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인스토어 애널리틱스 시장 : 성장, 동향, COVID-19의 영향과 예측(2021-2026년)

In-store Analytics Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022 - 2027)

리서치사 Mordor Intelligence Pvt Ltd
발행일 2022년 01월 상품코드 989411
페이지 정보 영문 배송안내 2-3일 (영업일 기준)
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인스토어 애널리틱스 시장 : 성장, 동향, COVID-19의 영향과 예측(2021-2026년) In-store Analytics Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022 - 2027)
발행일 : 2022년 01월 페이지 정보 : 영문

본 상품은 영문 자료로 한글과 영문 목차에 불일치하는 내용이 있을 경우 영문을 우선합니다. 정확한 검토를 위해 영문목차를 참고해주시기 바랍니다.

인스토어 애널리틱스 시장 규모는 2021-2026년의 예측 기간 중 17%의 CAGR로 확대할 거스로 예측됩니다. 인구통계학적 요인의 증가에 수반하여 소매 브랜드는 비지니스 판매를 늘리기 위한 첨단 테크놀러지의 도입에 중점을 두고 있습니다. 클라우드 컴퓨팅은 소매 브랜드가 초점을 맞추는 최근 동향입니다. 클라우드 컴퓨팅은 유연성이 높고 강력한 클라우드 기반 리포트 솔루션이며, 비지니스의 전체상을 제공하고, 핀매 증가에 수반하여 정보에 기반한 의사결정을 신속히 시행할 수 있습니다. 일부 기업은 독자적인 클라우드 기반 플랫폼을 통해 첨단 분석과 기계학습을 활용하고, 데이터 구동형 솔루션과 협업 컨설팅 서비스를 제공하고 있습니다. Shelfie 등의 기업은 일정한 간격으로 영상을 캡처하는 고정 카메라를 사용하고 있습니다. 클라우드 기반 첨단 기계학습 모듈은 영상 데이터가 처리되고 간과되거나 분실된 제품 및 라벨이 탐지 및 식별되는 선반 영상을 분석하기 위해 사용됩니다. 클라우드의 이점이 증가함에 따라 클라우드는 인스토어 애널리틱스 시장을 촉진한다고 하는 강력한 동향을 유지합니다.

점포 운영에 관한 데이터량의 증가가 시장을 촉진하고 있습니다. 미국 국세조사국에 따르면 2020년 1월 미국의 소매 판매량은 0.3% 증가했습니다. 이것에는 온라인 판매와 함께 실점포 판매량의 성장도 포함됩니다. 판매액의 증가에 수반하여 데이터량은 증가하고 있습니다. 데이터량이 증가하면 분석 기기를 도입하지 않고 모든 고객의 기록, 행동, 족적 등을 추적하는 것이 어려워집니다.

인스토어 애널리틱스 시장에 대해 조사했으며, 시장의 개요와 컴포넌트별, 도입별, 조직 규모별, 용도별, 지역별 동향 및 시장에 참여하는 기업의 개요 등을 정리하여 전해드립니다.

목차

제1장 서론

제2장 조사 방법

제3장 주요 요약

제4장 시장 역학

  • 시장 개요
  • 시장 촉진요인
    • 점포 운영에 관련된 데이터량의 증가
    • 더 나은 고객 서비스와 강화된 쇼핑 체험의 필요성
  • 시장 억제요인
    • 인사 스킬의 결여
  • 업계의 밸류체인 분석
  • 업계의 매력 - Porter's Five Forces 분석
    • 신규 진출업체의 위협
    • 구매자의 교섭력/소비자의 교섭력
    • 공급 기업의 교섭력
    • 대체품의 위협
    • 경쟁 기업간 경쟁 관계
  • Covid-19의 업계에 대한 영향 평가

제5장 시장 세분화

  • 컴포넌트별
    • 소프트웨어
    • 서비스
  • 도입별
    • 클라우드
    • 온프레미스
  • 조직 규모별
    • 대기업
    • 중소기업
  • 용도별
    • 고객 관리
    • 리스크와 컴플라이언스 관리
    • 점포 운영 관리
    • 상품 관리
    • 기타
  • 지역별
    • 북미
    • 유럽
    • 아시아태평양
    • 라틴아메리카
    • 중동과 아프리카

제6장 경쟁 구도

  • 기업 개요
    • Capgemini SE
    • RetailNext, Inc.
    • Happiest Minds Technologies
    • Capillary Technologies
    • Thinkinside SRL
    • Trax Image Recognition
    • Cloud4Wi, Inc.
    • Amoobi Inc.
    • Hoxton Analytics Limited
    • Motionloft Inc.

제7장 투자 분석

제8장 시장 기회 및 향후 전망

KSA 21.02.23

The in-store analytics market is anticipated to grow at a CAGR of 17% during the forecast period of 2021 - 2026. With increasing demographic factors, retail brands are more focused on implementing advanced technology to increase business sales. Cloud computing is a recent trend in which retail brands are focused on implementing. Cloud computing is a highly flexible and powerful cloud-based reporting solution that provides a complete view of the business, and empowering to make informed decisions faster with increasing sales. Some firms provide data-driven solutions and collaborative consulting services, leveraged on advanced analytics and machine learning through a proprietary cloud-based platform. Players such as Shelfie uses fixed cameras that capture images at regular intervals. Its Cloud-based advanced machine learning modules are used to analyze the shelf images where the image data is processed and missing, or misplaced products and labels are detected and identified. With the increasing advantage of the cloud, it further holds a strong trend in driving the in-store analytics market.

Key Highlights

  • Increasing data volume around in-store operations drives the market. According to the U.S. Census Bureau., United States retail sales rose 0.3% in January 2020, which also includes the increase in the sales growth of brick and mortar outlets along with online sales. With increasing sales value, the volume of data is increasing. With increasing data volume, it becomes difficult to track every customer's records, behaviors, fall foot, etc, without the implementation of analytics.
  • Further, according to NewGenApps, retailers who prefer to choose to leverage the full potential of big data analytics can optimize their operating margins by approximately 60%. Also, the omnichannel retailer can monitor in-store customer behavior and drive timely offers to customers to incent in-store purchases or later online purchases, thereby keeping the purchase within the fold of the retailer. So, due to the above those factors, the adoption of in-store analytics drives the market.
  • Better customer service and enhanced shopping experience requirements drive the market. In-store analytics offers a profound understanding of the consumer behavior inside the store. Tracing their shopping patterns and dwelling times can unlock immense opportunities for all kinds of retail operations, from individual stores to sprawling shopping malls. Managers can better form the kind of layouts that catch eyeballs, the product placements that draw maximum attention, and the service delivery quality that customers feel more pleased with. With these metrics at hand, retailers can analyze the best staffing options, the most appealing design techniques, and the most effective selling tactics. Further, knowing the busiest store periods will help ensure that the staffing levels are appropriate to meet customer demand. This keeps costs down, drives conversion rates up, and improves the customer journey within the store.
  • Further, currently, due to the COVID-19 pandemic, the business growth for analytics service providers is penetrating. As businesses for brick and mortar are shuttered during this pandemic, it is clear how important the cloud is for continuity of operations. Any retail organization that actively resisted digitalization may now confronted with a harsh reality of pandemic. This puts cloud providers in a strong position. In-store analytics also provides a platform for the supply chain distribution chain, which further holds the demand for the market in this critical situation.
  • However, the lack of personnel skills is challenging the growth of the market. The market faces few issues owing to the lack of skilled personnel, which are not highly efficient enough to derive the required and vital insights from the retail data.

Key Market Trends

Customer Analytics Under Customer Management to Witness Significant Market Growth

  • According to the US Department of Commerce, global retail sales in 2020 are estimated to be USD 27.7 trillion, with an increase of USD 1.4 trillion compare to the previous year. With increasing sales, the other factors, such as rapidly changing demographics and uncertain economic recovery, often present retailers with challenges. Thus, retailers try to understand which products, services, and offers are more attractive to customers, which significantly cater to the importance of the in-store analytics platform and further needs the demand of consumer engagement analytics for the retailers.
  • Brazilian retail analytics platform developer startup, Decision 6, specially focus on brick and mortar stores. Their analytics solution uses AI and deep learning for tracking the flow of customers into and out of a store. This information is used to optimize single store operation and compare the footfall data among different stores to measure their performance.
  • Further, AI-based video analytics also create efficiencies and offering non-security-related insights for businesses. In the retail market, for example, store owners using surveillance cameras with analytics can spot shoplifters and alert security personnel to intervene in real-time. The in-store analytics can also measure hotspots, visitor flow, dwell time, and product display activity.
  • Further, stores usually collect data from different types of sensors. As the number of tools and platforms increases due to the requirement to process all these types of data, the cost-to-performance ratio of the technology begins to decline. Startups are focused on developing centralized platforms processing all the data types for a store, and assist in making vital decisions. Slovakian startup Pygmalios designs a tool that accumulates all types of sensor data in a store and helps them to analyze customer's behavior in real-time through a single cloud-based app. This allows companies to optimize their product placement and customer flow.
  • Further, Beacon analytics is an incredibly effective way which enable retailers to capture invaluable data about their consumer shopping trends. By tracking a customer's in-store movement, retailers are able to deliver targeted information and discounts depending on which products customer is perusing. This can lead to higher conversion rates. Players such as Swirl Networks Inc. found over 70% of shoppers say beacon-triggered content and offers increased their likelihood to purchase in-store.
  • Further global brand players are seeking for the acquisition of a retail analytics company to serve consumers more personally at scale. For instance, in August 2019, Nike acquired Celect, a retail predictive analytics firm, where Nike announces its strategy for looking to serve customers personally and on a global scale, reducing its reliance on wholesale operations and third-party retail partners for in-store analytics. As the demand for their products is growing, Nike wants to be insight-driven, data-optimized, and hyper-focused on consumer behavior.

North America Accounts for Significant Market Share

  • With the presence of the highest number of technology innovators and increasing adoption of in-store analytics by the retail corporations to enhance customer's buying experience, this region witness a significant market share. According to the National Retail Federation (NRF), United States retail sales are expected to rise between 3.8 percent and 4.4 percent to more than USD 3.8 trillion in 2020.
  • Since Diageo embedded EDGE in early 2019, they have seen average volume in outlets that have adopted their recommendations grew three times faster than non-participating outlets in the United States. In the United States, Diageo has collected more than four million data points over the last two years.
  • Diageo uses new technologies and advanced analytics to unlock growth by transforming their understanding of customers, consumers, and shoppers. Their suite of 'Every Day Great Execution' (EDGE) technology tools capture in-store data and, through predictive analytics, revolutionize their ability to offer the right brands, in the right outlets, in the right way. Their TRAX technology uses image recognition to analyze a picture of the inside of a store, then automatically identifies products, shelf placement, display, price, and more. They can then generate scorecards based on these key performance indicators and provide targeted recommendations via their advanced analytics team.
  • Further, most of the United States CEOs who participate in the retail industry are keen to reinvent the bricks-and-mortar platform along with their online purchase. In September 2019, Microsoft expanded Dynamics 365 with e-commerce along with in-store modules. Dynamics 365 gets new IoT analytics tools, including Product Insights, to provide additional services to customers with connected devices and IoT Intelligence for supply chain management to help adapt production to changes in the supply chain. Further, allowing vendors to create and manage online stores and connecting it with existing retail outlets to provide in-store pick-up is one of the benefit. Also, the commerce and connected store applications can extend the reach of Microsoft's ERP and CRM suite, which help the retailers selling through multiple channels.
  • Further, due to COVID-19's impact on the US Retail Industry, the retail companies generate a huge base of unstructured data at an unprecedented rate, which makes it challenging to identify and capitalize on new lucrative opportunities. To cater to this issue, in April 2020, Quantzig announced that they would assist through the use of advanced retail data analytics solutions helping companies drive positive outcomes for business growth.
  • The post-pandemic world will be shaped to several factors contributing significantly to how retailers function. Their retail analytics solutions for the US retail industry will focus on dealing with challenges arises from heightened complexities and help to improve the market share. Their ability to offer actionable insights by analyzing multiple data sets will help their retail clients identifying the right strategies for recovering lost sales and boost market share by addressing the dynamic needs of its customers.

Competitive Landscape

The in-store analytics market is fragmented in nature due to several numbers of players who keep on innovating new platforms, which penetrates the rivalry in the market. Key players are Capgemini SE, RetailNext, Inc., etc. Recent developments in the market are -

  • April 2019 - Walmart, deployed AI technology to monitor retail stores in real-time. The company is digitizing its stores with an objective to enhance the customer's buying experience. The technology holds to find the spills in the store and identify when the shelves need to be refilled or when the shopping cart is running less.
  • January 2019 - Thinkinside added a new module, Funnel Analysis, in its in-store analytics platform, RetailerIN. This module enables supermarkets and grocery stores to fully analyze the complete shopping funnel by integrating sales data.

Additional Benefits:

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

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Deliverables
  • 1.2 Study Assumptions
  • 1.3 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET DYNAMICS

  • 4.1 Market Overview
  • 4.2 Market Drivers
    • 4.2.1 Increasing Data Volume Around In-Store Operations
    • 4.2.2 Need for Better Customer Service and Enhanced Shopping Experience
  • 4.3 Market Restraints
    • 4.3.1 Lack of Personnel Skills
  • 4.4 Industry Value Chain Analysis​
  • 4.5 Industry Attractiveness - Porter's Five Forces Analysis​
    • 4.5.1 Threat of New Entrants
    • 4.5.2 Bargaining Power of Buyers/Consumers
    • 4.5.3 Bargaining Power of Suppliers
    • 4.5.4 Threat of Substitute Products
    • 4.5.5 Intensity of Competitive Rivalry
  • 4.6 Assessment of Impact of Covid-19 on the Industry

5 MARKET SEGMENTATION

  • 5.1 Component
    • 5.1.1 Software
    • 5.1.2 Services
  • 5.2 Deployment
    • 5.2.1 Cloud
    • 5.2.2 On-Premises
  • 5.3 Organization Size
    • 5.3.1 Large Enterprises
    • 5.3.2 Small & Medium Enterprises
  • 5.4 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 Geography
    • 5.5.1 North America
      • 5.5.1.1 US
      • 5.5.1.2 Canada
    • 5.5.2 Europe
      • 5.5.2.1 Germany
      • 5.5.2.2 UK
      • 5.5.2.3 France
      • 5.5.2.4 Rest of Europe
    • 5.5.3 Asia-Pacific
      • 5.5.3.1 India
      • 5.5.3.2 China
      • 5.5.3.3 Japan
      • 5.5.3.4 Rest of Asia-Pacific
    • 5.5.4 Latin America
      • 5.5.4.1 Brazil
      • 5.5.4.2 Mexico
      • 5.5.4.3 Rest of Latin America
    • 5.5.5 Middle-East and Africa

6 COMPETITIVE LANDSCAPE

  • 6.1 Company Profiles
    • 6.1.1 Capgemini SE
    • 6.1.2 RetailNext, Inc.
    • 6.1.3 Happiest Minds Technologies
    • 6.1.4 Capillary Technologies
    • 6.1.5 Thinkinside SRL
    • 6.1.6 Trax Image Recognition
    • 6.1.7 Cloud4Wi, Inc.
    • 6.1.8 Amoobi Inc.
    • 6.1.9 Hoxton Analytics Limited
    • 6.1.10 Motionloft Inc.

7 INVESTMENT ANALYSIS

8 MARKET OPPORTUNITIES AND FUTURE TRENDS

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