Global Artificial Intelligence in Retail Market Overview

Artificial Intelligence in Retail Market size is projected to reach xxxx units by 2025 from an estimated xxxx unit in 2019, growing at a CAGR of xx% globally.

Report of Artificial Intelligence in Retail Market is currently supplying a comprehensive analysis of many things which are liable for economy growth and factors which could play an important part in the increase of the marketplace in the prediction period. The record of Artificial Intelligence in Retail Industry is providing the thorough study on the grounds of market revenue discuss production and price happened. The report also provides the overview of the segmentation on the basis of area, contemplating the particulars of earnings and sales pertaining to marketplace.

An extensive analysis of this Artificial Intelligence in Retail Market is completed to recognize the many applications of the qualities of merchandise and utilization. The report involves an explanation regarding the numerous facets linked to market involving data and market increase concerning technological advancements, production and the firm's revenue. Additionally, market risk factors inventions, market setting, economy restraints, and challenges on the market have been explored within the accounts..

Scope of the Artificial Intelligence in Retail Market

The Artificial Intelligence in Retail Market Research report incorporate value chain analysis for each of the product type. Value chain analysis offers in depth information about value addition at each stage. The study includes drivers and restraints for Artificial Intelligence in Retail Market along with their impact on demand during the forecast period. The study also provides key market indicators affecting the growth of the market. Research report includes major key player analysis with shares of each player inside market, growth rate and market attractiveness in different end users/regions. Our study Artificial Intelligence in Retail Market helps user to make precise decision in order to expand their market presence and increase market share.

Impact of COVID-19 on Artificial Intelligence in Retail Market

Report covers Impact of Coronavirus COVID-19: Since the COVID-19 virus outbreak in December 2019, the disease has spread to almost every country around the globe with the World Health Organization declaring it a public health emergency. The global impacts of the coronavirus disease 2019 (COVID-19) are already starting to be felt, and will significantly affect the Artificial Intelligence in Retail market in 2020. The outbreak of COVID-19 has brought effects on many aspects, like flight cancellations; travel bans and quarantines; restaurants closed; all indoor/outdoor events restricted; over forty countries state of emergency declared; massive slowing of the supply chain; stock market volatility; falling business confidence, growing panic among the population, and uncertainty about future.

Market Segmentation

Global Artificial Intelligence in Retail Market Research report comprises of Porter's five forces analysis to do the detail study about its each segmentation like Product segmentation, End user/application segment analysis and Major key players analysis mentioned as below;

Competitive Landscape and Artificial Intelligence in Retail Market Share Analysis

Competitive analysis is the analysis of weakness and strength, marketplace expenditure, market share and market sales volume, and market trends of important players in the industry. The Artificial Intelligence in Retail marketplace study focused on including each of the key level, secondary level and tertiary level competitors in the report. The data created by conducting the primary and secondary research. The report covers detail analysis of motorist, limitations and scope to new players going into the Artificial Intelligence in Retail market.

Players Covered in Artificial Intelligence in Retail market are :

• Microsoft (US)
• Google (US)
• IBM (US)
• NVIDIA (US)
• Intel (US)
• Oracle (US)
• Sentient Technologies (US)
• Salesforce (US)
• Amazon Web Services (US)
• SAP (Germany)
• Inbenta Technologies (US)
• Nuance Communications (US)
• SAMSUNG (South Korea)
• Narrative Science (US)
• Daisy Intelligence (Canada)
• Infosys (India)
• Wipro (India)
• Happiest Minds (India)
• MicroStrategy (US)
• Dynamic Yield (US)
• IPsoft (US)
• Appier.com (Taiwan)
• ViSenze (Singapore)
• Manthan Software Services (India)
• Optoro (US)

Among other players domestic and global, Artificial Intelligence in Retail market share data is available for global, North America, Europe, Asia-Pacific, Middle East and Africa and South America separately. Our analysts understand competitive strengths and provide competitive analysis for each competitor separately.

Reasons to Buy our Report:

• The study consists of an analytical depiction of the global Artificial Intelligence in Retail market with current trends and future estimates to illustrate the impending investment pocket.
• Overall Artificial Intelligence in Retail market potential is determined by understanding profitability trends in order to gain stronger coverage in the market.
• This report provides information on key impact factors, limitations, and opportunities along with detailed impact analysis.
• The current Artificial Intelligence in Retail market is quantitatively analyzed from 2019 to 2024 to emphasize the financial capacity of the market.
• Porter's five force analyzes show buyer and supplier power.

Objective to buy this Report:

• Global Artificial Intelligence in Retail Market provides a detailed analysis of the market structure, with forecasts for various segments and sub-segments of the market.
• To provides insight into factors that influence market growth. Analyze markets based on a variety of factors, including price analysis, supply chain analysis, and porters five force analysis.
• To provide historical and forecasted revenue for market segments and sub-segments in relation to major regions and their countries.
• To provide national level analysis of the Artificial Intelligence in Retail market for current market size and future prospects.
• To provides country-level analysis of segment markets by application, product type, and sub-segment.
• To provide strategic profiling for key players in the market, comprehensively analyze key competencies, and drive market competition.

Chapter 1: Introduction
 1.1 Research Objectives
 1.2 Research Methodology
 1.3 Research Process
 1.4 Scope and Coverage
  1.4.1 Market Definition
  1.4.2 Key Questions Answered
 1.5 Market Segmentation

Chapter 2:Executive Summary

Chapter 3:Growth Opportunities By Segment
 3.1 By Type
 3.2 By Application

Chapter 4: Market Landscape
 4.1 Porter's Five Forces Analysis
  4.1.1 Bargaining Power of Supplier
  4.1.2 Threat of New Entrants
  4.1.3 Threat of Substitutes
  4.1.4 Competitive Rivalry
  4.1.5 Bargaining Power Among Buyers
 4.2 Industry Value Chain Analysis
 4.3 Market Dynamics
  3.5.1 Drivers
  3.5.2 Restraints
  3.5.3 Opportunities
  3.5.4 Challenges
 4.4 Pestle Analysis
 4.5 Technological Roadmap
 4.6 Regulatory Landscape
 4.7 SWOT Analysis
 4.8 Price Trend Analysis
 4.9 Patent Analysis
 4.10 Analysis of the Impact of Covid-19
  4.10.1 Impact on the Overall Market
  4.10.2 Impact on the Supply Chain
  4.10.3 Impact on the Key Manufacturers
  4.10.4 Impact on the Pricing

Chapter 4: Artificial Intelligence in Retail Market by Type
 4.1 Artificial Intelligence in Retail Market Overview Snapshot and Growth Engine
 4.2 Artificial Intelligence in Retail Market Overview
 4.3 Machine Learning and Deep Learning
  4.3.1 Introduction and Market Overview
  4.3.2 Historic and Forecasted Market Size (2016-2028F)
  4.3.3 Key Market Trends, Growth Factors and Opportunities
  4.3.4 Machine Learning and Deep Learning: Grographic Segmentation
 4.4 NLP
  4.4.1 Introduction and Market Overview
  4.4.2 Historic and Forecasted Market Size (2016-2028F)
  4.4.3 Key Market Trends, Growth Factors and Opportunities
  4.4.4 NLP: Grographic Segmentation

Chapter 5: Artificial Intelligence in Retail Market by Application
 5.1 Artificial Intelligence in Retail Market Overview Snapshot and Growth Engine
 5.2 Artificial Intelligence in Retail Market Overview
 5.3 Cloud
  5.3.1 Introduction and Market Overview
  5.3.2 Historic and Forecasted Market Size (2016-2028F)
  5.3.3 Key Market Trends, Growth Factors and Opportunities
  5.3.4 Cloud: Grographic Segmentation
 5.4 On-Premises
  5.4.1 Introduction and Market Overview
  5.4.2 Historic and Forecasted Market Size (2016-2028F)
  5.4.3 Key Market Trends, Growth Factors and Opportunities
  5.4.4 On-Premises: Grographic Segmentation

Chapter 6: Company Profiles and Competitive Analysis
 6.1 Competitive Landscape
  6.1.1 Competitive Positioning
  6.1.2 Artificial Intelligence in Retail Sales and Market Share By Players
  6.1.3 Industry BCG Matrix
  6.1.4 Ansoff Matrix
  6.1.5 Artificial Intelligence in Retail Industry Concentration Ratio (CR5 and HHI)
  6.1.6 Top 5 Artificial Intelligence in Retail Players Market Share
  6.1.7 Mergers and Acquisitions
  6.1.8 Business Strategies By Top Players
 6.2 MICROSOFT (US)
  6.2.1 Company Overview
  6.2.2 Key Executives
  6.2.3 Company Snapshot
  6.2.4 Operating Business Segments
  6.2.5 Product Portfolio
  6.2.6 Business Performance
  6.2.7 Key Strategic Moves and Recent Developments
  6.2.8 SWOT Analysis
 6.3 GOOGLE (US)
 6.4 IBM (US)
 6.5 NVIDIA (US)
 6.6 INTEL (US)
 6.7 ORACLE (US)
 6.8 SENTIENT TECHNOLOGIES (US)
 6.9 SALESFORCE (US)
 6.10 AMAZON WEB SERVICES (US)
 6.11 SAP (GERMANY)
 6.12 INBENTA TECHNOLOGIES (US)
 6.13 NUANCE COMMUNICATIONS (US)
 6.14 SAMSUNG (SOUTH KOREA)
 6.15 NARRATIVE SCIENCE (US)
 6.16 DAISY INTELLIGENCE (CANADA)
 6.17 INFOSYS (INDIA)
 6.18 WIPRO (INDIA)
 6.19 HAPPIEST MINDS (INDIA)
 6.20 MICROSTRATEGY (US)
 6.21 DYNAMIC YIELD (US)
 6.22 IPSOFT (US)
 6.23 APPIER.COM (TAIWAN)
 6.24 VISENZE (SINGAPORE)
 6.25 MANTHAN SOFTWARE SERVICES (INDIA)
 6.26 OPTORO (US)

Chapter 7: Global Artificial Intelligence in Retail Market Analysis, Insights and Forecast, 2016-2028
 7.1 Market Overview
 7.2 Historic and Forecasted Market Size By Type
  7.2.1 Machine Learning and Deep Learning
  7.2.2 NLP
 7.3 Historic and Forecasted Market Size By Application
  7.3.1 Cloud
  7.3.2 On-Premises

Chapter 8: North America Artificial Intelligence in Retail Market Analysis, Insights and Forecast, 2016-2028
 8.1 Key Market Trends, Growth Factors and Opportunities
 8.2 Impact of Covid-19
 8.3 Key Players
 8.4 Key Market Trends, Growth Factors and Opportunities
 8.4 Historic and Forecasted Market Size By Type
  8.4.1 Machine Learning and Deep Learning
  8.4.2 NLP
 8.5 Historic and Forecasted Market Size By Application
  8.5.1 Cloud
  8.5.2 On-Premises
 8.6 Historic and Forecast Market Size by Country
  8.6.1 U.S.
  8.6.2 Canada
  8.6.3 Mexico

Chapter 9: Europe Artificial Intelligence in Retail Market Analysis, Insights and Forecast, 2016-2028
 9.1 Key Market Trends, Growth Factors and Opportunities
 9.2 Impact of Covid-19
 9.3 Key Players
 9.4 Key Market Trends, Growth Factors and Opportunities
 9.4 Historic and Forecasted Market Size By Type
  9.4.1 Machine Learning and Deep Learning
  9.4.2 NLP
 9.5 Historic and Forecasted Market Size By Application
  9.5.1 Cloud
  9.5.2 On-Premises
 9.6 Historic and Forecast Market Size by Country
  9.6.1 Germany
  9.6.2 U.K.
  9.6.3 France
  9.6.4 Italy
  9.6.5 Russia
  9.6.6 Spain

Chapter 10: Asia-Pacific Artificial Intelligence in Retail Market Analysis, Insights and Forecast, 2016-2028
 10.1 Key Market Trends, Growth Factors and Opportunities
 10.2 Impact of Covid-19
 10.3 Key Players
 10.4 Key Market Trends, Growth Factors and Opportunities
 10.4 Historic and Forecasted Market Size By Type
  10.4.1 Machine Learning and Deep Learning
  10.4.2 NLP
 10.5 Historic and Forecasted Market Size By Application
  10.5.1 Cloud
  10.5.2 On-Premises
 10.6 Historic and Forecast Market Size by Country
  10.6.1 China
  10.6.2 India
  10.6.3 Japan
  10.6.4 Southeast Asia

Chapter 11: South America Artificial Intelligence in Retail Market Analysis, Insights and Forecast, 2016-2028
 11.1 Key Market Trends, Growth Factors and Opportunities
 11.2 Impact of Covid-19
 11.3 Key Players
 11.4 Key Market Trends, Growth Factors and Opportunities
 11.4 Historic and Forecasted Market Size By Type
  11.4.1 Machine Learning and Deep Learning
  11.4.2 NLP
 11.5 Historic and Forecasted Market Size By Application
  11.5.1 Cloud
  11.5.2 On-Premises
 11.6 Historic and Forecast Market Size by Country
  11.6.1 Brazil
  11.6.2 Argentina

Chapter 12: Middle East & Africa Artificial Intelligence in Retail Market Analysis, Insights and Forecast, 2016-2028
 12.1 Key Market Trends, Growth Factors and Opportunities
 12.2 Impact of Covid-19
 12.3 Key Players
 12.4 Key Market Trends, Growth Factors and Opportunities
 12.4 Historic and Forecasted Market Size By Type
  12.4.1 Machine Learning and Deep Learning
  12.4.2 NLP
 12.5 Historic and Forecasted Market Size By Application
  12.5.1 Cloud
  12.5.2 On-Premises
 12.6 Historic and Forecast Market Size by Country
  12.6.1 Saudi Arabia
  12.6.2 South Africa

Chapter 13 Investment Analysis

Chapter 14 Analyst Viewpoint and Conclusion

LIST OF TABLES

TABLE 001. EXECUTIVE SUMMARY
TABLE 002. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET BARGAINING POWER OF SUPPLIERS
TABLE 003. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET BARGAINING POWER OF CUSTOMERS
TABLE 004. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET COMPETITIVE RIVALRY
TABLE 005. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET THREAT OF NEW ENTRANTS
TABLE 006. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET THREAT OF SUBSTITUTES
TABLE 007. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET BY TYPE
TABLE 008. MACHINE LEARNING AND DEEP LEARNING MARKET OVERVIEW (2016-2028)
TABLE 009. NLP MARKET OVERVIEW (2016-2028)
TABLE 010. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET BY APPLICATION
TABLE 011. CLOUD MARKET OVERVIEW (2016-2028)
TABLE 012. ON-PREMISES MARKET OVERVIEW (2016-2028)
TABLE 013. NORTH AMERICA ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE (2016-2028)
TABLE 014. NORTH AMERICA ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY APPLICATION (2016-2028)
TABLE 015. N ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY COUNTRY (2016-2028)
TABLE 016. EUROPE ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE (2016-2028)
TABLE 017. EUROPE ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY APPLICATION (2016-2028)
TABLE 018. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY COUNTRY (2016-2028)
TABLE 019. ASIA PACIFIC ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE (2016-2028)
TABLE 020. ASIA PACIFIC ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY APPLICATION (2016-2028)
TABLE 021. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY COUNTRY (2016-2028)
TABLE 022. MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE (2016-2028)
TABLE 023. MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY APPLICATION (2016-2028)
TABLE 024. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY COUNTRY (2016-2028)
TABLE 025. SOUTH AMERICA ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE (2016-2028)
TABLE 026. SOUTH AMERICA ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY APPLICATION (2016-2028)
TABLE 027. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY COUNTRY (2016-2028)
TABLE 028. MICROSOFT (US): SNAPSHOT
TABLE 029. MICROSOFT (US): BUSINESS PERFORMANCE
TABLE 030. MICROSOFT (US): PRODUCT PORTFOLIO
TABLE 031. MICROSOFT (US): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 031. GOOGLE (US): SNAPSHOT
TABLE 032. GOOGLE (US): BUSINESS PERFORMANCE
TABLE 033. GOOGLE (US): PRODUCT PORTFOLIO
TABLE 034. GOOGLE (US): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 034. IBM (US): SNAPSHOT
TABLE 035. IBM (US): BUSINESS PERFORMANCE
TABLE 036. IBM (US): PRODUCT PORTFOLIO
TABLE 037. IBM (US): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 037. NVIDIA (US): SNAPSHOT
TABLE 038. NVIDIA (US): BUSINESS PERFORMANCE
TABLE 039. NVIDIA (US): PRODUCT PORTFOLIO
TABLE 040. NVIDIA (US): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 040. INTEL (US): SNAPSHOT
TABLE 041. INTEL (US): BUSINESS PERFORMANCE
TABLE 042. INTEL (US): PRODUCT PORTFOLIO
TABLE 043. INTEL (US): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 043. ORACLE (US): SNAPSHOT
TABLE 044. ORACLE (US): BUSINESS PERFORMANCE
TABLE 045. ORACLE (US): PRODUCT PORTFOLIO
TABLE 046. ORACLE (US): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 046. SENTIENT TECHNOLOGIES (US): SNAPSHOT
TABLE 047. SENTIENT TECHNOLOGIES (US): BUSINESS PERFORMANCE
TABLE 048. SENTIENT TECHNOLOGIES (US): PRODUCT PORTFOLIO
TABLE 049. SENTIENT TECHNOLOGIES (US): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 049. SALESFORCE (US): SNAPSHOT
TABLE 050. SALESFORCE (US): BUSINESS PERFORMANCE
TABLE 051. SALESFORCE (US): PRODUCT PORTFOLIO
TABLE 052. SALESFORCE (US): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 052. AMAZON WEB SERVICES (US): SNAPSHOT
TABLE 053. AMAZON WEB SERVICES (US): BUSINESS PERFORMANCE
TABLE 054. AMAZON WEB SERVICES (US): PRODUCT PORTFOLIO
TABLE 055. AMAZON WEB SERVICES (US): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 055. SAP (GERMANY): SNAPSHOT
TABLE 056. SAP (GERMANY): BUSINESS PERFORMANCE
TABLE 057. SAP (GERMANY): PRODUCT PORTFOLIO
TABLE 058. SAP (GERMANY): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 058. INBENTA TECHNOLOGIES (US): SNAPSHOT
TABLE 059. INBENTA TECHNOLOGIES (US): BUSINESS PERFORMANCE
TABLE 060. INBENTA TECHNOLOGIES (US): PRODUCT PORTFOLIO
TABLE 061. INBENTA TECHNOLOGIES (US): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 061. NUANCE COMMUNICATIONS (US): SNAPSHOT
TABLE 062. NUANCE COMMUNICATIONS (US): BUSINESS PERFORMANCE
TABLE 063. NUANCE COMMUNICATIONS (US): PRODUCT PORTFOLIO
TABLE 064. NUANCE COMMUNICATIONS (US): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 064. SAMSUNG (SOUTH KOREA): SNAPSHOT
TABLE 065. SAMSUNG (SOUTH KOREA): BUSINESS PERFORMANCE
TABLE 066. SAMSUNG (SOUTH KOREA): PRODUCT PORTFOLIO
TABLE 067. SAMSUNG (SOUTH KOREA): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 067. NARRATIVE SCIENCE (US): SNAPSHOT
TABLE 068. NARRATIVE SCIENCE (US): BUSINESS PERFORMANCE
TABLE 069. NARRATIVE SCIENCE (US): PRODUCT PORTFOLIO
TABLE 070. NARRATIVE SCIENCE (US): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 070. DAISY INTELLIGENCE (CANADA): SNAPSHOT
TABLE 071. DAISY INTELLIGENCE (CANADA): BUSINESS PERFORMANCE
TABLE 072. DAISY INTELLIGENCE (CANADA): PRODUCT PORTFOLIO
TABLE 073. DAISY INTELLIGENCE (CANADA): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 073. INFOSYS (INDIA): SNAPSHOT
TABLE 074. INFOSYS (INDIA): BUSINESS PERFORMANCE
TABLE 075. INFOSYS (INDIA): PRODUCT PORTFOLIO
TABLE 076. INFOSYS (INDIA): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 076. WIPRO (INDIA): SNAPSHOT
TABLE 077. WIPRO (INDIA): BUSINESS PERFORMANCE
TABLE 078. WIPRO (INDIA): PRODUCT PORTFOLIO
TABLE 079. WIPRO (INDIA): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 079. HAPPIEST MINDS (INDIA): SNAPSHOT
TABLE 080. HAPPIEST MINDS (INDIA): BUSINESS PERFORMANCE
TABLE 081. HAPPIEST MINDS (INDIA): PRODUCT PORTFOLIO
TABLE 082. HAPPIEST MINDS (INDIA): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 082. MICROSTRATEGY (US): SNAPSHOT
TABLE 083. MICROSTRATEGY (US): BUSINESS PERFORMANCE
TABLE 084. MICROSTRATEGY (US): PRODUCT PORTFOLIO
TABLE 085. MICROSTRATEGY (US): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 085. DYNAMIC YIELD (US): SNAPSHOT
TABLE 086. DYNAMIC YIELD (US): BUSINESS PERFORMANCE
TABLE 087. DYNAMIC YIELD (US): PRODUCT PORTFOLIO
TABLE 088. DYNAMIC YIELD (US): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 088. IPSOFT (US): SNAPSHOT
TABLE 089. IPSOFT (US): BUSINESS PERFORMANCE
TABLE 090. IPSOFT (US): PRODUCT PORTFOLIO
TABLE 091. IPSOFT (US): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 091. APPIER.COM (TAIWAN): SNAPSHOT
TABLE 092. APPIER.COM (TAIWAN): BUSINESS PERFORMANCE
TABLE 093. APPIER.COM (TAIWAN): PRODUCT PORTFOLIO
TABLE 094. APPIER.COM (TAIWAN): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 094. VISENZE (SINGAPORE): SNAPSHOT
TABLE 095. VISENZE (SINGAPORE): BUSINESS PERFORMANCE
TABLE 096. VISENZE (SINGAPORE): PRODUCT PORTFOLIO
TABLE 097. VISENZE (SINGAPORE): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 097. MANTHAN SOFTWARE SERVICES (INDIA): SNAPSHOT
TABLE 098. MANTHAN SOFTWARE SERVICES (INDIA): BUSINESS PERFORMANCE
TABLE 099. MANTHAN SOFTWARE SERVICES (INDIA): PRODUCT PORTFOLIO
TABLE 100. MANTHAN SOFTWARE SERVICES (INDIA): KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 100. OPTORO (US): SNAPSHOT
TABLE 101. OPTORO (US): BUSINESS PERFORMANCE
TABLE 102. OPTORO (US): PRODUCT PORTFOLIO
TABLE 103. OPTORO (US): KEY STRATEGIC MOVES AND DEVELOPMENTS

LIST OF FIGURES

FIGURE 001. YEARS CONSIDERED FOR ANALYSIS
FIGURE 002. SCOPE OF THE STUDY
FIGURE 003. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET OVERVIEW BY REGIONS
FIGURE 004. PORTER'S FIVE FORCES ANALYSIS
FIGURE 005. BARGAINING POWER OF SUPPLIERS
FIGURE 006. COMPETITIVE RIVALRYFIGURE 007. THREAT OF NEW ENTRANTS
FIGURE 008. THREAT OF SUBSTITUTES
FIGURE 009. VALUE CHAIN ANALYSIS
FIGURE 010. PESTLE ANALYSIS
FIGURE 011. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET OVERVIEW BY TYPE
FIGURE 012. MACHINE LEARNING AND DEEP LEARNING MARKET OVERVIEW (2016-2028)
FIGURE 013. NLP MARKET OVERVIEW (2016-2028)
FIGURE 014. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET OVERVIEW BY APPLICATION
FIGURE 015. CLOUD MARKET OVERVIEW (2016-2028)
FIGURE 016. ON-PREMISES MARKET OVERVIEW (2016-2028)
FIGURE 017. NORTH AMERICA ARTIFICIAL INTELLIGENCE IN RETAIL MARKET OVERVIEW BY COUNTRY (2016-2028)
FIGURE 018. EUROPE ARTIFICIAL INTELLIGENCE IN RETAIL MARKET OVERVIEW BY COUNTRY (2016-2028)
FIGURE 019. ASIA PACIFIC ARTIFICIAL INTELLIGENCE IN RETAIL MARKET OVERVIEW BY COUNTRY (2016-2028)
FIGURE 020. MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN RETAIL MARKET OVERVIEW BY COUNTRY (2016-2028)
FIGURE 021. SOUTH AMERICA ARTIFICIAL INTELLIGENCE IN RETAIL MARKET OVERVIEW BY COUNTRY (2016-2028)

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