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Artificial Intelligence (AI) In Retail Market Report Scope & Overview:

Artificial Intelligence (AI) In Retail Market,Revenue Analysis

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Artificial Intelligence (AI) In Retail Market size was valued at USD 7.11 Bn in 2023 and is expected to reach USD 88.77 Bn by 2032 and grow at a CAGR of 32.38 % over the forecast period 2024-2032.

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

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.

Artificial-Intelligence-AI-In-Retail-Market-By-Technology.

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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.

Artificial-Intelligence-AI-In-Retail-Market-Regional-Analysis-2023

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.

Recent Development

  • In January 2023, Microsoft joined forces with AiFi, a promising tech start-up, to introduce Smart Store Analytics. This groundbreaking cloud-based tracking service is specifically designed for cashier-less outlets, empowering retailers with invaluable shopper and operational analytics.

  • In January 2023, EY, a leading Fintech company, unveiled the EY Retail Intelligence solution, leveraging the power of Microsoft Cloud. This cutting-edge solution aims to revolutionize the shopping experience by providing clients with a secure and time-saving platform. By harnessing Microsoft Cloud for Retail and its advanced technologies such as Artificial Intelligence (AI), analytics, and image recognition, EY Retail Intelligence delivers unparalleled insights to its users.

  • In January 2023 witnessed an exciting collaboration between Perfect and Valmont, a renowned luxury cosmetics brand. This partnership revolves around an AI-focused beauty initiative, combining Valmont's expertise in skincare with Perfect's state-of-the-art artificial intelligence solution. The result is a comprehensive skin analysis offering that caters to the discerning needs of consumers.

Artificial Intelligence (AI) In Retail Market Report Scope:

Report Attributes Details
Market Size in 2024  USD 7.11 Bn
Market Size by 2032  USD 88.77 Bn
CAGR   CAGR of 32.38 % From 2024 to 2032
Base Year  2023
Forecast Period  2024-2032
Historical Data  2020-2022
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. 

 

Frequently Asked Questions

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:  

  • 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.

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.

Secondary Research

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.

Primary Research

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.

Data Bank Validation

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.


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