HOME Top Market Reports Artificial Intelligence in Retail Market by Type (Online, Offline), Technology (Machine Learning and Deep Learning, NLP), Solution, Service (Professional, Managed), Deployment Mode (Cloud, On-Premises), Application, Region - Global Forecast to 2022

Artificial Intelligence in Retail Market by Type (Online, Offline), Technology (Machine Learning and Deep Learning, NLP), Solution, Service (Professional, Managed), Deployment Mode (Cloud, On-Premises), Application, Region - Global Forecast to 2022

By: marketsandmarkets.com
Publishing Date: October 2017
Report Code: TC 5669

 

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The global AI in retail market size is expected to grow from USD 736.1 Million in 2016 to USD 5,034.0 Million by 2022, at a Compound Annual Growth Rate (CAGR) of 38.3%. Increasing necessity for superior surveillance and monitoring at a physical store, growing awareness and application of AI in the retail industry, enhanced user-experience, improved productivity, Return on Investment (RoI), mainlining inventory accuracy, and supply chain optimization are some of the key factors fueling the growth of this market. The base year considered for this report is 2016, and the market forecast period is 2017–2022.

Objectives of the Study

The main objective of the report is to define, describe, and forecast the global Artificial Intelligence in retail market on the basis of types (online and offline), technologies, solutions, services, deployment modes, applications, and regions. The report provides detailed information regarding the major factors influencing the growth of the AI in retail market (drivers, restraints, opportunities, and industry-specific challenges). The report aims to strategically analyze micromarkets with respect to individual growth trends, future prospects, and contributions to the total market. The report attempts to forecast the market size with respect to 5 main regions, namely, North America, Europe, Asia Pacific (APAC), Middle East and Africa (MEA), and Latin America. The report strategically profiles key players and comprehensively analyzes their core competencies. It also tracks and analyzes competitive developments, such as partnerships, collaborations, and agreements; mergers and acquisitions; new product launches and product developments; and Research and Development (R&D) activities in the market.

Research Methodology

The research methodology used to estimate and forecast the AI in retail market begins with capturing data on key vendor revenues through secondary research, which includes directories and databases (D&B Hoovers, Bloomberg Businessweek, and Factiva). The vendor offerings have also been taken into consideration to determine the market segmentation. The bottom-up procedure was employed to arrive at the overall market size of the global Artificial Intelligence in retail market that was derived from the revenue of the key players in the market. After arriving at the overall market size, the total market was split into several segments and subsegments, which were then verified through primary research by conducting extensive interviews with key people, such as Chief Executive Officers (CEOs), Vice Presidents (VPs), directors, and executives. The data triangulation and market breakdown procedures were employed to complete the overall market engineering process and arrive at the exact statistics for all segments and subsegments. The breakdown of profiles of primary participants is depicted in the figure below:

Artificial Intelligence in Retail Market

To know about the assumptions considered for the study, download the pdf brochure

The Artificial Intelligence in retail ecosystem comprises vendors such as IBM (US), Microsoft (US), Amazon Web Services (US), Oracle (US), SAP (Germany), Intel (US), NVIDIA (US), Google (US), Sentient technologies (US), Salesforce (US), and ViSenze (Singapore). Other stakeholders of the AI in retail market include vendors, research organizations, network and system integrators, AI in retail managed service providers, Business Intelligence (BI) solution providers, marketing analytics executives, third-party providers, and technology providers.

IoT Analytics Key Target Audience:

  • AI in retail solutions, platforms, and service providers
  • Research organizations and consulting companies
  • Information security directors/managers
  • Government organizations
  • Consultants/advisory firms
  • Managed service providers
  • AI system providers
  • Venture capitalists, private equity firms, and startup companies
  • AI in retail application builders

The study answers several questions for the stakeholders, primarily which market segments to focus on in the next 2–5 years for prioritizing efforts and investments.”

Scope of the Report

The research report categorizes the AI in retail market to forecast the revenues and analyze trends in each of the following subsegments:

By Type

  • Online
  • Offline

By Technology

  • Machine Learning and Deep Learning
  • Natural Language Processing
  • Others (Analytics and Process Automation)

By Solution

  • Product Recommendation and Planning
  • Customer Relationship Management
  • Visual Search
  • Virtual Assistant
  • Price Optimization 
  • Payment Services management
  • Supply chain management and Demand Planning
  • Others (Website and Content Optimization, Space Planning, Fraud Detection, and Franchise Management)

By Service

  • Professional Services
  • Managed Services

By Deployment Model

  • Cloud
  • On-Premises

By Application

  • Predictive Merchandising
  • Programmatic Advertising
  • Market Forecasting
  • In-Store Visual Monitoring and Surveillance
  • Location-Based Marketing
  • Other (Real-Time Pricing and Incentives, and Real-Time Product Targeting)

By Region

  • North America
  • Europe
  • APAC
  • Latin America
  • MEA

Available Customizations

With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:

Product Analysis

  • Product matrix gives a detailed comparison of the product portfolio of each company

Geographic Analysis

  • Further breakdown of the North American AI in retail market
  • Further breakdown of the European market
  • Further breakdown of the APAC market
  • Further breakdown of the Latin American market
  • Further breakdown of the MEA market

Company Information

  • Detailed analysis and profiling of additional market players upto 5.

Table of Contents

1 Introduction (Page No. - 15)
    1.1 Objectives of the Study
    1.2 Market Definition
    1.3 Market Scope
           1.3.1 Years Considered for the Study
           1.3.2 Currency
    1.4 Stakeholders

2 Research Methodology (Page No. - 19)
    2.1 Research Data
           2.1.1 Secondary Data
           2.1.2 Primary Data
                    2.1.2.1 Key Industry Insights
    2.2 Market Size Estimation
           2.2.1 Bottom-Up Approach
           2.2.2 Top-Down Approach
    2.3 Research Assumptions
    2.4 Limitations

3 Executive Summary (Page No. - 25)

4 Premium Insights (Page No. - 28)
    4.1 Attractive Market Opportunities
    4.2 Artificial Intelligence in Retail Market: Technologies
    4.3 Lifecycle Analysis, By Region, 2017–2022

5 Market Overview and Industry Trends (Page No. - 30)
    5.1 Introduction
    5.2 Market Dynamics
           5.2.1 Drivers
                    5.2.1.1 Increasing Necessity for Superior Surveillance and Monitoring at Physically Present Retail Stores
                    5.2.1.2 Growing Awareness and Application of AI in the Retail Industry
                    5.2.1.3 to Enhance End-User Experience, Improve Productivity, and Generate More Revenue
                    5.2.1.4 to Maintain Inventory Accuracy and Supply Chain Optimization
           5.2.2 Restraints
                    5.2.2.1 Incompatibility Concerns
           5.2.3 Opportunities
                    5.2.3.1 Increase in AI-Based Data Analysis Application
                    5.2.3.2 Growing Number of Smartphones
                    5.2.3.3 Increase in Adoption of Cloud-Based Technology Solutions
           5.2.4 Challenges
                    5.2.4.1 Issues With Diverse Development Framework, Models, and Mechanism in AI
                    5.2.4.2 Concerns Over Privacy and Identity of Individuals
                    5.2.4.3 Lack of Skilled Staff
    5.3 Industry Trends
           5.3.1 Introduction
           5.3.2 Use Cases
                    5.3.2.1 Scenario 1
                    5.3.2.2 Scenario 2
                    5.3.2.3 Scenario 3
                    5.3.2.4 Scenario 4
                    5.3.2.5 Scenario 5
                    5.3.2.6 Scenario 6
                    5.3.2.7 Scenario 7
                    5.3.2.8 Scenario 8
                    5.3.2.9 Scenario 9
                    5.3.2.10 Scenario 10
                    5.3.2.11 Scenario 11
                    5.3.2.12 Scenario 12
    5.4 Regulatory Implications
           5.4.1 Introduction
           5.4.2 Sarbanes-Oxley Act of 2002
           5.4.3 General Data Protection Regulation
           5.4.4 Basel

6 AI in Retail Market Analysis, By Type (Page No. - 40)
    6.1 Introduction
    6.2 Online Retail
    6.3 Offline Retail

7 Artificial Intelligence in Retail Market Analysis, By Technology (Page No. - 44)
    7.1 Introduction
    7.2 Machine Learning and Deep Learning
           7.2.1 Facial Recognition
           7.2.2 Emotion Detection
    7.3 Natural Language Processing
    7.4 Others
           7.4.1 Analytics
           7.4.2 Process Automation

8 AI in Retail Market Analysis, By Solution (Page No. - 50)
    8.1 Introduction
    8.2 Product Recommendation and Planning
    8.3 Customer Relationship Management
    8.4 Visual Search
    8.5 Virtual Assistant
    8.6 Price Optimization
    8.7 Payment Services Management
    8.8 Supply Chain Management and Demand Planning
    8.9 Others

9 Artificial Intelligence in Retail Market Analysis, By Service (Page No. - 60)
    9.1 Introduction
    9.2 Professional Services
    9.3 Managed Services

10 AI in Retail Market Analysis, By Deployment Mode (Page No. - 64)
     10.1 Introduction
     10.2 Cloud
     10.3 On-Premises

11 Artificial Intelligence in Retail Market Analysis, By Application (Page No. - 68)
     11.1 Introduction
     11.2 Predictive Merchandising
     11.3 Programmatic Advertising
     11.4 Market Forecasting
     11.5 In-Store Visual Monitoring and Surveillance
     11.6 Location-Based Marketing
     11.7 Others
             11.7.1 Real-Time Pricing and Incentives
             11.7.2 Real-Time Product Targeting

12 Geographic Analysis (Page No. - 75)
     12.1 Introduction
     12.2 North America
             12.2.1 North America, By Type
             12.2.2 North America, By Technology
             12.2.3 North America, By Solution
             12.2.4 North America, By Service
             12.2.5 North America, By Deployment Mode
             12.2.6 North America, By Application
     12.3 Europe
             12.3.1 Europe, By Type
             12.3.2 Europe, By Technology
             12.3.3 Europe, By Solution
             12.3.4 Europe, By Service
             12.3.5 Europe, By Deployment Mode
             12.3.6 Europe, By Application
     12.4 Asia Pacific
             12.4.1 Asia Pacific, By Type
             12.4.2 Asia Pacific, By Technology
             12.4.3 Asia Pacific, By Solution
             12.4.4 Asia Pacific, By Service
             12.4.5 Asia Pacific, By Deployment Mode
             12.4.6 Asia Pacific, By Application
     12.5 Latin America
             12.5.1 Latin America, By Type
             12.5.2 Latin America, By Technology
             12.5.3 Latin America, By Solution
             12.5.4 Latin America, By Service
             12.5.5 Latin America, By Deployment Mode
             12.5.6 Latin America, By Application
     12.6 Middle East and Africa
             12.6.1 Middle East and Africa, By Type
             12.6.2 Middle East and Africa, By Technology
             12.6.3 Middle East and Africa, By Solution
             12.6.4 Middle East and Africa, By Service
             12.6.5 Middle East and Africa, By Deployment Mode
             12.6.6 Middle East and Africa, By Application

13 Company Profiles (Page No. - 96)
     13.1 IBM
(Overview, Strength of Product Portfolio, Business Strategy Excellence, and Recent Developments)*
     13.2 Microsoft
     13.3 Nvidia
     13.4 Amazon Web Services
     13.5 Oracle
     13.6 SAP
     13.7 Intel
     13.8 Google
     13.9 Sentient Technologies
     13.10 Salesforce
     13.11 Visenze

*Details on Overview, Strength of Product Portfolio, Business Strategy Excellence, and Recent Developments Might Not Be Captured in Case of Unlisted Companies.

14 Appendix (Page No. - 129)
     14.1 Industry Experts
     14.2 Discussion Guide
     14.3 Knowledge Store: Marketsandmarkets’ Subscription Portal
     14.4 Introducing RT: Real-Time Market Intelligence
     14.5 Related Reports
     14.6 Author Details


List of Tables (61 Tables)

Table 1 Currency Exchange Rate
Table 2 Artificial Intelligence in Retail Market Size, By Type, 2015–2022 (USD Million)
Table 3 Online: AI in Retail Market Size, By Region, 2015–2022 (USD Million)
Table 4 Offline: Market Size, By Region, 2015–2022 (USD Million)
Table 5 Artificial Intelligence in Retail Market Size, By Technology, 2015–2022 (USD Million)
Table 6 Machine Learning and Deep Learning: AI in Retail Market Size, By Region, 2015–2022 (USD Million)
Table 7 Natural Language Processing: Market Size, By Region, 2015–2022 (USD Million)
Table 8 Others: Market Size, By Region, 2015–2022 (USD Million)
Table 9 Artificial Intelligence in Retail Market Size, By Solution, 2015–2022 (USD Million)
Table 10 Product Recommendation and Planning: Market Size, By Region, 2015–2022 (USD Million)
Table 11 Customer Relationship Management: Market Size, By Region, 2015–2022 (USD Million)
Table 12 Visual Search: Market Size, By Region, 2015–2022 (USD Million)
Table 13 Virtual Assistant: Market Size, By Region, 2015–2022 (USD Million)
Table 14 Price Optimization: Market Size, By Region, 2015–2022 (USD Million)
Table 15 Payment Services Management: Market Size, By Region, 2015–2022 (USD Million)
Table 16 Supply Chain Management and Demand Planning: Market Size, By Region, 2015–2022 (USD Million)
Table 17 Others: AI in Retail Market Size, By Region, 2015–2022 (USD Million)
Table 18 Artificial Intelligence in Retail Market Size, By Service, 2015–2022 (USD Million)
Table 19 Professional Services: Market Size, By Region, 2015–2022 (USD Million)
Table 20 Managed Services: Market Size, By Region, 2015–2022 (USD Million)
Table 21 Artificial Intelligence in Retail Market Size, By Deployment Mode, 2015–2022 (USD Million)
Table 22 Cloud: Market Size, By Region, 2015–2022 (USD Million)
Table 23 On-Premises: AI in Retail Market Size, By Region, 2015–2022 (USD Million)
Table 24 Artificial Intelligence in Retail Market Size, By Application, 2015–2022 (USD Million)
Table 25 Predictive Merchandising: Market Size, By Region, 2015–2022 (USD Million)
Table 26 Programmatic Advertising: Market Size, By Region, 2015–2022 (USD Million)
Table 27 Market Forecasting: Market Size, By Region, 2015–2022 (USD Million)
Table 28 In-Store Visual Monitoring and Surveillance: Market Size, By Region, 2015–2022 (USD Million)
Table 29 Location-Based Marketing: Market Size, By Region, 2015–2022 (USD Million)
Table 30 Others: AI in retail Market Size, By Region, 2015–2022 (USD Million)
Table 31 Artificial Intelligence in Retail Market Size, By Region, 2015–2022 (USD Million)
Table 32 North America: AI in Retail Market Size, By Type, 2015–2022 (USD Million)
Table 33 North America: Market Size, By Technology, 2015–2022 (USD Million)
Table 34 North America: Market Size, By Solution, 2015–2022 (USD Million)
Table 35 North America: Market Size, By Service, 2015–2022 (USD Million)
Table 36 North America: Market Size, By Deployment Mode, 2015–2022 (USD Million)
Table 37 North America: Artificial Intelligence in Retail Market Size, By Application, 2015–2022 (USD Million)
Table 38 Europe: AI in Retail Market Size, By Type, 2015–2022 (USD Million)
Table 39 Europe: Market Size, By Technology, 2015–2022 (USD Million)
Table 40 Europe: Market Size, By Solution, 2015–2022 (USD Million)
Table 41 Europe: Market Size, By Service, 2015–2022 (USD Million)
Table 42 Europe: Market Size, By Deployment Mode, 2015–2022 (USD Million)
Table 43 Europe: Artificial Intelligence in Retail Market Size, By Application, 2015–2022 (USD Million)
Table 44 Asia Pacific: AI in Retail Market Size, By Type, 2015–2022 (USD Million)
Table 45 Asia Pacific: Market Size, By Technology, 2015–2022 (USD Million)
Table 46 Asia Pacific: Market Size, By Solution, 2015–2022 (USD Million)
Table 47 Asia Pacific: Market Size, By Service, 2015–2022 (USD Million)
Table 48 Asia Pacific: Market Size, By Deployment Mode, 2015–2022 (USD Million)
Table 49 Asia Pacific: Artificial Intelligence in Retail Market Size, By Application, 2015–2022 (USD Million)
Table 50 Latin America: AI in Retail Market Size, By Type, 2015–2022 (USD Million)
Table 51 Latin America: Market Size, By Technology, 2015–2022 (USD Million)
Table 52 Latin America: Market Size, By Solution, 2015–2022 (USD Million)
Table 53 Latin America: etail Market Size, By Service, 2015–2022 (USD Million)
Table 54 Latin America: Market Size, By Deployment Mode, 2015–2022 (USD Million)
Table 55 Latin America: Artificial Intelligence in Retail Market Size, By Application, 2015–2022 (USD Million)
Table 56 Middle East and Africa: AI in Retail Market Size, By Type, 2015–2022 (USD Million)
Table 57 Middle East and Africa: Market Size, By Technology, 2015–2022 (USD Million)
Table 58 Middle East and Africa: Market Size, By Solution, 2015–2022 (USD Million)
Table 59 Middle East and Africa: Market Size, By Service, 2015–2022 (USD Million)
Table 60 Middle East and Africa: Market Size, By Deployment Mode, 2015–2022 (USD Million)
Table 61 Middle East and Africa: Artificial Intelligence in Retail Market Size, By Application, 2015–2022 (USD Million)

List of Figures (32 Figures)

Figure 1 Markets Covered
Figure 2 Artificial Intelligence in Retail Market: Research Design
Figure 3 Breakdown of Primary Interviews: By Company, Designation, and Region
Figure 4 AI in Retail Market Size Estimation Methodology: Bottom-Up Approach
Figure 5 Market Size Estimation Methodology: Top-Down Approach
Figure 6 AI in Retail Market: Data Triangulation
Figure 7 Global Artificial Intelligence in Retail Market Snapshot (2017–2022)
Figure 8 Market Snapshot, By Solution and Service
Figure 9 AI in Retail Market Snapshot, By Region
Figure 10 Demand for Personalized Product Recommendation is One of the Major Factors Driving the Overall Growth of the AI in Retail Market During the Forecast Period
Figure 11 Natural Language Processing Technology is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 12 Asia Pacific is Expected to Exhibit the Highest Growth Potential During the Forecast Period
Figure 13 North America, and Product Recommendation and Planning are Expected to Have the Highest Market Shares During the Forecast Period
Figure 14 Artificial Intelligence in Retail Market: Drivers, Restraints, Opportunities, and Challenges
Figure 15 Offline Type is Expected to Grow With A Higher Growth Rate in the AI in Retail Market During the Forecast Period
Figure 16 Natural Language Processing Segment is Expected to Be the Fastest Growing Technology in the Artificial Intelligence in Retail Market
Figure 17 Visual Search Segment is Expected to Be the Fastest Growing Solution During the Forecast Period
Figure 18 Managed Services Segment is Expected to Be the Faster Growing Segment During the Forecast Period
Figure 19 On-Premises Deployment Mode is Expected to Have the Higher Growth Rate in the Artificial Intelligence in Retail Market During the Forecast Period
Figure 20 In-Store Visual Monitoring and Surveillance Segment is Expected to Be the Fastest Growing Application During the Forecast Period
Figure 21 Asia Pacific is Expected to Be the Most Attractive Market for Retailers During the Forecast Period
Figure 22 North America: Artificial Intelligence in Retail Market Snapshot
Figure 23 Asia Pacific: Market Snapshot
Figure 24 IBM: Company Snapshot
Figure 25 Microsoft: Company Snapshot
Figure 26 Nvidia: Company Snapshot
Figure 27 Amazon Web Services: Company Snapshot
Figure 28 Oracle: Company Snapshot
Figure 29 SAP: Company Snapshot
Figure 30 Intel: Company Snapshot
Figure 31 Google: Company Snapshot
Figure 32 Salesforce: Company Snapshot

The Artificial Intelligence (AI) in retail market is expected to grow from USD 993.6 Million in 2017 to USD 5,034.0 Million by 2022, at a Compound Annual Growth Rate (CAGR) of 38.3%. Factors such as increasing necessity for surveillance and monitoring at a physical store, growing awareness, and application of AI, enhanced user-experience, improved productivity, Return on Investment (RoI), maintaining inventory accuracy, and supply chain optimization are driving the global AI in retail market.

The report provides detailed insights into the global AI in retail market, which is segmented by type, technology, solution, service, deployment mode, application, and region. In the types, the online (eCommerce) retail market will have the largest market share during the forecast period. The online retailing includes buying and selling of FMCG, CPG, apparels, electronics goods, and other forms of life essentials. It excludes entertainment and travel services offered online. Contrary to the brick-and-mortar stores, customers no longer have to stand in long queues to buy their preferred goods. They can purchase them easily through mobile applications and websites, sitting comfortably in their homes or offices. The AI-based solution are majorly adopted by the online retailers to target the customer, who want to shop from the comfort of their homes.

Among solutions, product recommendation and planning is expected to hold the largest market share and is expected to continue its dominating position during the forecast period. Product recommendation is a very powerful aspect of the overall shopping cycle for any shopper. eRetailers are using AI to give a personalized experience to their customers and give recommendations on products they would like to purchase by showing relevant products. Moreover, machine learning and deep learning technology will remain the most significant technology contributing highest revenue compared to other technologies.

Whereas, the in-store visual monitoring and surveillance application is expected to have the highest growth rate during the forecast period. AI for video surveillance analyze the images in order to recognize humans, vehicles, or objects by using computer software programs. This can help in curbing the issue of shoplifting which is one of the major reasons to incur financial loss in stores. The cloud deployment model is expected to exhibit a higher market share, due to the rising demand for 24*7 availability of accessible information and low-cost maintenance services.

Artificial Intelligence in Retail Market

The report covers all the major aspects of the AI in retail market and provides an in-depth analysis for major countries across the regions of North America, Europe, Asia Pacific (APAC), Latin America, and the Middle East and Africa (MEA). North America, owing to the early adoption of new and emerging technologies and the presence of the major industry players, is expected to dominate the market in terms of market size, throughout the forecast period. The APAC region is expected to grow at the highest CAGR during the forecast period, owing to the growing adoption of AI-based solutions and services among retailers.

The issues related to diverse development framework, models, mechanisms in AI, privacy concern, and lack of skilled staff are some major challenges faced by the retail users deploying AI, which needs to be enhanced to improve the growth of the AI in retail market.

The AI in retail ecosystem comprises vendors such as IBM (US), Microsoft (US), Amazon Web Services (US), Oracle (US), SAP (Germany), Intel (US), NVIDIA (US), Google (US), Sentient Technologies (US), Salesforce (US), and ViSenze (Singapore). Other stakeholders of the AI in retail market include vendors, research organizations, network and system integrators, AI managed service providers, Business Intelligence (BI) solution providers, marketing analytics executives, third-party providers, and technology providers.

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