Artificial Intelligence in Retail Market Is Expected To Reach around USD 45.74 Billion by 2030, Grow at a CAGR Of 18.45% during Forecast Period 2023 To 2030 | Data By Contrive Datum Insights Pvt Ltd.
According to a market research study published by Contrive Datum Insights, In 2021, North America had the majority with a 38.5% revenue share.
Farmington, Jan. 19, 2023 (GLOBE NEWSWIRE) -- The Global Artificial Intelligence (AI) In Retail Market Size Accounted For USD 8.41 Billion In 2022 And It Is Projected To Attain Around USD 45.74 Billion By 2030, Poised To Grow at a CAGR Of 18.45% During The Forecast Period 2023 To 2030. The growth is being driven by things like the increasing number of people who use the internet, smart devices, the need for surveillance and monitoring at a physical store, and government policies that encourage digitization. AI in retail is based on how businesses have been run for the past few decades. AI and analytics for big data are important parts of digital business. They can change everything, from how a business works to how a customer feels about it.
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Recent Developments:
In September 2022, Microsoft partnered with Indian global IT company Infosys. The organizations wanted to enable companies to quickly redesign customer experiences, augment systems with cloud and data, and update processes through this alliance.
In August 2022, the company introduced a new solution for personalized e-commerce product suggestions called ViSenze's Session-Based Recommendations. With the new approach, customers would get a more personalized experience without providing any personal information.
In July 2022, Intel released novel reference kits. The new solution should make it easier for data scientists and engineers to understand how AI can be implemented in diverse environments, including manufacturing, retail, healthcare, and more.
Segment Overview
By Offering Analysis:
Based on what is being sold, artificial intelligence in the retail sector can be broken down into solutions and services. The cure is taking over the market. Smart shop, digital commerce, intelligent consumer insights, smart delivery, intelligent supply chain, and other solutions are all taken into account. Because it's getting harder to keep track of all the different retail activities, new and creative automated solutions are expected to drive the retail business. With the help of the AI-based retail solution, retailers can handle logistics, supply chain operations, warehouse management, and better customer experiences. This will likely speed up the use of AI in the retail sector.
By Function Analysis:
Based on what they do, artificial intelligence in retail is divided into two groups: operations-focused and customer-facing. Focusing on operations grows a market's share of revenue. Solutions for operations are being thought about. These include Intel Movidius VPUs, Taskdesk Virtual Agents, RetailNext Store Layout, and ViSenze merchandising planning. AI is being used by retailers to improve the efficiency of their operations in areas like merchandising, logistics, supply chains, on-time delivery, and more. Effective backend management gives merchants more time to work on growing their sales and new growth projects.
By Application Analysis:
Some of the applications that make up the market are predictive analytics, in-store visual monitoring and surveillance, customer relationship management (CRM), market forecasting, inventory management, and others. This market was led by predictive analytics in 2020. Some of its most important uses are labour optimization, shelf management, store operations, and dividing people into groups based on their demographics. Retailers are using AI-based predictive analysis to learn more about how customers might behave and how the market might change in the future. The AI is also used to get analysis based on many demographics, such as region, country, culture, gender, age, and others.
By Type Analysis:
Based on how it works, artificial intelligence (AI) in retail is divided into two types: online and offline. The most money is made offline, and it is expected that this will stay the same during the projected time period. Customers want this technology because, among other things, it can help manage store operations, improve merchandising and assortment, and automate personalised product recommendations, all of which make shopping better for customers. Online is likely to grow quickly because more people are shopping online and virtually. Artificial intelligence technology is being used by retailers to improve their online customer service. ViSenze, for example, offers a number of smart e-commerce solutions, such as usability across devices, smart recommendations, discovery, and motivational SEO marketing.
By Technology Analysis:
In the retail sector, artificial intelligence is categorised using computing technologies like computer vision, machine learning, natural language processing, and others. During the time frame of the projection, natural language processing is expected to grow quickly. Businesses pay close attention to how clients act, how they feel, what kind of personality they have, and other factors in order to offer specialised and personalised services.
Regional Outlook:
With 38.5% of the revenue in 2021, North America had the most. Given how much money is being spent on AI projects and related research and development, there is a lot of room for the industry to grow. Regional retailers are also focusing on getting as much information as they can about their customers' preferences so they can provide better customer service.
Google Inc., Microsoft, IBM Corp., Salesforce, and Amazon Web Services are among the market leaders who use both organic and inorganic methods. For example, in January 2021, Google Cloud launched Product Discovery Solutions for retail to make online shopping more personalised.
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Scope of Report:
Report Attributes | Details |
Growth Rate | CAGR of 18.45% from 2023 to 2030. |
Revenue Forecast by 2030 | USD 45.74 Billion |
By Type | Offline, Online, Other |
By Application | Predictive Analytics, In-Store Visual Monitoring and Surveillance, Customer Relationship Management (CRM), Market Forecasting, Inventory Management, Others |
By Technology | Computer Vision, Machine Learning, Natural Language Processing, Other |
By Companies | IBM Corporation, Microsoft, SAP SE, Amazon Web Services, Oracle, Salesforce Inc., Intel, NVIDIA, Google LLC, Sentient Technology, ViSenze |
Regions and Countries Covered |
|
Base Year | 2022 |
Historical Year | 2017 to 2022 |
Forecast Year | 2023 to 2030 |
LATEST TRENDS:
E-commerce sites and virtual shops are being used by more and more people every day. People can search for new products in new ways today, such as by using images, videos, and their voices. Visual search makes the most of its features by processing queries and mining the metadata. This is done with the help of artificial intelligence. AI is used by the visual search engine to analyse, track, and predict growing shopping trends. This makes shopping better and keeps shoppers interested.
According to the 2020 report from Syte Visual Conception Ltd., almost 80% of shoppers start their shopping with a visual search. So, retailers who want to improve customer service and boost sales must now have AI-based search engines. AI-powered search features also help retailers learn important things about consumer trends and make good business decisions. In the next few years, retailers can expect to get a lot of information and growth opportunities from search engines that use AI.
DRIVING FACTORS:
Because they are so good at helping customers, chatbots that use artificial intelligence are becoming very popular in the retail industry. Chatbot helps customers have a better experience by giving them answers that are specific to them and fit their needs. Accenture insights found that in 2018, 91% of customers were more likely to buy from brands that gave them personalised recommendations and services.
The AI chatbots can understand what people say with the help of natural language processing (NLP) and machine learning (ML). These technologies let you know what customers want right now. It also helps the chatbot understand how customers feel and act, which helps the chatbot answer customer questions and build relationships. For example, Levi's has a platform called Levi's Virtual Stylist, which is a chatbot that makes suggestions to the customer. The bot asks users for basic information like size, fit, material, and even preferred brands so it can make quick suggestions. So, it is expected that the AI-powered chatbot will make AI more popular in the retail industry.
Key Segments Covered:
Top Market Players:
IBM Corporation, Microsoft, SAP SE, Amazon Web Services, Oracle, Salesforce Inc., Intel, NVIDIA, Google LLC, Sentient Technology, ViSenze, and others.
By Offering
Solution
Service
By Function
Operations-Focused
Customer-Facing
Other
By Type
Offline
Online
Other
By Application
Predictive Analytics
In-Store Visual Monitoring and Surveillance
Customer Relationship Management (CRM)
Market Forecasting
Inventory Management
Others
By Technology
Computer Vision
Machine Learning
Natural Language Processing
Other
Regions and Countries Covered
North America: (US, Canada, Mexico, Rest of North America)
Europe: (Germany, France, Italy, Spain, UK, Nordic Countries, Benelux Union, Rest of Europe)
Asia-Pacific: (Japan, China, India, Australia, South Korea, Southeast Asia, Rest of Asia-Pacific)
The Middle East & Africa: (Saudi Arabia, UAE, Egypt, South Africa, Rest of the Middle East & Africa)
Latin America: (Brazil, Argentina, Rest of Latin America)
Rest Of the World
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