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Artificial Intelligence (AI) In Retail Market

Artificial Intelligence (AI) In Retail Market Size, Share & Segmentation by Technology (Neural networks, Deep learning, Facial recognition, Natural language processing, Voice assistance), by Solution (Visual Search, Virtual Assistant, Product Recommendation and Planning, Price Optimization, Customer Relationship Management, Others), by components (Solutions and Services), by Deployment (Premise and Cloud), by Regions and Global Market Forecast 2022-2028

Report Id: SNS/ICT/1335 | May 2022 | Region: Global | 130 Pages

Report Scope & Overview:

The Artificial Intelligence (AI) In Retail Market size was valued at USD3.87Bn in 2021 and is expected to reach USD 33.97Bn by 2028, and grow at a CAGR of 31.17% over the forecast period 2022-2028.

Artificial intelligence (AI) is the replication of human intellect in machines that can envision themselves as people and emulate their activities. The phrase may also refer to any machine that exhibits human-like characteristics like learning and problem-solving. The usage of algorithms is a common theme in AI. A set of unambiguous directions that a mechanical computer can follow is known as an algorithm. A complex algorithm is frequently developed on top of a foundation of smaller algorithms. More than just associating items lies at the heart of digital change in retail. It's all about turning data into insights, which guide actions that lead to more intangible business results.

Artificial Intelligence (AI) In Retail Market

The key to producing these penetrations is artificial intelligence in retail, which includes machine learning and deep learning. For retailers, this means incredible customer experiences, income opportunities, rapid innovation, and smart operations, all of which help you stand out from the competition. Retail systems are collaborating with AI to improve consumer experiences, forecasting, inventory management, and more. As a consequence, clients are connected to the appropriate items, at the right time, and in the right location. Machine vision and other AI technologies offer near-real-time intelligence to brick-and-mortar establishments. The same data might yield additional business insights when analyzed on the cloud.

Retail systems are collaborating with AI to improve consumer experiences, forecasting, inventory management, and more. Computer vision and other AI technologies offer near-real-time intelligence to brick-and-mortar establishments. When evaluated on the cloud, the same data might yield additional business insights. Intelligent display advertisements, smart shelves, infinite aisle kiosks, increased inventory control, and smart self-checkout are just a few of the AI possibilities enabled by Intel technology.

MARKET DYNAMICS:

KEY DRIVERS:

  • The progress in big data is one of the primary factors driving the growth of the artificial intelligence industry in retail.

  • Artificial intelligence-enabled products and services are being adopted in a variety of areas.

RESTRAINTS:

  • Insufficient infrastructure

  • The greater implementation expenses are associated with it.

OPPORTUNITY:

  • The importance of internet buying channels has increased as a result of the COVID-19 pandemic.

  • To take advantage of shifting trend, retailers are turning to e-commerce platforms and online marketplaces.

CHALLENGES:

  • worries about data security and privacy.

  • workers lacking in expertise.

IMPACT OF COVID-19:

Since the outbreak of this devastating epidemic, almost every business in the world has suffered a significant setback. While every business seeks strategies to reduce loss, they also need direction to guarantee that they can continue to operate effectively and smoothly in the future. On the other hand, no one knows when the epidemic will stop. To provide a flawless working atmosphere, several things need to be modified in the working pattern, and Artificial Intelligence in Retail Market Analysis is done correctly by the specialists.

Through the most attractive Artificial Intelligence in Retail Market Research Report, industry specialists have been taking care of every organization's demands. The emphasis is on mentoring them in a way that allows them to perform at their best.

MARKET ESTIMATION:

The market is divided into three categories based on technology: Natural Language Processing, Machine Learning, Deep Learning, and Others. During the forecast period, the Machine Learning and Deep Learning sector of the worldwide AI in the retail market is predicted to develop at the fastest CAGR. The rising usage of machine learning technology by online merchants to provide tailored services and improve the consumer experience is credited with the segment's rise. In recent years, technology has seen increased use throughout the world, particularly in the United States and China.

Visual Search, Virtual Assistant, Product Recommendation and Planning, Price Optimization, Customer Relationship Management, and Others are the market segments based on solutions. During the forecast period, the worldwide Artificial Intelligence in the Retail market's Product Recommendation and Planning sector is predicted to develop at the fastest CAGR. The continued usage of AI-driven suggestion generators by online retail organizations such as Amazon.com Inc. and eBay Inc. for targeted product marketing based on consumers' previous purchasing is credited with the segment's rise. In addition, as North America and APAC place a greater emphasis on digital marketing, demand for reference engines is likely to expand, propelling the market in this area even further.

The market is segmented by application into In-Store Visual Monitoring and Surveillance, Market Forecasting, Predictive Merchandising, Programmatic Advertising, and Others. During the forecast period, the Predictive Merchandising segment in the global Artificial Intelligence in the Retail market is expected to grow at the highest CAGR. The segment's rise may be ascribed to retailers' increasing demand for useful insights into customers' motivations for purchases and buying patterns, which is prompting them to turn to predictive merchandising solutions.

KEY MARKET SEGMENTS:

On The Basis of Technology:

  • Neural networks

  • Deep learning

  • Facial recognition

  • Natural language processing

  • Voice assistance

On The Basis of Solution:

  • Visual Search

  • Virtual Assistant

  • Product Recommendation and Planning

  • Price Optimization

  • Customer Relationship Management

  • Others

On The Basis of components:

  • Solutions

  • Services

On The Basis of Deployment:

  • Premise

  • Cloud

Artificial Intelligence (AI) In Retail Market

REGIONAL ANALYSIS:

North America, Europe, Asia Pacific, Middle East & Africa, and South America are the regions that make up the worldwide artificial intelligence in retail market. Because of the existence of developed economies such as the United States and Canada, North America led the worldwide artificial intelligence in retail industry with the highest share. Because of its early acceptance and deployment of artificial intelligence in retail, the United States is a prominent market in the area. Many businesses in the region have implemented AI-based solutions to improve their supply chain operations and inventories. During the forecast period, the artificial intelligence in retail market in Asia Pacific is expected to grow at a quick rate. This might be due to the region's increasing usage of AI-based products and services.

REGIONAL COVERAGE:

  • North America

    • USA

    • Canada

    • Mexico

  • Europe

    • Germany

    • UK

    • France

    • Italy

    • Spain

    • The Netherlands

    • Rest of Europe

  • Asia-Pacific

    • Japan

    • south Korea

    • China

    • India

    • Australia

    • Rest of Asia-Pacific

  • The Middle East & Africa

    • Israel

    • UAE

    • South Africa

    • Rest of Middle East & Africa

  • Latin America

    • Brazil

    • Argentina

    • Rest of Latin America

KEY PLAYERS:

Amazon.com, 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.

Artificial Intelligence (AI) In Retail Market Report Scope:
Report Attributes Details
Market Size in 2021  US$ 3.87 Bn
Market Size by 2028  US$ 33.97 Bn
CAGR   CAGR of 31.17% From 2022 to 2028
Base Year  2021
Forecast Period  2022-2028
Historical Data  2017-2020
Report Scope & Coverage Market Size, Segments Analysis, Competitive  Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook
Key Segments • by Technology (Neural networks, Deep learning, Facial recognition, Natural language processing, Voice assistance)
• by Solution (Visual Search, Virtual Assistant, Product Recommendation and Planning, Price Optimization, Customer Relationship Management, Others)
• by Components (Solutions and Services), by Deployment (Premise and Cloud)
Regional Analysis/Coverage North America (USA, Canada, Mexico), Europe
(Germany, UK, France, Italy, Spain, Netherlands,
Rest of Europe), Asia-Pacific (Japan, South Korea,
China, India, Australia, Rest of Asia-Pacific), The
Middle East & Africa (Israel, UAE, South Africa,
Rest of Middle East & Africa), Latin America (Brazil, Argentina, 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 progress in big data is one of the primary factors driving the growth of the artificial intelligence industry in retail.
• Artificial intelligence-enabled products and services are being adopted in a variety of areas.
Market Opportunities • To take advantage of shifting trend, retailers are turning to e-commerce platforms and online marketplaces.

 


Frequently Asked Questions (FAQ) :


Table of Contents

 

1. Introduction

1.1 Market Definition 

1.2 Scope

1.3 Research Assumptions

 

2. Research Methodology

 

3. Market Dynamics

3.1 Drivers

3.2 Restraints

3.3 Opportunities

3.4 Challenges 

 

4. Impact Analysis

    1. COVID 19 Impact Analysis

4.2 Impact of the Ukraine- Russia war

 

5. Value Chain Analysis

 

6. Porter’s 5 forces model

 

7. PEST Analysis

 

8. Artificial Intelligence (AI) In Retail Market Segmentation, by Technology

8.1 Neural networks

8.2 Deep learning

8.3 Facial recognition

8.4 Natural language processing

8.5 Voice assistance

 

9. Artificial Intelligence (AI) In Retail Market Segmentation, by Solution

9.1 Visual Search

9.2 Virtual Assistant

9.3 Product Recommendation and Planning

9.4 Price Optimization

9.5 Customer Relationship Management

9.6 Others

 

10. Artificial Intelligence (AI) In Retail Market Segmentation, by components

10.1 Solutions

10.2 Services

 

11. Artificial Intelligence (AI) In Retail Market Segmentation, by Deployment

11.1  Premise

 11.2 Cloud

 

12. Regional Analysis

12.1 Introduction

12.2 North America

12.2.1 USA

12.2.2 Canada

12.2.3 Mexico

12.3 Europe

12.3.1 Germany

12.3.2 UK

12.3.3 France

12.3.4 Italy

12.3.5 Spain

12.3.6 The Netherlands

12.3.7 Rest of Europe

12.4 Asia-Pacific

12.4.1 Japan

12.4.2 South Korea

12.4.3 China

12.4.4 India

12.4.5 Australia

12.4.6 Rest of Asia-Pacific

12.5 The Middle East & Africa

12.5.1 Israel

12.5.2 UAE

12.5.3 South Africa

12.5.4 Rest

12.6 Latin America

12.6.1 Brazil

12.6.2 Argentina

12.6.3 Rest of Latin America

 

13. Company Profiles

13.1 Amazon.com, Inc.

13.1.1 Financial

13.1.2 Products/ Services Offered

13.1.3 SWOT Analysis

13.1.4 The SNS view

13.2 Google LLC

13.3 IBM Corporation

13.4 Intel Corporation

13.5 Microsoft Corporation

13.6 Nvidia Corporation

13.7 Oracle Corporation

13.8 SAP SE

13.9 Salesforce.com, Inc.

13.10 BloomReach, Inc.

 

14. Competitive Landscape

14.1 Competitive Benchmarking

14.2 Market Share analysis

14.3 Recent Developments

 

15. 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.

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:

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