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세계의 소매용 AI(인공지능) 시장 : 부문별 분석, 벤더 포지셔닝, 시장 예측(2019-2023년)

AI (Artificial Intelligence) in Retail: Segment Analysis, Vendor Positioning & Market Forecasts 2019-2023

리서치사 Juniper Research Ltd
발행일 2019년 04월 상품 코드 372628
페이지 정보 영문
가격
£ 1,990 ₩ 3,144,000 Web Access - Deep Dive Strategy & Competition (Enterprise Wide License)
£ 1,990 ₩ 3,144,000 Web Access - Executive Summary & Core Findings (Enterprise Wide License)
£ 2,250 ₩ 3,555,000 Web Access - Deep Dive Data & Forecasting (Enterprise Wide License)
£ 4,090 ₩ 6,463,000 Web Access - Full Research Suite (Enterprise Wide License)


세계의 소매용 AI(인공지능) 시장 : 부문별 분석, 벤더 포지셔닝, 시장 예측(2019-2023년) AI (Artificial Intelligence) in Retail: Segment Analysis, Vendor Positioning & Market Forecasts 2019-2023
발행일 : 2019년 04월 페이지 정보 : 영문

세계의 소매용 AI(인공지능) 시장에 대해 조사 분석했으며, 부문별 동향(성장 촉진요인, 전략적 기회, 제안), 지역별 분석(주요 8개 지역), 주요 기업, 산업 예측 등에 대한 체계적인 정보를 제공합니다.

전략과 경쟁(PDF)

제1장 소매용 AI : 서론

제2장 AI : 소매의 파괴

  • 소매의 파괴적 AI : 영향평가
  • 소매용 AI 부문별 분석
  • 소매용 AI 전망
  • 소매용 AI : 파괴자와 도전자

제3장 소매용 AI : 벤더 분석

  • 벤더 분석과 리더보드 소개
  • 소매용 AI의 유력자
  • 벤더 개요
    • Adobe
    • Amazon
    • Cortexica
    • Evolv
    • Google
    • IBM
    • Intel
    • Microsoft
    • Oracle
    • Salesforce
    • Relex
    • SAP
    • Slyce
    • ToolsGroup
    • ViSenze

데이터와 예측(PDF, Excel)

제1장 소매용 AI의 서론

제2장 AI 소매 서비스 시장 예측

  • 서론
  • 조사 방법과 가정
  • ML 서비스를 이용하는 소매업체
  • 공급망의 ML 수요 예측
  • 고객 서비스 및 감정 분석에서의 ML
  • 자동 마케팅 솔루션에서의 ML
  • 소매 ML 총지출

제3장 소매 챗봇 시장 예측

  • 서론
  • 조사 방법과 가정
  • 챗봇 예측

제4장 AI 디지털 사이니지 시장 예측

  • 서론
  • 조사 방법과 가정
  • 디지털 사이니지 예측

제5장 스마트 체크아웃 시장 예측

  • 서론
  • 조사 방법과 가정
  • 스마트 체크아웃 예측
KSM 19.04.17

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Overview

Juniper's latest ‘AI in Retail’ research provides a detailed overview of how AI (Artificial Intelligence) and machine learning strategies are being harnessed by retailers to transform both back office operations and customer-facing efforts. The research analyses the regional outlook for AI in retail adoption, as well as offering analysis of key AI areas, such as demand forecasting and personalisation.

The report also examines the use of chatbots, AI-managed digital signage and smart checkout technologies in the retail environment; assessing their future viability. It also includes insightful player analysis alongside key recommendations for stakeholders in the industry to inform strategic planning.

The analysis covers key industry segments, including:

  • Demand Forecasting
  • Sentiment Analytics and Customer Service
  • Automated Marketing
  • Retail Chatbots

This research suite includes:

  • Deep Dive Strategy & Competition (PDF)
  • 5-Year Deep Dive Data & Forecasting (PDF & Excel)
  • Executive Summary & Core Findings (PDF)
  • 12 months' access to harvest online data platform

Key Features

  • Sector Dynamics: AI drivers, strategic opportunities and recommendations for:
    • Personalisation
    • Demand Forecasting
    • Customer Analytics & Marketing
    • Payment Provider Analytics
    • Retail Chatbots
  • Regional Analysis: Detailed analysis of Juniper's 8 key regions; assessing the current investment landscape, challenges to future investment and a future outlook.
  • Interviews: Leading AI in Retail vendors across the value chain interviewed, including:
    • Cortexica Vision Systems
    • Nosto
    • ViSenze
  • Juniper Leaderboard: Key player capability and capacity assessment for 15 emerging AI in Retail service providers.
  • AI in Retail Disruptors & Challengers Quadrant: Analyses 15 of the emerging and innovative technology companies with the potential to disrupt key retail markets.
  • Benchmark Industry Forecasts: Market segment forecasts for key AI in Retail verticals, including:
    • Demand Forecasting
    • Sentiment Analytics and Customer Service
    • Automated Marketing
    • Retail Chatbots
    • AI Digital Signage
    • Smart Checkouts

Key Questions

  • 1. At what pace are retailers expected to adopt machine learning services?
  • 2. What are the most viable use cases for AI deployment in the retail industry?
  • 3. Who are the key disruptors in this space, and what strategies are vendors employing?
  • 4. What are the key trends, drivers and challenges acting on the AI industry?
  • 5. How will the customer experience change with AI deployment in retail?

Companies Referenced

  • Interviewed: Cortexica Vision Systems, Nosto, ViSenze, ZestFinance.
  • Profiled: Adobe, Amazon, Cortexica Vision Systems, Evolv, Google, IBM, Intel, Microsoft, Oracle, Relex, Salesforce, SAP, Slyce, ToolsGroup, ViSenze.
  • Case Studied: Granify, JP Morgan Chase, Symphony RetailAI.
  • Included in Disruptors & Challengers Quadrant: AntVoice, Cognitive Operational Systems, Daisy Intelligence, Deepomatic, Emarsys, Focal Systems, Granify, Kore.ai, Nosto, Plexure, Satisfi Labs, Seez, Synerise, Syte.ai, Thread.
  • Mentioned: 3PM Solutions, 3Sverige, 44Pixel, A.S. Adventure, AAEON, AB InBev, Accenture, Affirm, AiSensum, Al Tayer, Aldo, Alessi, Amway, Analyteq, AO.com, Apple, Argility, Ashley Furniture, Aston Martin, Avenue Supermarts, Axis, Best Buy, Blispay, BlueStone, Booths, BQ, Bread, Brooks Brothers, California Design Den, Caratlane, Carrefour, Celebrity Cruises, Centrica, Chalhoub Group, Charlotte Tilbury, Charming Charlie, CI&T, Cisco, Clicksco, Cognira, Columbus Consulting, CommerceHub, Conversionista, ConversionXL, COOP, Coop Denmark, Cosabella, Costa, Craveable Brands, CSAV Norasia, DataSine, Dell, Deloitte, Demandtex, Direct Investment, Ditto Labs, Dixons Carphone, Eagle Retailing, eBags, eBay, Ellos Group, Energie Direct, Essent, Euroflorist, Express, Facebook, Farfetch, Fashion Island, Fennobiz, Fit Analytics, Flipkart, Fluid AI, FMCG Retail, Focal Systems, Forecast Solutions, Fullbeauty.com, Future Group, Galleria RTS, Gant, Gap, Glowforge, Goodrich, Goxip, GPA, Graymatter, GreenSky, Grokstyle, GS Shop, GSK, H&M, Hamleys, Hammerson, HipVan, Home Depot, Honeywell, Huawei, Ikea, IMS Evolve, Inbenta, Innogy, Interpark, Irvine Spectrum Centre, ITP Group, JCPenney, John Lewis, Kabbage, Kia, Kingston SCL, Klarna, Kolonial.no, L'Oréal, La Redoute, Landal Greenparks, Lenox, LG, Lululemon Athletica, Lush, Macy's, Maison du Monde, Mall of America, Malong Technologies, Manthan, Marks & Spencer, Mastercard, Maui Jim, MediaCorp, MNC Media, Mobiqa, Morrisons, Myntra, Naver, Neal Analytics, NeoMedia, Neudesic, Nike, Nixor, North Face, O2, Ocado, One Stop, Online Dialogue, Orange, OSP Retail, Pacific Internet, Paytm, Pitney Bowes, Plantasjen, Public, Publicis.Sapient, PWC, Pythian, Quann, Rackspace, Rakuten, Reebonz, Reliance Retail, Renner, River Island, Rossmann, RS, Samsung, Sensitel, Sentient Technologies, Sephora, Singtel, Solteq, Specsavers, Square, Strategix CFT, T. J. Maxx, Target, TelesensKSCL, Tesco, Ticketmaster, Tinyclues, T Mobile, Tommy Hilfiger, Travis Perkins, Trax, Tumi, Under Armour, UNIQLO, United Colours of Benetton, Urban Outfitters, Vente-Exclusive, Verizon, Very, Virgin, Visa, Vivo, Vue.ai, Waitrose, Walmart, Wellio, WHSmith, Wipro, Woolworths, WPP, Yosh.AI, Zabka, Zalando, Zalora.

Data & Interactive Forecast

Juniper's latest ‘AI in Retail’ forecast suite includes:

  • Regional splits for 8 key global regions, as well as country level data splits for:
    • Canada
    • China
    • Denmark
    • Germany
    • Japan
    • Norway
    • Portugal
    • Spain
    • Sweden
    • UK
    • US
  • AI retail services forecast, including users and revenues, across the following segments:
    • Demand Forecasting
    • Sentiment Analytics and Customer Service
    • Automated Marketing
  • Retail chatbot forecast, including the number of successful interactions and revenues from chatbot-based purchases.
  • AI digital signage forecasts, including the number of digital signs managed by AI and the service revenues generated.
  • Smart checkouts forecast, including the number of smart checkouts deployed and the resulting transaction volume and value.
  • Access to the full set of forecast data of 90 tables and over 11,880 datapoints.
  • Interactive Excel Scenario tool allowing users the ability to manipulate Juniper's data for 12 different metrics.

Juniper Research's highly granular interactive Excels enable clients to manipulate Juniper's forecast data and charts to test their own assumptions using the Interactive Scenario Tool, and compare select markets side by side in customised charts and tables. IFxls greatly increase clients' ability to both understand a particular market and to integrate their own views into the model.

Table of Contents

Deep Dive Strategy & Competition

1. AI in Retail: Introduction

  • 1.1 Introduction
    • Figure 1.1: AI Skills in Retail
    • Figure 1.2: Types of AI
  • 1.2 Investment Landscape
    • Table 1.3: Selected AI in Retail Investments, 2018-19
  • 1.3 Retail Industry/Start-up Activity by Region
    • 1.3.1 North America
      • i. Current Retail Market
        • Figure 1.4: Total US Retail Sales ($bn), 2010-2018
      • ii. Investment/Development Activity
    • 1.3.2 Latin America
      • i. Current Retail Market
      • ii. Juniper's View: Future Prospects
        • Figure 1.5: Annual GDP Growth (%) Selected Latin American Countries, 2011-2017
      • iii. Investment/Development Activity
    • 1.3.3 West Europe
      • i. Current Retail Market
        • Figure 1.6: UK Retail Sales ($bn), 2011-2018
      • ii. Investment/Development Activity
    • 1.3.4 Central & East Europe
      • i. Current Retail Market
        • Figure 1.7: Annual GDP Growth (%) Selected Central & East European Countries, 2011-2017
      • ii. Investment/Development Activity
      • iii. Juniper's View: Future Prospects
    • 1.3.5 Far East & China
      • i. Current Retail Market
        • Figure 1.8: Annual GDP Growth (%), Selected Countries, 2011-2017
      • ii. Investment/Development Activity
      • iii. Juniper's View: Future Prospects
    • 1.3.6 Indian Subcontinent
      • i. Current Retail Market
        • Figure 1.9: GDP per Capita ($), Selected Countries 2011-2017
      • ii. Investment/Development Activity
      • iii. Juniper's View: Future Prospects
    • 1.3.7 Rest of Asia Pacific
      • i. Current Retail Market
        • Figure 1.10: Total Retail Sales ($m), Singapore, 2010-2017
      • ii. Investment/Development Activity
      • iii. Juniper's View: Future Prospects
    • 1.3.8 Africa & Middle East
      • i. Current Retail Market
        • Figure 1.11: GDP per Capita ($), Selected Countries 2011-2017
      • ii. Investment/Development Activity
      • iii. Juniper's View: Future Prospects

2. AI: Disruption in Retail

  • 2.1 Disruptive AI in Retail - Impact Assessment ..
    • 2.1.1 Summary
      • Table 2.1: AI in Retail Impact Assessment
      • Table 2.2: AI in Retail Impact Assessment Heatmap Key
    • 2.1.2 AI in Retail Impact Assessment Methodology
      • Table 2.3: AI in Retail Impact Assessment Methodology
  • 2.2 AI in Retail Segment Analysis
    • 2.2.1 Personalisation
      • Case Study: Granify
      • i. Visual Search
        • Figure 2.4: ViSenze Visual Search
      • ii. Challenges to Approach
      • iii. Future Outlook
    • 2.2.2 Demand Forecasting
      • Figure 2.5: Elements of Demand Forecasting
      • i. Challenges to Approach
      • ii. Future Outlook
        • Case Study: Symphony RetailAI
    • 2.2.3 Customer Analytics & Marketing
      • i. Challenges to Approach
      • ii. Future Outlook
    • 2.2.4 Payment Provider Analytics
      • i. Challenges to Approach
      • ii. Future Outlook
    • 2.2.5 Chatbots
      • i. Challenges to Approach
      • ii. Future Outlook
    • 2.2.6 The POS Finance Opportunity
      • Case Study: My Chase Plan
      • i. Challenges to Approach
      • ii. Future Outlook
    • 2.2.7 Voice Assistants
      • i. Challenges to Approach
      • ii. Future Outlook
  • 2.3 AI Outlook in Retail
    • Figure 2.6: Juniper Phased Evolution: AI & Connected Retail
    • i. Future Developments
  • 2.4 AI in Retail: Disruptors & Challengers Quadrant
    • 2.4.1 Introduction
      • Figure 2.7: Juniper Disruptors & Challengers Quadrant - AI in Retail
    • 2.4.2 Landscape Analysis
      • i. Overview
      • ii. Disruptors
      • iii. Catalysts
      • iv. Embryonic Stakeholders

3. AI in Retail: Vendor Analysis

  • 3.1 Vendor Analysis & Leaderboard Introduction
    • 3.1.1 Stakeholder Assessment Criteria
      • Table 3.1: AI in Retail Player Capability Criteria
      • Figure 3.2: AI in Retail Stakeholder Leaderboard
      • Table 3.3 AI in Retail Leaderboard Scoring
    • 3.1.2 Vendor Groupings
      • i. Established Leaders
      • ii. Leading Challengers
      • iii. Disruptors & Emulators
    • 3.1.3 Limitations & Interpretation
  • 3.2 AI in Retail Movers & Shakers
  • 3.3 Vendor Profiles
    • 3.3.1 Adobe
      • i. Corporate
        • Table 3.4: Adobe Financial Snapshot ($bn) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.3.2 Amazon
      • i. Corporate
        • Table 3.5: Amazon: Key Financial Data ($bn) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.3.3 Cortexica
      • i.Corporate
        • Table 3.6: Cortexica Funding Rounds
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.3.4 Evolv
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.3.5 Google
      • i. Corporate
        • Table 3.7: Alphabet Financial Snapshot ($bn) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.3.6 IBM
      • i. Corporate
        • Table 3.8: IBM Financial Snapshot ($m) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.3.7 Intel
      • i. Corporate
        • Table 3.9: Intel Financial Snapshot ($bn) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.3.8 Microsoft
      • i. Corporate
        • Table 3.10: Microsoft Financial Snapshot ($bn) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.3.9 Oracle
      • i. Corporate
        • Table 3.11: Oracle Financial Snapshot ($m) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.3.10 Salesforce
      • i. Corporate
        • Table 3.12: Salesforce.com Financial Snapshot ($bn) 2016-2019
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.3.11 Relex
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.3.12 SAP
      • i. Corporate
        • Table 3.13: SAP Financial Snapshot ($bn) 2016-2018
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.3.13 Slyce
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.3.14 ToolsGroup
      • i. Corporate
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities
    • 3.3.15 ViSenze
      • i. Corporate
        • Table 3.14: ViSenze Funding Rounds
      • ii. Geographic Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High Level View of Offerings
      • v. Juniper's View: Key Strengths & Strategic Development Opportunities

Deep Dive Data & Forecasting

1. Introduction to AI in Retail

  • 1.1 Introduction
    • Figure 1.1: AI Skills in Retail

2. AI Retail Services Market Forecasts

  • 2.1 Introduction
  • 2.2 Methodology & Assumptions
    • Figure 2.1: AI Retail Services Forecast Methodology
  • 2.3 Retailers Using Machine Learning Services
    • Figure & Table 2.2: Total Connected Retailers Accessing Machine Learning Services (m), Split by 8 Key Regions, 2018-2023
  • 2.4 Machine Learning in Supply Chain Demand Forecasting
    • Figure & Table 2.3: Total Retailer Spend on Machine Learning for Demand Forecasting ($m), Split by 8 Key Regions 2018-2023
  • 2.5 Machine Learning in Customer Service & Sentiment Analytics
    • Figure & Table 2.4: Total Retailer Spend on Machine Learning Assisted Customer Service & Sentiment Analytics ($m), Split by 8 Key Regions 2018-2023
  • 2.6 Machine Learning in Automated Marketing Solutions
    • Figure & Table 2.5: Total Spend by Retailers Using AI-based Automated Marketing Services ($m), Split by 8 Key Regions, 2018-2023
  • 2.7 Total Retail Machine Learning Spend
    • Figure & Table 2.6: Total Retail Machine Learning Spend ($m), Split by 8 Key Regions 2018-2023

3. Retail Chatbots Market Forecasts

  • 3.1 Introduction
  • 3.2 Assumptions & Methodology
    • Figure 3.1: Methodology for Messaging Application Chatbots
    • Figure 3.2: Methodology for Discrete Application Chatbots
    • Figure 3.3: Methodology for Web-based Chatbots
  • 3.3 Chatbot Forecasts
    • 3.3.1 Total Number of Successful Retail Chatbot Interactions
      • Figure & Table 3.4: Total Number of Successful Retail Chatbot Interactions (m) Split by 8 Key Regions 2018-2023
    • 3.3.2 Total Revenues from Retail Chatbots
      • Figure & Table 3.5: Total Revenues from Retail Chatbots per Annum ($m) Split by 8 Key Regions 2018-2023

4. AI Digital Signage Market Forecasts

  • 4.1 Introduction
  • 4.2 Methodology & Assumptions
    • Figure 4.1: Digital Signage Forecast Methodology
  • 4.3 Digital Signage Forecasts
    • 4.3.1 Number of Installed Digital Signs
      • Figure & Table 4.2: Global Number of Installed Digital Signs, ESL (Electronic Shelf Labels) & Large Display (m) Split by 8 Key Regions 2018-2023
    • 4.3.2 Number of Connected Digital Signs Controlled by AI Systems
      • Figure & Table 4.3: Number of Connected Digital Signs Controlled by AI Systems (m) Split by 8 Key Regions 2018-2023

5. Smart Checkouts Market Forecasts

  • 5.1 Introduction
  • 5.2 Methodology & Assumptions
    • Figure 5.1: Smart Checkouts Forecast Methodology
  • 5.3 Smart Checkouts Forecasts
    • 5.3.1 Retail Outlets Adopting Smart Checkout Technologies
      • Figure & Table 5.2: Number of Retail Outlets Adopting Smart Checkout Technologies (,000s) Split by 8 Key Regions 2018-2023
    • 5.3.2 Annual Transaction Value Processed by Smart Checkout Technologies
      • Figure & Table 5.3: Annual Transaction Value Processed by Smart Checkout Technologies ($m) Split by 8 Key Regions 2018-2023
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