution.

Table of Content

1. Executive Summary

    1.1. Market Outlook

    1.2. Demand-side Trends

    1.3. Supply-side Trends

    1.4. Technology Roadmap Analysis

    1.5. Analysis and Recommendations

2. Market Overview

    2.1. Market Coverage / Taxonomy

    2.2. Market Definition / Scope / Limitations

3. Market Background

    3.1. Market Dynamics

        3.1.1. Drivers

        3.1.2. Restraints

        3.1.3. Opportunity

        3.1.4. Trends

    3.2. Scenario Forecast

        3.2.1. Demand in Optimistic Scenario

        3.2.2. Demand in Likely Scenario

        3.2.3. Demand in Conservative Scenario

    3.3. Opportunity Map Analysis

    3.4. Investment Feasibility Matrix

    3.5. PESTLE and Porter’s Analysis

    3.6. Regulatory Landscape

        3.6.1. By Key Regions

    3.7. Regional Parent Market Outlook

4. Industry Analysis and Outlook 2019 to 2023 and Forecast, 2024 to 2034

    4.1. Historical Market Size Value (US$ Million) Analysis, 2019 to 2023

    4.2. Current and Future Market Size Value (US$ Million) Projections, 2024 to 2034

        4.2.1. Y-o-Y Growth Trend Analysis

        4.2.2. Absolute $ Opportunity Analysis

5. Industry Analysis and Outlook 2019 to 2023 and Forecast 2024 to 2034, By Component

    5.1. Introduction / Key Findings

    5.2. Historical Market Size Value (US$ Million) Analysis By Component, 2019 to 2023

    5.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Component, 2024 to 2034

        5.3.1. Software

        5.3.2. Service

    5.4. Y-o-Y Growth Trend Analysis By Component, 2019 to 2023

    5.5. Absolute $ Opportunity Analysis By Component, 2024 to 2034

6. Industry Analysis and Outlook 2019 to 2023 and Forecast 2024 to 2034, By Application

    6.1. Introduction / Key Findings

    6.2. Historical Market Size Value (US$ Million) Analysis By Application, 2019 to 2023

    6.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Application, 2024 to 2034

        6.3.1. Historical Data Analysis

        6.3.2. Response Time Analysis

        6.3.3. Vendor Pattern Analysis

        6.3.4. Potential Risk Analysis

    6.4. Y-o-Y Growth Trend Analysis By Application, 2019 to 2023

    6.5. Absolute $ Opportunity Analysis By Application, 2024 to 2034

7. Industry Analysis and Outlook 2019 to 2023 and Forecast 2024 to 2034, By Deployment Type

    7.1. Introduction / Key Findings

    7.2. Historical Market Size Value (US$ Million) Analysis By Deployment Type, 2019 to 2023

    7.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Deployment Type, 2024 to 2034

        7.3.1. On-premises

        7.3.2. SaaS

    7.4. Y-o-Y Growth Trend Analysis By Deployment Type, 2019 to 2023

    7.5. Absolute $ Opportunity Analysis By Deployment Type, 2024 to 2034

8. Industry Analysis and Outlook 2019 to 2023 and Forecast 2024 to 2034, By End User

    8.1. Introduction / Key Findings

    8.2. Historical Market Size Value (US$ Million) Analysis By End User, 2019 to 2023

    8.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By End User, 2024 to 2034

        8.3.1. CPG Manufacturers

        8.3.2. Retailers

        8.3.3. Online Retailers

        8.3.4. Suppliers

        8.3.5. Warehouses

    8.4. Y-o-Y Growth Trend Analysis By End User, 2019 to 2023

    8.5. Absolute $ Opportunity Analysis By End User, 2024 to 2034

9. Industry Analysis and Outlook 2019 to 2023 and Forecast 2024 to 2034, By Region

    9.1. Introduction

    9.2. Historical Market Size Value (US$ Million) Analysis By Region, 2019 to 2023

    9.3. Current Market Size Value (US$ Million) Analysis and Forecast By Region, 2024 to 2034

        9.3.1. South Gyeongsang

        9.3.2. North Jeolla

        9.3.3. South Jeolla

        9.3.4. Jeju

        9.3.5. Rest of Korea

    9.4. Market Attractiveness Analysis By Region

10. South Gyeongsang Industry Analysis and Outlook 2019 to 2023 and Forecast 2024 to 2034

    10.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2019 to 2023

    10.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2024 to 2034

        10.2.1. By Component

        10.2.2. By Application

        10.2.3. By Deployment Type

        10.2.4. By End User

    10.3. Market Attractiveness Analysis

        10.3.1. By Component

        10.3.2. By Application

        10.3.3. By Deployment Type

        10.3.4. By End User

    10.4. Key Takeaways

11. North Jeolla Industry Analysis and Outlook 2019 to 2023 and Forecast 2024 to 2034

    11.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2019 to 2023

    11.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2024 to 2034

        11.2.1. By Component

        11.2.2. By Application

        11.2.3. By Deployment Type

        11.2.4. By End User

    11.3. Market Attractiveness Analysis

        11.3.1. By Component

        11.3.2. By Application

        11.3.3. By Deployment Type

        11.3.4. By End User

    11.4. Key Takeaways

12. South Jeolla Industry Analysis and Outlook 2019 to 2023 and Forecast 2024 to 2034

    12.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2019 to 2023

    12.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2024 to 2034

        12.2.1. By Component

        12.2.2. By Application

        12.2.3. By Deployment Type

        12.2.4. By End User

    12.3. Market Attractiveness Analysis

        12.3.1. By Component

        12.3.2. By Application

        12.3.3. By Deployment Type

        12.3.4. By End User

    12.4. Key Takeaways

13. Jeju Industry Analysis and Outlook 2019 to 2023 and Forecast 2024 to 2034

    13.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2019 to 2023

    13.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2024 to 2034

        13.2.1. By Component

        13.2.2. By Application

        13.2.3. By Deployment Type

        13.2.4. By End User

    13.3. Market Attractiveness Analysis

        13.3.1. By Component

        13.3.2. By Application

        13.3.3. By Deployment Type

        13.3.4. By End User

    13.4. Key Takeaways

14. Rest of Industry Analysis and Outlook 2019 to 2023 and Forecast 2024 to 2034

    14.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2019 to 2023

    14.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2024 to 2034

        14.2.1. By Component

        14.2.2. By Application

        14.2.3. By Deployment Type

        14.2.4. By End User

    14.3. Market Attractiveness Analysis

        14.3.1. By Component

        14.3.2. By Application

        14.3.3. By Deployment Type

        14.3.4. By End User

    14.4. Key Takeaways

15. Market Structure Analysis

    15.1. Competition Dashboard

    15.2. Competition Benchmarking

    15.3. Market Share Analysis of Top Players

        15.3.1. By Regional

        15.3.2. By Component

        15.3.3. By Application

        15.3.4. By Deployment Type

        15.3.5. By End User

16. Competition Analysis

    16.1. Competition Deep Dive

        16.1.1. NEOGRID

            16.1.1.1. Overview

            16.1.1.2. Product Portfolio

            16.1.1.3. Profitability by Market Segments

            16.1.1.4. Sales Footprint

            16.1.1.5. Strategy Overview

                16.1.1.5.1. Marketing Strategy

        16.1.2. eBest IOT

            16.1.2.1. Overview

            16.1.2.2. Product Portfolio

            16.1.2.3. Profitability by Market Segments

            16.1.2.4. Sales Footprint

            16.1.2.5. Strategy Overview

                16.1.2.5.1. Marketing Strategy

        16.1.3. SAP SE

            16.1.3.1. Overview

            16.1.3.2. Product Portfolio

            16.1.3.3. Profitability by Market Segments

            16.1.3.4. Sales Footprint

            16.1.3.5. Strategy Overview

                16.1.3.5.1. Marketing Strategy

        16.1.4. Impinj, Inc.

            16.1.4.1. Overview

            16.1.4.2. Product Portfolio

            16.1.4.3. Profitability by Market Segments

            16.1.4.4. Sales Footprint

            16.1.4.5. Strategy Overview

                16.1.4.5.1. Marketing Strategy

        16.1.5. Mindtree Ltd.

            16.1.5.1. Overview

            16.1.5.2. Product Portfolio

            16.1.5.3. Profitability by Market Segments

            16.1.5.4. Sales Footprint

            16.1.5.5. Strategy Overview

                16.1.5.5.1. Marketing Strategy

        16.1.6. Retail Solutions Inc.

            16.1.6.1. Overview

            16.1.6.2. Product Portfolio

            16.1.6.3. Profitability by Market Segments

            16.1.6.4. Sales Footprint

            16.1.6.5. Strategy Overview

                16.1.6.5.1. Marketing Strategy

        16.1.7. Retail Velocity

            16.1.7.1. Overview

            16.1.7.2. Product Portfolio

            16.1.7.3. Profitability by Market Segments

            16.1.7.4. Sales Footprint

            16.1.7.5. Strategy Overview

                16.1.7.5.1. Marketing Strategy

        16.1.8. Market6, Inc.

            16.1.8.1. Overview

            16.1.8.2. Product Portfolio

            16.1.8.3. Profitability by Market Segments

            16.1.8.4. Sales Footprint

            16.1.8.5. Strategy Overview

                16.1.8.5.1. Marketing Strategy

        16.1.9. Lokad

            16.1.9.1. Overview

            16.1.9.2. Product Portfolio

            16.1.9.3. Profitability by Market Segments

            16.1.9.4. Sales Footprint

            16.1.9.5. Strategy Overview

                16.1.9.5.1. Marketing Strategy

        16.1.10. Verix

            16.1.10.1. Overview

            16.1.10.2. Product Portfolio

            16.1.10.3. Profitability by Market Segments

            16.1.10.4. Sales Footprint

            16.1.10.5. Strategy Overview

                16.1.10.5.1. Marketing Strategy

        16.1.11. Frontier Field Marketing

            16.1.11.1. Overview

            16.1.11.2. Product Portfolio

            16.1.11.3. Profitability by Market Segments

            16.1.11.4. Sales Footprint

            16.1.11.5. Strategy Overview

                16.1.11.5.1. Marketing Strategy

        16.1.12. International Business Machines Corporation

            16.1.12.1. Overview

            16.1.12.2. Product Portfolio

            16.1.12.3. Profitability by Market Segments

            16.1.12.4. Sales Footprint

            16.1.12.5. Strategy Overview

                16.1.12.5.1. Marketing Strategy

        16.1.13. Panasonic Corporation

            16.1.13.1. Overview

            16.1.13.2. Product Portfolio

            16.1.13.3. Profitability by Market Segments

            16.1.13.4. Sales Footprint

            16.1.13.5. Strategy Overview

                16.1.13.5.1. Marketing Strategy

        16.1.14. Enterra Solutions LLC

            16.1.14.1. Overview

            16.1.14.2. Product Portfolio

            16.1.14.3. Profitability by Market Segments

            16.1.14.4. Sales Footprint

            16.1.14.5. Strategy Overview

                16.1.14.5.1. Marketing Strategy

17. Assumptions & Acronyms Used

18. Research Methodology

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