Artificial Intelligence (AI) In Retail Market size was valued at USD 7.11 Bn in 2023 and is expected to reach USD 67.12 Bn by 2031 and grow at a CAGR of 32.38% over the forecast period 2024-2031.
Retail businesses are increasingly focusing on productivity to stay competitive, and automation is crucial for this. AI aids retailers by automating tasks, leading to higher profits and streamlined operations. Factors driving AI's growth in retail include the need for better in-store monitoring, increasing AI awareness, and improving user experiences. Digital transformation in retail has improved speed, efficiency, and accuracy through data analytics and IoT. AI's integration empowers retailers with valuable data for operational enhancements and new opportunities, vital for success in today's competitive market. a growing need for superior surveillance and monitoring in physical stores. the awareness and application of AI in retail are increasing, leading to enhanced user experiences and improved productivity. Return on Investment (ROI), inventory accuracy, and supply chain optimization are also important factors contributing to this market's growth.
DROC
Drivers
The Use of AI-powered chatbots for Enhanced Customer Experience Driving Market Growth.
The ongoing investment in AI technology by prominent retail companies, the widespread adoption of AI in the retail sector.
Government policies are playing a significant role in driving the digitization process.
The retail industry is witnessing a surge in the adoption of AI-powered chatbot assistance, thanks to its highly efficient customer service capabilities. These chatbots provide dedicated and personalized responses to customers, elevating their overall experience. An excellent example of this is upliance.ai, a smart appliances brand that integrated ChatGPT into its products in May 2023. Their smart cooking assistant, DelishUp, revolutionized the cooking process by automating it. Furthermore, upliance.ai has plans to expand its product line to include home appliances, solidifying its position as a leader in Artificial Intelligence within the retail industry. These technologies provide real-time insights into customer preferences and enable the chatbot to understand customer sentiments and behaviour patterns. This understanding allows the chatbot to respond effectively to customer queries and build strong relationships. Levi's, for instance, has implemented a chatbot platform called Levi's Virtual Stylist, which offers personalized recommendations to customers. By collecting basic details such as size, fit, material, and preferred brands, the chatbot quickly provides tailored suggestions. As a result, the AI-driven chatbot is expected to fuel the growth of artificial intelligence in the retail market.
Restrains
Limitations in Infrastructure AI Adoption in the Retail Sector
The significant challenge that comes with higher implementation costs.
Prominent retail brands are constantly investing in cutting-edge technologies to elevate customer engagement. However, various factors are poised to impede market growth. While industry giants like Walmart have successfully integrated AI technology into their in-store operations and online platforms, startups and small to medium-sized enterprises face challenges in embracing this technology due to inadequate infrastructure and technical expertise. According to insights from IBM's cloud-data service, 37% of respondents identified a lack of AI expertise as a significant obstacle to implementing such technology. Additionally, the substantial costs associated with implementing AI in retail solutions pose a major barrier for smaller retailers, further limiting its adoption.
Opportunities
The number of internet users is constantly rising, along with the proliferation of smart devices.
This surge in connectivity has led to an increased demand for surveillance and monitoring in physical stores.
Challenges
Concerns regarding data security and privacy have become increasingly prevalent in recent times.
There is a noticeable deficiency in the expertise of workers in this field.
Impact of Russia-Ukraine War:
The Russia-Ukraine conflict has significantly disrupted global supply chains, affecting the retail sector. With supply shortages and price increases, retailers are struggling to fulfill customer demands. The uncertain market conditions are prompting cautious investment strategies and strategic planning among retail businesses. Many retailers are encountering difficulties in sourcing products and are compelled to adjust pricing strategies accordingly. These economic challenges could potentially hinder the growth of the retail industry, impacting consumer confidence and spending habits.
Impact of Economic Downturn:
Economic downturns adversely affect AI in the retail market. Reduced consumer spending leads to lower demand for AI-powered solutions. Companies may cut back on technology investments, impacting innovation and adoption of AI in retail operations. Cost-cutting measures could also slow down AI implementation projects. Overall, economic downturns create challenges for AI integration in the retail sector, affecting its growth and development.
KEY MARKET SEGMENTS:
By Offering
Solution
Product Recommendation and Planning
Customer Relationship Management
Visual Search
Virtual Assistant
Price Optimization
Payment Services management
Supply chain management and Demand Planning
Others
Service
Professional Services
Managed Services
The solution segment holds the largest market share at 69.5%, driven by innovations addressing retail's operational challenges. These technologies focus on automation, improving warehouse management, streamlining supply chains, and enhancing consumer experiences. Software introductions have particularly fueled this segment's growth. Services are poised for significant growth due to the rising demand for managed solutions that boost operational efficiency, accuracy, and productivity. As AI adoption increases, there's a surge in demand for services facilitating smart functions, revenue growth, innovation, and error reduction in retail operations.
By Type
Online
Offline
By Technology
Computer Vision
Machine Learning
Others
The machine learning segment dominated the market, accounting for a revenue share of 31%. Machine learning is a powerful tool that leverages data to provide personalized experiences to consumers. It greatly enhances supply chain systems and demand forecasts, thereby improving inventory efficiency for retail vendors. Amazon Inc.'s Amazon SageMaker is a prime example of a fully integrated service that utilizes machine learning techniques for a wide range of applications, from predictive analytics to enhancing the consumer experience.
Natural language processing (NLP) is expected to experience rapid growth throughout the forecast period. The increasing demand for AI-driven chatbots and the exponential growth of data analysis will drive advancements in NLP. NLP-powered chatbots, including those with mobile interfaces and touchscreen capabilities, will revolutionize the customer experience by fostering interactivity. Additionally, NLP can be utilized for sentiment analysis, enabling businesses to assess call center interactions, customer messages, social media posts, and online reviews.
By Function
Operations-Focused
Customer-Facing
By Application
Predictive Analytics
In-Store Visual Monitoring and Surveillance
Customer Relationship Management (CRM)
Market Forecasting
Inventory Management
Others
The retail industry is experiencing a significant shift in customer behavior, prompting the adoption of AI in various applications, The predictive analytics emerged as the dominant segment. This powerful tool enables retailers to leverage demographic segmentation, store operations, shelf management, inventory management, labor optimization, and more to gain valuable insights into future market opportunities and customer behaviour. By utilizing AI, retailers can also obtain real-time analysis of different locations, countries, cultures, gender, age, and other demographics.
The customer relationship management segment is expected to witness rapid growth due to the increasing demand for enhanced customer engagement. AI-driven virtual assistance, chatbots, search engines, and other technologies enable retailers to establish and maintain strong customer relationships and foster loyalty. Additionally, the demand for AI in market forecasting is gaining traction as customer buying behavior becomes more uncertain and rapidly changing.
Regional analysis
North America dominates the Market holding a global revenue share of more than 36%, with retailers in the region focusing on extracting customer data to enhance customer service efficiency. The country is also experiencing notable growth in startups and small enterprises due to the increasing demand for AI.
Asia Pacific is expected to grow with a rapid CAGR during the forecast period, primarily due to extensive digitalization. For example, China has secured a 24% share of AI investments in its commerce and retail industry, with investments. India is also anticipated to register the highest compound annual growth rate (CAGR) due to the high demand for automation tools to enhance decision-making capabilities and operations.
Europe holds the second-largest market share, The various retailers in these sectors cosmetics, fashion, and apparel are actively investing in advanced technologies to Improve customer experience. This is projected to drive the demand for artificial intelligence in the retail industry.
KEY PLAYERS
The Major players are Amazon, Inc., Google LLC, IBM Corporation, Intel Corporation, Microsoft Corporation, Nvidia Corporation, Oracle Corporation, SAP SE, Salesforce.com, Inc., and BloomReach, Inc. are among the key participants in this sector, as are other local and regional businesses.
| Report Attributes | Details |
| Market Size in 2024 | US$ 7.11 Bn |
| Market Size by 2031 | US$ 67.12 Bn |
| CAGR | CAGR of 32.38 % From 2024 to 2031 |
| Base Year | 2022 |
| Forecast Period | 2024-2031 |
| Historical Data | 2020-2021 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segments | • By Offering (Solution {Product Recommendation and Planning, Customer Relationship Management, Visual Search, Virtual Assistant, Price Optimization, Payment Services management, Supply chain management and Demand Planning, Others}, Service {Professional Services, Managed Services}) • By Type (Online, Offline) • By Technology (Computer Vision, Machine Learning, Natural Language Processing, Others) |
| Regional Analysis/Coverage | North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe] Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]), Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia, Rest of Latin America) |
| Company Profiles | Amazon.com, Inc., Google LLC, IBM Corporation, Intel Corporation, Microsoft Corporation, Nvidia Corporation, Oracle Corporation, SAP SE, Salesforce.com, Inc., and BloomReach, Inc. |
| Key Drivers | • The Use of AI-powered chatbots for Enhanced Customer Experience Driving Market Growth. • The ongoing investment in AI technology by prominent retail companies, the widespread adoption of AI in the retail sector. |
| Market Opportunities | • The number of internet users is constantly rising, along with the proliferation of smart devices. • This surge in connectivity has led to an increased demand for surveillance and monitoring in physical stores. |
Ans. The Compound Annual Growth rate for Artificial Intelligence (AI) In Retail Market over the forecast period is 32.38%.
Ans. The projected market size for Artificial Intelligence (AI) In Retail Market is USD 67.12 Billion by 2031.
Ans: The North American region dominates the Artificial Intelligence (AI) In Retail market.
Ans:
Ans: Yes, you can ask for the customization as per your business requirement.
TABLE OF CONTENTS
1. Introduction
1.1 Market Definition
1.2 Scope
1.3 Research Assumptions
2. Industry Flowchart
3. Research Methodology
4. Market Dynamics
4.1 Drivers
4.2 Restraints
4.3 Opportunities
4.4 Challenges
5. Impact Analysis
5.1 Impact of Russia-Ukraine Crisis
5.2 Impact of Economic Slowdown on Major Countries
5.2.1 Introduction
5.2.2 United States
5.2.3 Canada
5.2.4 Germany
5.2.5 France
5.2.6 UK
5.2.7 China
5.2.8 Japan
5.2.9 South Korea
5.2.10 India
6. Value Chain Analysis
7. Porter’s 5 Forces Model
8. Pest Analysis
9. Artificial Intelligence (AI) In Retail Market Segmentation, By Offering
9.1 Introduction
9.2 Trend Analysis
9.3 Solution
9.3.1 Product Recommendation and Planning
9.3.2 Customer Relationship Management
9.3.3 Visual Search
9.3.4 Virtual Assistant
9.3.5 Price Optimization
9.3.6 Payment Services management
9.3.7 Supply chain management and Demand Planning
9.3.9 Others
9.4 Service
9.4.1 Professional Services
9.4.2 Managed Services
10. Artificial Intelligence (AI) In Retail Market Segmentation, By Type
10.1 Introduction
10.2 Trend Analysis
10.3 Online
10.4 Offline
11. Artificial Intelligence (AI) In Retail Market Segmentation, By Technology
11.1 Introduction
11.2 Trend Analysis
11.3 Computer Vision
11.4 Machine Learning
11.5 Natural Language Processing
11.6 Others
12. Artificial Intelligence (AI) In Retail Market Segmentation, By Function
12.1 Introduction
12.2 Trend Analysis
12.3 Operations-Focused
12.4 Customer-Facing
13. Artificial Intelligence (AI) In Retail Market Segmentation, By Application
13.1 Introduction
13.2 Trend Analysis
13.3 Predictive Analytics
13.4 In-Store Visual Monitoring and Surveillance
13.5 Customer Relationship Management (CRM)
13.6 Market Forecasting
13.7 Inventory Management
13.8 Others
14. Regional Analysis
14.1 Introduction
14.2 North America
14.2.1 Trend Analysis
14.2.2 North America Artificial Intelligence (AI) In Retail Market By Country
14.2.3 North America Artificial Intelligence (AI) In Retail Market By Offering
14.2.4 North America Artificial Intelligence (AI) In Retail Market By Type
14.2.5 North America Artificial Intelligence (AI) In Retail Market By Technology
14.2.6 North America Artificial Intelligence (AI) In Retail Market, By Function
14.2.7 North America Artificial Intelligence (AI) In Retail Market, By Application
14.2.8 USA
14.2.8.1 USA Artificial Intelligence (AI) In Retail Market By Offering
14.2.8.2 USA Artificial Intelligence (AI) In Retail Market By Type
14.2.8.3 USA Artificial Intelligence (AI) In Retail Market By Technology
14.2.8.4 USA Artificial Intelligence (AI) In Retail Market, By Function
14.2.8.5 USA Artificial Intelligence (AI) In Retail Market, By Application
14.2.9 Canada
14.2.9.1 Canada Artificial Intelligence (AI) In Retail Market By Offering
14.2.9.2 Canada Artificial Intelligence (AI) In Retail Market By Type
14.2.9.3 Canada Artificial Intelligence (AI) In Retail Market By Technology
14.2.9.4 Canada Artificial Intelligence (AI) In Retail Market, By Function
14.2.9.5 Canada Artificial Intelligence (AI) In Retail Market, By Application
14.2.10 Mexico
14.2.10.1 Mexico Artificial Intelligence (AI) In Retail Market By Offering
14.2.10.2 Mexico Artificial Intelligence (AI) In Retail Market By Type
14.2.10.3 Mexico Artificial Intelligence (AI) In Retail Market By Technology
14.2.10.4 Mexico Artificial Intelligence (AI) In Retail Market, By Function
14.2.10.5 Mexico Artificial Intelligence (AI) In Retail Market, By Application
14.3 Europe
14.3.1 Trend Analysis
14.3.2 Eastern Europe
14.3.2.1 Eastern Europe Artificial Intelligence (AI) In Retail Market By Country
14.3.2.2 Eastern Europe Artificial Intelligence (AI) In Retail Market By Offering
14.3.2.3 Eastern Europe Artificial Intelligence (AI) In Retail Market By Type
14.3.2.4 Eastern Europe Artificial Intelligence (AI) In Retail Market By Technology
14.3.2.5 Eastern Europe Artificial Intelligence (AI) In Retail Market By Function
14.3.2.6 Eastern Europe Artificial Intelligence (AI) In Retail Market, By Application
14.3.2.7 Poland
14.3.2.7.1 Poland Artificial Intelligence (AI) In Retail Market By Offering
14.3.2.7.2 Poland Artificial Intelligence (AI) In Retail Market By Type
14.3.2.7.3 Poland Artificial Intelligence (AI) In Retail Market By Technology
14.3.2.7.4 Poland Artificial Intelligence (AI) In Retail Market By Function
14.3.2.7.5 Poland Artificial Intelligence (AI) In Retail Market, By Application
14.3.2.8 Romania
14.3.2.8.1 Romania Artificial Intelligence (AI) In Retail Market By Offering
14.3.2.8.2 Romania Artificial Intelligence (AI) In Retail Market By Type
14.3.2.8.3 Romania Artificial Intelligence (AI) In Retail Market By Technology
14.3.2.8.4 Romania Artificial Intelligence (AI) In Retail Market By Function
14.3.2.8.5 Romania Artificial Intelligence (AI) In Retail Market, By Application
14.3.2.9 Hungary
14.3.2.9.1 Hungary Artificial Intelligence (AI) In Retail Market By Offering
14.3.2.9.2 Hungary Artificial Intelligence (AI) In Retail Market By Type
14.3.2.9.3 Hungary Artificial Intelligence (AI) In Retail Market By Technology
14.3.2.9.4 Hungary Artificial Intelligence (AI) In Retail Market By Function
14.3.2.9.5 Hungary Artificial Intelligence (AI) In Retail Market, By Application
14.3.2.10 Turkey
14.3.2.10.1 Turkey Artificial Intelligence (AI) In Retail Market By Offering
14.3.2.10.2 Turkey Artificial Intelligence (AI) In Retail Market By Type
14.3.2.10.3 Turkey Artificial Intelligence (AI) In Retail Market By Technology
14.3.2.10.4 Turkey Artificial Intelligence (AI) In Retail Market By Function
14.3.2.10.5 Turkey Artificial Intelligence (AI) In Retail Market, By Application
14.3.2.11 Rest of Eastern Europe
14.3.2.11.1 Rest of Eastern Europe Artificial Intelligence (AI) In Retail Market By Offering
14.3.2.11.2 Rest of Eastern Europe Artificial Intelligence (AI) In Retail Market By Type
14.3.2.11.3 Rest of Eastern Europe Artificial Intelligence (AI) In Retail Market By Technology
14.3.2.11.4 Rest of Eastern Europe Artificial Intelligence (AI) In Retail Market By Function
14.3.2.11.5 Rest of Eastern Europe Artificial Intelligence (AI) In Retail Market, By Application
14.3.3 Western Europe
14.3.3.1 Western Europe Artificial Intelligence (AI) In Retail Market By Country
14.3.3.2 Western Europe Artificial Intelligence (AI) In Retail Market By Offering
14.3.3.3 Western Europe Artificial Intelligence (AI) In Retail Market By Type
14.3.3.4 Western Europe Artificial Intelligence (AI) In Retail Market By Technology
14.3.3.5 Western Europe Artificial Intelligence (AI) In Retail Market By Function
14.3.3.6 Western Europe Artificial Intelligence (AI) In Retail Market, By Application
14.3.3.7 Germany
14.3.3.7.1 Germany Artificial Intelligence (AI) In Retail Market By Offering
14.3.3.7.2 Germany Artificial Intelligence (AI) In Retail Market By Type
14.3.3.7.3 Germany Artificial Intelligence (AI) In Retail Market By Technology
14.3.3.7.4 Germany Artificial Intelligence (AI) In Retail Market By Function
14.3.3.7.5 Germany Artificial Intelligence (AI) In Retail Market, By Application
14.3.3.8 France
14.3.3.8.1 France Artificial Intelligence (AI) In Retail Market By Offering
14.3.3.8.2 France Artificial Intelligence (AI) In Retail Market By Type
14.3.3.8.3 France Artificial Intelligence (AI) In Retail Market By Technology
14.3.3.8.4 France Artificial Intelligence (AI) In Retail Market By Function
14.3.3.8.5 France Artificial Intelligence (AI) In Retail Market, By Application
14.3.3.9 UK
14.3.3.9.1 UK Artificial Intelligence (AI) In Retail Market By Offering
14.3.3.9.2 UK Artificial Intelligence (AI) In Retail Market By Type
14.3.3.9.3 UK Artificial Intelligence (AI) In Retail Market By Technology
14.3.3.9.4 UK Artificial Intelligence (AI) In Retail Market By Function
14.3.3.9.5 UK Artificial Intelligence (AI) In Retail Market, By Application
14.3.3.10 Italy
14.3.3.10.1 Italy Artificial Intelligence (AI) In Retail Market By Offering
14.3.3.10.2 Italy Artificial Intelligence (AI) In Retail Market By Type
14.3.3.10.3 Italy Artificial Intelligence (AI) In Retail Market By Technology
14.3.3.10.4 Italy Artificial Intelligence (AI) In Retail Market By Function
14.3.3.10.5 Italy Artificial Intelligence (AI) In Retail Market, By Application
14.3.3.11 Spain
14.3.3.11.1 Spain Artificial Intelligence (AI) In Retail Market By Offering
14.3.3.11.2 Spain Artificial Intelligence (AI) In Retail Market By Type
14.3.3.11.3 Spain Artificial Intelligence (AI) In Retail Market By Technology
14.3.3.11.4 Spain Artificial Intelligence (AI) In Retail Market By Function
14.3.3.11.5 Spain Artificial Intelligence (AI) In Retail Market, By Application
14.3.3.12 Netherlands
14.3.3.12.1 Netherlands Artificial Intelligence (AI) In Retail Market By Offering
14.3.3.12.2 Netherlands Artificial Intelligence (AI) In Retail Market By Type
14.3.3.12.3 Netherlands Artificial Intelligence (AI) In Retail Market By Technology
14.3.3.12.4 Netherlands Artificial Intelligence (AI) In Retail Market By Function
14.3.3.12.5 Netherlands Artificial Intelligence (AI) In Retail Market, By Application
14.3.3.13 Switzerland
14.3.3.13.1 Switzerland Artificial Intelligence (AI) In Retail Market By Offering
14.3.3.13.2 Switzerland Artificial Intelligence (AI) In Retail Market By Type
14.3.3.13.3 Switzerland Artificial Intelligence (AI) In Retail Market By Technology
14.3.3.13.4 Switzerland Artificial Intelligence (AI) In Retail Market By Function
14.3.3.13.5 Switzerland Artificial Intelligence (AI) In Retail Market, By Application
14.3.3.14 Austria
14.3.3.14.1 Austria Artificial Intelligence (AI) In Retail Market By Offering
14.3.3.14.2 Austria Artificial Intelligence (AI) In Retail Market By Type
14.3.3.14.3 Austria Artificial Intelligence (AI) In Retail Market By Technology
14.3.3.14.4 Austria Artificial Intelligence (AI) In Retail Market By Function
14.3.3.14.5 Austria Artificial Intelligence (AI) In Retail Market, By Application
14.3.3.15 Rest of Western Europe
14.3.3.15.1 Rest of Western Europe Artificial Intelligence (AI) In Retail Market By Offering
14.3.3.15.2 Rest of Western Europe Artificial Intelligence (AI) In Retail Market By Type
14.3.3.15.3 Rest of Western Europe Artificial Intelligence (AI) In Retail Market By Technology
14.3.3.15.4 Rest of Western Europe Artificial Intelligence (AI) In Retail Market By Function
14.3.3.15.5 Rest of Western Europe Artificial Intelligence (AI) In Retail Market, By Application
14.4 Asia-Pacific
14.4.1 Trend Analysis
14.4.2 Asia-Pacific Artificial Intelligence (AI) In Retail Market By country
14.4.3 Asia-Pacific Artificial Intelligence (AI) In Retail Market By Offering
14.4.4 Asia-Pacific Artificial Intelligence (AI) In Retail Market By Type
14.4.5 Asia-Pacific Artificial Intelligence (AI) In Retail Market By Technology
14.4.6 Asia-Pacific Artificial Intelligence (AI) In Retail Market By Function
14.4.7 Asia-Pacific Artificial Intelligence (AI) In Retail Market, By Application
14.4.8 China
14.4.8.1 China Artificial Intelligence (AI) In Retail Market By Offering
14.4.8.2 China Artificial Intelligence (AI) In Retail Market By Type
14.4.8.3 China Artificial Intelligence (AI) In Retail Market By Technology
14.4.8.4 China Artificial Intelligence (AI) In Retail Market By Function
14.4.8.5 China Artificial Intelligence (AI) In Retail Market, By Application
14.4.9 India
14.4.9.1 India Artificial Intelligence (AI) In Retail Market By Offering
14.4.9.2 India Artificial Intelligence (AI) In Retail Market By Type
14.4.9.3 India Artificial Intelligence (AI) In Retail Market By Technology
14.4.9.4 India Artificial Intelligence (AI) In Retail Market By Function
14.4.9.5 India Artificial Intelligence (AI) In Retail Market, By Application
14.4.10 Japan
14.4.10.1 Japan Artificial Intelligence (AI) In Retail Market By Offering
14.4.10.2 Japan Artificial Intelligence (AI) In Retail Market By Type
14.4.10.3 Japan Artificial Intelligence (AI) In Retail Market By Technology
14.4.10.4 Japan Artificial Intelligence (AI) In Retail Market By Function
14.4.10.5 Japan Artificial Intelligence (AI) In Retail Market, By Application
14.4.11 South Korea
14.4.11.1 South Korea Artificial Intelligence (AI) In Retail Market By Offering
14.4.11.2 South Korea Artificial Intelligence (AI) In Retail Market By Type
14.4.11.3 South Korea Artificial Intelligence (AI) In Retail Market By Technology
14.4.11.4 South Korea Artificial Intelligence (AI) In Retail Market By Function
14.4.11.5 South Korea Artificial Intelligence (AI) In Retail Market, By Application
14.4.12 Vietnam
14.4.12.1 Vietnam Artificial Intelligence (AI) In Retail Market By Offering
14.4.12.2 Vietnam Artificial Intelligence (AI) In Retail Market By Type
14.4.12.3 Vietnam Artificial Intelligence (AI) In Retail Market By Technology
14.4.12.4 Vietnam Artificial Intelligence (AI) In Retail Market By Function
14.4.12.5 Vietnam Artificial Intelligence (AI) In Retail Market, By Application
14.4.13 Singapore
14.4.13.1 Singapore Artificial Intelligence (AI) In Retail Market By Offering
14.4.13.2 Singapore Artificial Intelligence (AI) In Retail Market By Type
14.4.13.3 Singapore Artificial Intelligence (AI) In Retail Market By Technology
14.4.13.4 Singapore Artificial Intelligence (AI) In Retail Market By Function
14.4.13.5 Singapore Artificial Intelligence (AI) In Retail Market, By Application
14.4.14 Australia
14.4.14.1 Australia Artificial Intelligence (AI) In Retail Market By Offering
14.4.14.2 Australia Artificial Intelligence (AI) In Retail Market By Type
14.4.14.3 Australia Artificial Intelligence (AI) In Retail Market By Technology
14.4.14.4 Australia Artificial Intelligence (AI) In Retail Market By Function
14.4.14.5 Australia Artificial Intelligence (AI) In Retail Market, By Application
14.4.15 Rest of Asia-Pacific
14.4.15.1 Rest of Asia-Pacific Artificial Intelligence (AI) In Retail Market By Offering
14.4.15.2 Rest of Asia-Pacific Artificial Intelligence (AI) In Retail Market By Type
14.4.15.3 Rest of Asia-Pacific Artificial Intelligence (AI) In Retail Market By Technology
14.4.15.4 Rest of Asia-Pacific Artificial Intelligence (AI) In Retail Market By Function
14.4.15.5 Rest of Asia-Pacific Artificial Intelligence (AI) In Retail Market, By Application
14.5 Middle East & Africa
14.5.1 Trend Analysis
14.5.2 Middle East
14.5.2.1 Middle East Artificial Intelligence (AI) In Retail Market By Country
14.5.2.2 Middle East Artificial Intelligence (AI) In Retail Market By Offering
14.5.2.3 Middle East Artificial Intelligence (AI) In Retail Market By Type
14.5.2.4 Middle East Artificial Intelligence (AI) In Retail Market By Technology
14.5.2.5 Middle East Artificial Intelligence (AI) In Retail Market By Function
14.5.2.6 Middle East Artificial Intelligence (AI) In Retail Market, By Application
14.5.2.7 UAE
14.5.2.7.1 UAE Artificial Intelligence (AI) In Retail Market By Offering
14.5.2.7.2 UAE Artificial Intelligence (AI) In Retail Market By Type
14.5.2.7.3 UAE Artificial Intelligence (AI) In Retail Market By Technology
14.5.2.7.4 UAE Artificial Intelligence (AI) In Retail Market By Function
14.5.2.7.5 UAE Artificial Intelligence (AI) In Retail Market, By Application
14.5.2.8 Egypt
14.5.2.8.1 Egypt Artificial Intelligence (AI) In Retail Market By Offering
14.5.2.8.2 Egypt Artificial Intelligence (AI) In Retail Market By Type
14.5.2.8.3 Egypt Artificial Intelligence (AI) In Retail Market By Technology
14.5.2.8.4 Egypt Artificial Intelligence (AI) In Retail Market By Function
14.5.2.8.5 Egypt Artificial Intelligence (AI) In Retail Market, By Application
14.5.2.9 Saudi Arabia
14.5.2.9.1 Saudi Arabia Artificial Intelligence (AI) In Retail Market By Offering
14.5.2.9.2 Saudi Arabia Artificial Intelligence (AI) In Retail Market By Type
14.5.2.9.3 Saudi Arabia Artificial Intelligence (AI) In Retail Market By Technology
14.5.2.9.4 Saudi Arabia Artificial Intelligence (AI) In Retail Market By Function
14.5.2.9.5 Saudi Arabia Artificial Intelligence (AI) In Retail Market, By Application
14.5.2.10 Qatar
14.5.2.10.1 Qatar Artificial Intelligence (AI) In Retail Market By Offering
14.5.2.10.2 Qatar Artificial Intelligence (AI) In Retail Market By Type
14.5.2.10.3 Qatar Artificial Intelligence (AI) In Retail Market By Technology
14.5.2.10.4 Qatar Artificial Intelligence (AI) In Retail Market By Function
14.5.2.10.5 Qatar Artificial Intelligence (AI) In Retail Market, By Application
14.5.2.11 Rest of Middle East
14.5.2.11.1 Rest of Middle East Artificial Intelligence (AI) In Retail Market By Offering
14.5.2.11.2 Rest of Middle East Artificial Intelligence (AI) In Retail Market By Type
14.5.2.11.3 Rest of Middle East Artificial Intelligence (AI) In Retail Market By Technology
14.5.2.11.4 Rest of Middle East Artificial Intelligence (AI) In Retail Market By Function
14.5.2.11.5 Rest of Middle East Artificial Intelligence (AI) In Retail Market, By Application
14.5.3 Africa
14.5.3.1 Africa Artificial Intelligence (AI) In Retail Market By Country
14.5.3.2 Africa Artificial Intelligence (AI) In Retail Market By Offering
14.5.3.3 Africa Artificial Intelligence (AI) In Retail Market By Type
14.5.3.4 Africa Artificial Intelligence (AI) In Retail Market By Technology
14.5.3.5 Africa Artificial Intelligence (AI) In Retail Market By Function
14.5.3.6 Africa Artificial Intelligence (AI) In Retail Market, By Application
14.5.3.7 Nigeria
14.5.3.7.1 Nigeria Artificial Intelligence (AI) In Retail Market By Offering
14.5.3.7.2 Nigeria Artificial Intelligence (AI) In Retail Market By Type
14.5.3.7.3 Nigeria Artificial Intelligence (AI) In Retail Market By Technology
14.5.3.7.4 Nigeria Artificial Intelligence (AI) In Retail Market By Function
14.5.3.7.5 Nigeria Artificial Intelligence (AI) In Retail Market, By Application
14.5.3.8 South Africa
14.5.3.8.1 South Africa Artificial Intelligence (AI) In Retail Market By Offering
14.5.3.8.2 South Africa Artificial Intelligence (AI) In Retail Market By Type
14.5.3.8.3 South Africa Artificial Intelligence (AI) In Retail Market By Technology
14.5.3.8.4 South Africa Artificial Intelligence (AI) In Retail Market By Function
14.5.3.8.5 South Africa Artificial Intelligence (AI) In Retail Market, By Application
14.5.3.9 Rest of Africa
14.5.3.9.1 Rest of Africa Artificial Intelligence (AI) In Retail Market By Offering
14.5.3.9.2 Rest of Africa Artificial Intelligence (AI) In Retail Market By Type
14.5.3.9.3 Rest of Africa Artificial Intelligence (AI) In Retail Market By Technology
14.5.3.9.4 Rest of Africa Artificial Intelligence (AI) In Retail Market By Function
14.5.3.9.5 Rest of Africa Artificial Intelligence (AI) In Retail Market, By Application
14.6 Latin America
14.6.1 Trend Analysis
14.6.2 Latin America Artificial Intelligence (AI) In Retail Market By country
14.6.3 Latin America Artificial Intelligence (AI) In Retail Market By Offering
14.6.4 Latin America Artificial Intelligence (AI) In Retail Market By Type
14.6.5 Latin America Artificial Intelligence (AI) In Retail Market By Technology
14.6.6 Latin America Artificial Intelligence (AI) In Retail Market By Function
14.6.7 Latin America Artificial Intelligence (AI) In Retail Market, By Application
14.6.8 Brazil
14.6.8.1 Brazil Artificial Intelligence (AI) In Retail Market By Offering
14.6.8.2 Brazil Artificial Intelligence (AI) In Retail Market By Type
14.6.8.3 Brazil Artificial Intelligence (AI) In Retail Market By Technology
14.6.8.4 Brazil Artificial Intelligence (AI) In Retail Market By Function
14.6.8.5 Brazil Artificial Intelligence (AI) In Retail Market, By Application
14.6.9 Argentina
14.6.9.1 Argentina Artificial Intelligence (AI) In Retail Market By Offering
14.6.9.2 Argentina Artificial Intelligence (AI) In Retail Market By Type
14.6.9.3 Argentina Artificial Intelligence (AI) In Retail Market By Technology
14.6.9.4 Argentina Artificial Intelligence (AI) In Retail Market By Function
14.6.9.5 Argentina Artificial Intelligence (AI) In Retail Market, By Application
14.6.10 Colombia
14.6.10.1 Colombia Artificial Intelligence (AI) In Retail Market By Offering
14.6.10.2 Colombia Artificial Intelligence (AI) In Retail Market By Type
14.6.10.3 Colombia Artificial Intelligence (AI) In Retail Market By Technology
14.6.10.4 Colombia Artificial Intelligence (AI) In Retail Market By Function
14.6.10.5 Colombia Artificial Intelligence (AI) In Retail Market, By Application
14.6.11 Rest of Latin America
14.6.11.1 Rest of Latin America Artificial Intelligence (AI) In Retail Market By Offering
14.6.11.2 Rest of Latin America Artificial Intelligence (AI) In Retail Market By Type
14.6.11.3 Rest of Latin America Artificial Intelligence (AI) In Retail Market By Technology
14.6.11.4 Rest of Latin America Artificial Intelligence (AI) In Retail Market By Function
14.6.11.5 Rest of Latin America Artificial Intelligence (AI) In Retail Market, By Application
15. Company Profiles
15.1 Amazon, Inc.
15.1.1 Company Overview
15.1.2 Financial
15.1.3 Products/ Services Offered
15.1.4 SWOT Analysis
15.1.5 The SNS View
15.2 Google LLC
15.2.1 Company Overview
15.2.2 Financial
15.2.3 Products/ Services Offered
15.2.4 SWOT Analysis
15.2.5 The SNS View
15.3 IBM Corporation
15.3.1 Company Overview
15.3.2 Financial
15.3.3 Products/ Services Offered
15.3.4 SWOT Analysis
15.3.5 The SNS View
15.4 Intel Corporation
15.4.1 Company Overview
15.4.2 Financial
15.4.3 Products/ Services Offered
15.4.4 SWOT Analysis
15.4.5 The SNS View
15.5 Microsoft Corporation
15.5.1 Company Overview
15.5.2 Financial
15.5.3 Products/ Services Offered
15.5.4 SWOT Analysis
15.5.5 The SNS View
15.6 Nvidia Corporation
15.6.1 Company Overview
15.6.2 Financial
15.6.3 Products/ Services Offered
15.6.4 SWOT Analysis
15.6.5 The SNS View
15.7 Oracle Corporation
15.7.1 Company Overview
15.7.2 Financial
15.7.3 Products/ Services Offered
15.7.4 SWOT Analysis
15.7.5 The SNS View
15.8 Talkdesk, Inc.
15.8.1 Company Overview
15.8.2 Financial
15.8.3 Products/ Services Offered
15.8.4 SWOT Analysis
15.8.5 The SNS View
15.9 SAP SE
15.9.1 Company Overview
15.9.2 Financial
15.9.3 Products/ Services Offered
15.9.4 SWOT Analysis
15.9.5 The SNS View
15.10 Salesforce.com, Inc.
15.10.1 Company Overview
15.10.2 Financial
15.10.3 Products/ Services Offered
15.10.4 SWOT Analysis
15.10.5 The SNS View
16. Competitive Landscape
16.1 Competitive Benchmarking
16.2 Market Share Analysis
16.3 Recent Developments
16.3.1 Industry News
16.3.2 Company News
16.3.3 Mergers & Acquisitions
17. Use Case and Best Practices
18. Conclusion
An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.
Each report that we prepare takes a timeframe of 350-400 business hours for production. Starting from the selection of titles through a couple of in-depth brain storming session to the final QC process before uploading our titles on our website we dedicate around 350 working hours. The titles are selected based on their current market cap and the foreseen CAGR and growth.
The 5 steps process:
Step 1: Secondary Research:
Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.
Step 2: Primary Research
When we talk about primary research, it is a type of study in which the researchers collect relevant data samples directly, rather than relying on previously collected data. This type of research is focused on gaining content specific facts that can be sued to solve specific problems. Since the collected data is fresh and first hand therefore it makes the study more accurate and genuine.
We at SNS Insider have divided Primary Research into 2 parts.
Part 1 wherein we interview the KOLs of major players as well as the upcoming ones across various geographic regions. This allows us to have their view over the market scenario and acts as an important tool to come closer to the accurate market numbers. As many as 45 paid and unpaid primary interviews are taken from both the demand and supply side of the industry to make sure we land at an accurate judgement and analysis of the market.
This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.
Part 2: In this part of primary research the data collected via secondary research and the part 1 of the primary research is validated with the interviews from individual consultants and subject matter experts.
Consultants are those set of people who have at least 12 years of experience and expertise within the industry whereas Subject Matter Experts are those with at least 15 years of experience behind their back within the same space. The data with the help of two main processes i.e., FGDs (Focused Group Discussions) and IDs (Individual Discussions). This gives us a 3rd party nonbiased primary view of the market scenario making it a more dependable one while collation of the data pointers.
Step 3: Data Bank Validation
Once all the information is collected via primary and secondary sources, we run that information for data validation. At our intelligence centre our research heads track a lot of information related to the market which includes the quarterly reports, the daily stock prices, and other relevant information. Our data bank server gets updated every fortnight and that is how the information which we collected using our primary and secondary information is revalidated in real time.
Step 4: QA/QC Process
After all the data collection and validation our team does a final level of quality check and quality assurance to get rid of any unwanted or undesired mistakes. This might include but not limited to getting rid of the any typos, duplication of numbers or missing of any important information. The people involved in this process include technical content writers, research heads and graphics people. Once this process is completed the title gets uploader on our platform for our clients to read it.
Step 5: Final QC/QA Process:
This is the last process and comes when the client has ordered the study. In this process a final QA/QC is done before the study is emailed to the client. Since we believe in giving our clients a good experience of our research studies, therefore, to make sure that we do not lack at our end in any way humanly possible we do a final round of quality check and then dispatch the study to the client.
The Rail Asset Management Market size was valued at USD 10.42 billion in 2022 and is projected to reach USD 16.49 billion by 2030 with a growing CAGR of 5.9% From 2023 to 2030.
The Logistics Automation Market size was USD 30.91 billion in 2022 and is expected to Reach USD 93.8 billion by 2030 with a growing CAGR of 14.9 % over the forecast period of 2023-2030.
The Task Management Software Market was worth USD 3.42 billion in 2022 and is predicted to increase to USD 9.25 billion By 2030, it is expected to expand at a CAGR of 13.25% between 2023 and 2030.
The Digital Transaction Management Market size was USD 9.92 billion in 2022 and is expected to Reach USD 62.38 billion by 2030 and grow at a CAGR of 25.84 % over the forecast period of 2023-2030.
The Communication Platform-as-a-Service (CPaaS) Market size was valued at USD 10.63 billion in 2022 and is expected to grow to USD 82.02 billion by 2030 and grow at a CAGR of 29.1 % over the forecast period of 2023-2030.
The Application Security Market size was valued at USD 8.04 Bn in 2022 and is expected to reach USD 27.85 Bn by 2030, and grow at a CAGR of 16.79 % over the forecast period 2023-2030.
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