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Global Machine Learning in Retail Market Research Report 2024
Synopsis
In the retail sector, top competitors like Amazon, Walmart, Target, and Home Depot clearly and publicly rely on data, analytics, and machine learning to create their market edge. As a result, ML is fast becoming a commonly used tool among retail marketers.
The global Machine Learning in Retail market was valued at US$ 2487 million in 2023 and is anticipated to reach US$ 3743.5 million by 2030, witnessing a CAGR of 5.9% during the forecast period 2024-2030.
North American market for Machine Learning in Retail is estimated to increase from $ million in 2023 to reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
Asia-Pacific market for Machine Learning in Retail is estimated to increase from $ million in 2023 to reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
The global market for Machine Learning in Retail in Online is estimated to increase from $ million in 2023 to $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
The major global companies of Machine Learning in Retail include IBM, Microsoft, Amazon Web Services, Oracle, SAP, Intel, NVIDIA, Google and Sentient Technologies, etc. In 2023, the world's top three vendors accounted for approximately % of the revenue.
This report aims to provide a comprehensive presentation of the global market for Machine Learning in Retail, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Machine Learning in Retail.
Report Scope
The Machine Learning in Retail market size, estimations, and forecasts are provided in terms of revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. This report segments the global Machine Learning in Retail market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Machine Learning in Retail companies, new entrants, and industry chain related companies in this market with information on the revenues, sales volume, and average price for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
Market Segmentation
By Company
IBM
Microsoft
Amazon Web Services
Oracle
SAP
Intel
NVIDIA
Google
Sentient Technologies
Salesforce
ViSenze
Segment by Type
Cloud Based
On-Premises
Segment by Application
Online
Offline
By Region
North America
United States
Canada
Europe
Germany
France
UK
Italy
Russia
Nordic Countries
Rest of Europe
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type, by Application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of Machine Learning in Retail companies’ competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.
In the retail sector, top competitors like Amazon, Walmart, Target, and Home Depot clearly and publicly rely on data, analytics, and machine learning to create their market edge. As a result, ML is fast becoming a commonly used tool among retail marketers.
The global Machine Learning in Retail market was valued at US$ 2487 million in 2023 and is anticipated to reach US$ 3743.5 million by 2030, witnessing a CAGR of 5.9% during the forecast period 2024-2030.
North American market for Machine Learning in Retail is estimated to increase from $ million in 2023 to reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
Asia-Pacific market for Machine Learning in Retail is estimated to increase from $ million in 2023 to reach $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
The global market for Machine Learning in Retail in Online is estimated to increase from $ million in 2023 to $ million by 2030, at a CAGR of % during the forecast period of 2024 through 2030.
The major global companies of Machine Learning in Retail include IBM, Microsoft, Amazon Web Services, Oracle, SAP, Intel, NVIDIA, Google and Sentient Technologies, etc. In 2023, the world's top three vendors accounted for approximately % of the revenue.
This report aims to provide a comprehensive presentation of the global market for Machine Learning in Retail, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Machine Learning in Retail.
Report Scope
The Machine Learning in Retail market size, estimations, and forecasts are provided in terms of revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. This report segments the global Machine Learning in Retail market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Machine Learning in Retail companies, new entrants, and industry chain related companies in this market with information on the revenues, sales volume, and average price for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
Market Segmentation
By Company
IBM
Microsoft
Amazon Web Services
Oracle
SAP
Intel
NVIDIA
Sentient Technologies
Salesforce
ViSenze
Segment by Type
Cloud Based
On-Premises
Segment by Application
Online
Offline
By Region
North America
United States
Canada
Europe
Germany
France
UK
Italy
Russia
Nordic Countries
Rest of Europe
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type, by Application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of Machine Learning in Retail companies’ competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.
Index1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global Machine Learning in Retail Market Size Growth Rate by Type: 2019 VS 2023 VS 2030
1.2.2 Cloud Based
1.2.3 On-Premises
1.3 Market by Application
1.3.1 Global Machine Learning in Retail Market Growth by Application: 2019 VS 2023 VS 2030
1.3.2 Online
1.3.3 Offline
1.4 Study Objectives
1.5 Years Considered
1.6 Years Considered
2 Global Growth Trends
2.1 Global Machine Learning in Retail Market Perspective (2019-2030)
2.2 Machine Learning in Retail Growth Trends by Region
2.2.1 Global Machine Learning in Retail Market Size by Region: 2019 VS 2023 VS 2030
2.2.2 Machine Learning in Retail Historic Market Size by Region (2019-2024)
2.2.3 Machine Learning in Retail Forecasted Market Size by Region (2025-2030)
2.3 Machine Learning in Retail Market Dynamics
2.3.1 Machine Learning in Retail Industry Trends
2.3.2 Machine Learning in Retail Market Drivers
2.3.3 Machine Learning in Retail Market Challenges
2.3.4 Machine Learning in Retail Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top Machine Learning in Retail Players by Revenue
3.1.1 Global Top Machine Learning in Retail Players by Revenue (2019-2024)
3.1.2 Global Machine Learning in Retail Revenue Market Share by Players (2019-2024)
3.2 Global Machine Learning in Retail Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Players Covered: Ranking by Machine Learning in Retail Revenue
3.4 Global Machine Learning in Retail Market Concentration Ratio
3.4.1 Global Machine Learning in Retail Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Machine Learning in Retail Revenue in 2023
3.5 Machine Learning in Retail Key Players Head office and Area Served
3.6 Key Players Machine Learning in Retail Product Solution and Service
3.7 Date of Enter into Machine Learning in Retail Market
3.8 Mergers & Acquisitions, Expansion Plans
4 Machine Learning in Retail Breakdown Data by Type
4.1 Global Machine Learning in Retail Historic Market Size by Type (2019-2024)
4.2 Global Machine Learning in Retail Forecasted Market Size by Type (2025-2030)
5 Machine Learning in Retail Breakdown Data by Application
5.1 Global Machine Learning in Retail Historic Market Size by Application (2019-2024)
5.2 Global Machine Learning in Retail Forecasted Market Size by Application (2025-2030)
6 North America
6.1 North America Machine Learning in Retail Market Size (2019-2030)
6.2 North America Machine Learning in Retail Market Growth Rate by Country: 2019 VS 2023 VS 2030
6.3 North America Machine Learning in Retail Market Size by Country (2019-2024)
6.4 North America Machine Learning in Retail Market Size by Country (2025-2030)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe Machine Learning in Retail Market Size (2019-2030)
7.2 Europe Machine Learning in Retail Market Growth Rate by Country: 2019 VS 2023 VS 2030
7.3 Europe Machine Learning in Retail Market Size by Country (2019-2024)
7.4 Europe Machine Learning in Retail Market Size by Country (2025-2030)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Machine Learning in Retail Market Size (2019-2030)
8.2 Asia-Pacific Machine Learning in Retail Market Growth Rate by Region: 2019 VS 2023 VS 2030
8.3 Asia-Pacific Machine Learning in Retail Market Size by Region (2019-2024)
8.4 Asia-Pacific Machine Learning in Retail Market Size by Region (2025-2030)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America Machine Learning in Retail Market Size (2019-2030)
9.2 Latin America Machine Learning in Retail Market Growth Rate by Country: 2019 VS 2023 VS 2030
9.3 Latin America Machine Learning in Retail Market Size by Country (2019-2024)
9.4 Latin America Machine Learning in Retail Market Size by Country (2025-2030)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Machine Learning in Retail Market Size (2019-2030)
10.2 Middle East & Africa Machine Learning in Retail Market Growth Rate by Country: 2019 VS 2023 VS 2030
10.3 Middle East & Africa Machine Learning in Retail Market Size by Country (2019-2024)
10.4 Middle East & Africa Machine Learning in Retail Market Size by Country (2025-2030)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 IBM
11.1.1 IBM Company Detail
11.1.2 IBM Business Overview
11.1.3 IBM Machine Learning in Retail Introduction
11.1.4 IBM Revenue in Machine Learning in Retail Business (2019-2024)
11.1.5 IBM Recent Development
11.2 Microsoft
11.2.1 Microsoft Company Detail
11.2.2 Microsoft Business Overview
11.2.3 Microsoft Machine Learning in Retail Introduction
11.2.4 Microsoft Revenue in Machine Learning in Retail Business (2019-2024)
11.2.5 Microsoft Recent Development
11.3 Amazon Web Services
11.3.1 Amazon Web Services Company Detail
11.3.2 Amazon Web Services Business Overview
11.3.3 Amazon Web Services Machine Learning in Retail Introduction
11.3.4 Amazon Web Services Revenue in Machine Learning in Retail Business (2019-2024)
11.3.5 Amazon Web Services Recent Development
11.4 Oracle
11.4.1 Oracle Company Detail
11.4.2 Oracle Business Overview
11.4.3 Oracle Machine Learning in Retail Introduction
11.4.4 Oracle Revenue in Machine Learning in Retail Business (2019-2024)
11.4.5 Oracle Recent Development
11.5 SAP
11.5.1 SAP Company Detail
11.5.2 SAP Business Overview
11.5.3 SAP Machine Learning in Retail Introduction
11.5.4 SAP Revenue in Machine Learning in Retail Business (2019-2024)
11.5.5 SAP Recent Development
11.6 Intel
11.6.1 Intel Company Detail
11.6.2 Intel Business Overview
11.6.3 Intel Machine Learning in Retail Introduction
11.6.4 Intel Revenue in Machine Learning in Retail Business (2019-2024)
11.6.5 Intel Recent Development
11.7 NVIDIA
11.7.1 NVIDIA Company Detail
11.7.2 NVIDIA Business Overview
11.7.3 NVIDIA Machine Learning in Retail Introduction
11.7.4 NVIDIA Revenue in Machine Learning in Retail Business (2019-2024)
11.7.5 NVIDIA Recent Development
11.8 Google
11.8.1 Google Company Detail
11.8.2 Google Business Overview
11.8.3 Google Machine Learning in Retail Introduction
11.8.4 Google Revenue in Machine Learning in Retail Business (2019-2024)
11.8.5 Google Recent Development
11.9 Sentient Technologies
11.9.1 Sentient Technologies Company Detail
11.9.2 Sentient Technologies Business Overview
11.9.3 Sentient Technologies Machine Learning in Retail Introduction
11.9.4 Sentient Technologies Revenue in Machine Learning in Retail Business (2019-2024)
11.9.5 Sentient Technologies Recent Development
11.10 Salesforce
11.10.1 Salesforce Company Detail
11.10.2 Salesforce Business Overview
11.10.3 Salesforce Machine Learning in Retail Introduction
11.10.4 Salesforce Revenue in Machine Learning in Retail Business (2019-2024)
11.10.5 Salesforce Recent Development
11.11 ViSenze
11.11.1 ViSenze Company Detail
11.11.2 ViSenze Business Overview
11.11.3 ViSenze Machine Learning in Retail Introduction
11.11.4 ViSenze Revenue in Machine Learning in Retail Business (2019-2024)
11.11.5 ViSenze Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.2 Data Source
13.2 Disclaimer
13.3 Author Details
Published By : QY Research
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