PUBLISHER: TechNavio | PRODUCT CODE: 1915693
PUBLISHER: TechNavio | PRODUCT CODE: 1915693
Global Machine Learning In Retail Market 2025-2029
The global machine learning in retail market is forecasted to grow by USD 22260.3 mn during 2024-2029, accelerating at a CAGR of 32.7% during the forecast period. The report on the global machine learning in retail market provides a holistic analysis, market size and forecast, trends, growth drivers, and challenges, as well as vendor analysis covering around 25 vendors.
The report offers an up-to-date analysis regarding the current market scenario, the latest trends and drivers, and the overall market environment. The market is driven by proliferation of hyper-personalization and enhanced customer experience, imperative for supply chain and operational efficiency, ascendance of generative AI and conversational commerce.
The study was conducted using an objective combination of primary and secondary information including inputs from key participants in the industry. The report contains a comprehensive market size data, segment with regional analysis and vendor landscape in addition to an analysis of the key companies. Reports have historic and forecast data.
| Market Scope | |
|---|---|
| Base Year | 2025 |
| End Year | 2029 |
| Series Year | 2025-2029 |
| Growth Momentum | Accelerate |
| YOY 2025 | 30.7% |
| CAGR | 32.7% |
| Incremental Value | $22260.3 mn |
Technavio's global machine learning in retail market is segmented as below:
By Component
- Software
- Services
By Deployment
- Cloud-based
- On-premises
By End-User
- FMCG
- Electronics
- Apparel
- Others
Geography
- North America
- US
- Canada
- Mexico
- Europe
- Germany
- UK
- France
- Italy
- Spain
- The Netherlands
- APAC
- China
- Japan
- India
- South Korea
- Australia
- Indonesia
- Middle East and Africa
- UAE
- South Africa
- Turkey
- South America
- Brazil
- Colombia
- Argentina
- Rest of World (ROW)
This study identifies the hyper-personalization at scale fueled by generative AI as one of the prime reasons driving the global machine learning in retail market growth during the next few years. Also, ai-driven autonomous operations and resilient supply chain management and proliferation of computer vision for in-store analytics and frictionless commerce will lead to sizable demand in the market.
The report on the global machine learning in retail market covers the following areas:
- Global machine learning in retail market sizing
- Global machine learning in retail market forecast
- Global machine learning in retail market industry analysis
The robust vendor analysis is designed to help clients improve their market position, and in line with this, this report provides a detailed analysis of several leading global machine learning in retail market vendors that include Adobe Inc., Algolia Inc., Amazon Web Services Inc., BloomReach Inc., Blue Yonder Group Inc., Consultadoria e Inovacao Tecnologica S.A., Databricks Inc., Google Cloud, H2O.ai Inc., Microsoft Corp., Oracle Corp., SAP SE, SAS Institute Inc., Sephora USA Inc., Snowflake Inc., Stylumia Intelligence Technology Pvt Ltd, Teradata Corp., Walmart Inc.. Also, the global machine learning in retail market analysis report includes information on upcoming trends and challenges that will influence market growth. This is to help companies strategize and leverage all forthcoming growth opportunities.
The publisher presents a detailed picture of the market by the way of study, synthesis, and summation of data from multiple sources by an analysis of key parameters such as profit, pricing, competition, and promotions. It presents various market facets by identifying the key industry influencers. The data presented is comprehensive, reliable, and a result of extensive primary and secondary research. The market research reports provide a complete competitive landscape and an in-depth vendor selection methodology and analysis using qualitative and quantitative research to forecast accurate market growth.
Table of Contents
1 Executive Summary
- 1.1 Market overview
- Executive Summary - Chart on Market Overview
- Executive Summary - Data Table on Market Overview
- Executive Summary - Chart on Global Market Characteristics
- Executive Summary - Chart on Market by Geography
- Executive Summary - Chart on Market Segmentation by Component
- Executive Summary - Chart on Market Segmentation by Deployment
- Executive Summary - Chart on Market Segmentation by End-user
- Executive Summary - Chart on Incremental Growth
- Executive Summary - Data Table on Incremental Growth
- Executive Summary - Chart on Company Market Positioning
2 Technavio Analysis
- 2.1 Analysis of price sensitivity, lifecycle, customer purchase basket, adoption rates, and purchase criteria
- Analysis of price sensitivity, lifecycle, customer purchase basket, adoption rates, and purchase criteria
- 2.2 Criticality of inputs and Factors of differentiation
- 2.3 Factors of disruption
- 2.4 Impact of drivers and challenges
3 Market Landscape
- 3.1 Market ecosystem
- 3.2 Market characteristics
- 3.3 Value chain analysis
4 Market Sizing
- 4.1 Market definition
- 4.2 Market segment analysis
- Market segments
- 4.3 Market size 2024
- 4.4 Market outlook: Forecast for 2024-2029
5 Historic Market Size
- 5.1 Global Machine Learning In Retail Market 2019 - 2023
- Historic Market Size - Data Table on Global Machine Learning In Retail Market 2019 - 2023 ($ million)
- 5.2 Component segment analysis 2019 - 2023
- Historic Market Size - Component Segment 2019 - 2023 ($ million)
- 5.3 Deployment segment analysis 2019 - 2023
- Historic Market Size - Deployment Segment 2019 - 2023 ($ million)
- 5.4 End-user segment analysis 2019 - 2023
- Historic Market Size - End-user Segment 2019 - 2023 ($ million)
- 5.5 Geography segment analysis 2019 - 2023
- Historic Market Size - Geography Segment 2019 - 2023 ($ million)
- 5.6 Country segment analysis 2019 - 2023
- Historic Market Size - Country Segment 2019 - 2023 ($ million)
6 Five Forces Analysis
- 6.1 Five forces summary
- Five forces analysis - Comparison between 2024 and 2029
- 6.2 Bargaining power of buyers
- Bargaining power of buyers - Impact of key factors 2024 and 2029
- 6.3 Bargaining power of suppliers
- Bargaining power of suppliers - Impact of key factors in 2024 and 2029
- 6.4 Threat of new entrants
- Threat of new entrants - Impact of key factors in 2024 and 2029
- 6.5 Threat of substitutes
- Threat of substitutes - Impact of key factors in 2024 and 2029
- 6.6 Threat of rivalry
- Threat of rivalry - Impact of key factors in 2024 and 2029
- 6.7 Market condition
7 Market Segmentation by Component
- 7.1 Market segments
- 7.2 Comparison by Component
- 7.3 Software - Market size and forecast 2024-2029
- 7.4 Services - Market size and forecast 2024-2029
- 7.5 Market opportunity by Component
- Market opportunity by Component ($ million)
8 Market Segmentation by Deployment
- 8.1 Market segments
- 8.2 Comparison by Deployment
- 8.3 Cloud-based - Market size and forecast 2024-2029
- 8.4 On-premises - Market size and forecast 2024-2029
- 8.5 Market opportunity by Deployment
- Market opportunity by Deployment ($ million)
9 Market Segmentation by End-user
- 9.1 Market segments
- 9.2 Comparison by End-user
- 9.3 FMCG - Market size and forecast 2024-2029
- 9.4 Electronics - Market size and forecast 2024-2029
- 9.5 Apparel - Market size and forecast 2024-2029
- 9.6 Others - Market size and forecast 2024-2029
- 9.7 Market opportunity by End-user
- Market opportunity by End-user ($ million)
10 Customer Landscape
- 10.1 Customer landscape overview
- Analysis of price sensitivity, lifecycle, customer purchase basket, adoption rates, and purchase criteria
11 Geographic Landscape
- 11.1 Geographic segmentation
- 11.2 Geographic comparison
- 11.3 North America - Market size and forecast 2024-2029
- 11.3.1 US - Market size and forecast 2024-2029
- 11.3.2 Canada - Market size and forecast 2024-2029
- 11.3.3 Mexico - Market size and forecast 2024-2029
- 11.4 Europe - Market size and forecast 2024-2029
- 11.4.1 Germany - Market size and forecast 2024-2029
- 11.4.2 UK - Market size and forecast 2024-2029
- 11.4.3 France - Market size and forecast 2024-2029
- 11.4.4 Italy - Market size and forecast 2024-2029
- 11.4.5 Spain - Market size and forecast 2024-2029
- 11.4.6 The Netherlands - Market size and forecast 2024-2029
- 11.5 APAC - Market size and forecast 2024-2029
- 11.5.1 China - Market size and forecast 2024-2029
- 11.5.2 Japan - Market size and forecast 2024-2029
- 11.5.3 India - Market size and forecast 2024-2029
- 11.5.4 South Korea - Market size and forecast 2024-2029
- 11.5.5 Australia - Market size and forecast 2024-2029
- 11.5.6 Indonesia - Market size and forecast 2024-2029
- 11.6 Middle East and Africa - Market size and forecast 2024-2029
- 11.6.1 Saudi Arabia - Market size and forecast 2024-2029
- 11.6.2 UAE - Market size and forecast 2024-2029
- 11.6.3 South Africa - Market size and forecast 2024-2029
- 11.6.4 Israel - Market size and forecast 2024-2029
- 11.6.5 Turkey - Market size and forecast 2024-2029
- 11.7 South America - Market size and forecast 2024-2029
- 11.7.1 Brazil - Market size and forecast 2024-2029
- 11.7.2 Colombia - Market size and forecast 2024-2029
- 11.7.3 Argentina - Market size and forecast 2024-2029
- 11.8 Market opportunity by geography
- Market opportunity by geography ($ million)
- Data Tables on Market opportunity by geography ($ million)
12 Drivers, Challenges, and Opportunity
- 12.1 Market drivers
- Proliferation of hyper-personalization and enhanced customer experience
- Imperative for supply chain and operational efficiency
- Ascendance of generative AI and conversational commerce
- 12.2 Market challenges
- Data privacy, security, and regulatory compliance
- High implementation costs and scarcity of specialized talent
- Integration complexity, model interpretability, and ethical concerns
- 12.3 Impact of drivers and challenges
- Impact of drivers and challenges in 2024 and 2029
- 12.4 Market opportunities
- Hyper-personalization at scale fueled by generative AI
- AI-driven autonomous operations and resilient supply chain management
- Proliferation of computer vision for in-store analytics and frictionless commerce
13 Competitive Landscape
- 13.1 Overview
- 13.2 Competitive Landscape
- Overview on criticality of inputs and factors of differentiation
- 13.3 Landscape disruption
- Overview on factors of disruption
- 13.4 Industry risks
- Impact of key risks on business
14 Competitive Analysis
- 14.1 Companies profiled
- Companies covered
- 14.2 Company ranking index
- Company ranking index
- 14.3 Market positioning of companies
- Matrix on companies position and classification
- 14.4 Algolia Inc.
- Algolia Inc. - Overview
- Algolia Inc. - Product / Service
- Algolia Inc. - Key offerings
- SWOT
- 14.5 Amazon Web Services Inc.
- Amazon Web Services Inc. - Overview
- Amazon Web Services Inc. - Product / Service
- Amazon Web Services Inc. - Key news
- Amazon Web Services Inc. - Key offerings
- SWOT
- 14.6 BloomReach Inc.
- BloomReach Inc. - Overview
- BloomReach Inc. - Product / Service
- BloomReach Inc. - Key offerings
- SWOT
- 14.7 Blue Yonder Group Inc.
- Blue Yonder Group Inc. - Overview
- Blue Yonder Group Inc. - Product / Service
- Blue Yonder Group Inc. - Key offerings
- SWOT
- 14.8 Consultadoria e Inovacao Tecnologica S.A.
- Consultadoria e Inovacao Tecnologica S.A. - Overview
- Consultadoria e Inovacao Tecnologica S.A. - Product / Service
- Consultadoria e Inovacao Tecnologica S.A. - Key offerings
- SWOT
- 14.9 Databricks Inc.
- Databricks Inc. - Overview
- Databricks Inc. - Product / Service
- Databricks Inc. - Key offerings
- SWOT
- 14.10 Google Cloud
- Google Cloud - Overview
- Google Cloud - Product / Service
- Google Cloud - Key offerings
- SWOT
- 14.11 H2O.ai Inc.
- H2O.ai Inc. - Overview
- H2O.ai Inc. - Product / Service
- H2O.ai Inc. - Key offerings
- SWOT
- 14.12 Microsoft Corp.
- Microsoft Corp. - Overview
- Microsoft Corp. - Business segments
- Microsoft Corp. - Key news
- Microsoft Corp. - Key offerings
- Microsoft Corp. - Segment focus
- SWOT
- 14.13 Oracle Corp.
- Oracle Corp. - Overview
- Oracle Corp. - Business segments
- Oracle Corp. - Key news
- Oracle Corp. - Key offerings
- Oracle Corp. - Segment focus
- SWOT
- 14.14 Stylumia Intelligence Technology Pvt Ltd
- Stylumia Intelligence Technology Pvt Ltd - Overview
- Stylumia Intelligence Technology Pvt Ltd - Product / Service
- Stylumia Intelligence Technology Pvt Ltd - Key offerings
- SWOT
- 14.15 Teradata Corp.
- Teradata Corp. - Overview
- Teradata Corp. - Business segments
- Teradata Corp. - Key news
- Teradata Corp. - Key offerings
- Teradata Corp. - Segment focus
- SWOT
- 14.16 Walmart Inc.
- Walmart Inc. - Overview
- Walmart Inc. - Business segments
- Walmart Inc. - Key news
- Walmart Inc. - Key offerings
- Walmart Inc. - Segment focus
- SWOT
15 Appendix
- 15.1 Scope of the report
- Market definition
- Objectives
- Notes and caveats
- 15.2 Inclusions and exclusions checklist
- Inclusions checklist
- Exclusions checklist
- 15.3 Currency conversion rates for US$
- Currency conversion rates for US$
- 15.4 Research methodology
- Research methodology
- 15.5 Data procurement
- Information sources
- 15.6 Data validation
- Data validation
- 15.7 Validation techniques employed for market sizing
- Validation techniques employed for market sizing
- 15.8 Data synthesis
- Data synthesis
- 15.9 360 degree market analysis
- 360 degree market analysis
- 15.10 List of abbreviations
- List of abbreviations
