Facts and Factors have published a new research report titled "Artificial Intelligence in Retail Market By Type (Offline, and Online), By Technology (Natural Language Processing, Machine Learning, and Deep Learning, and Others), By Solution (Customer Relationship Management, Payment Services management, Price Optimization, Product Recommendation, and Planning, Supply chain management and Demand Planning, Virtual Assistant, Visual Search, Others ) By Service (Managed Services, and Professional Services), By Deployment Model (On-Premises, and Cloud), and By Application (In-Store Visual Monitoring and Surveillance, Location-Based Marketing, Market Forecasting, Predictive Merchandising, Programmatic Advertising, and Others): Global Industry Perspective, Comprehensive Analysis, and Forecast, 2020 - 2026".
"According to the research report, the global Artificial Intelligence in Retail Market was estimated at USD 2.7 Billion in 2019 and is expected to reach USD 20.05 Billion by 2026. The global Artificial Intelligence in Retail Market is expected to grow at a compound annual growth rate (CAGR) of 39% from 2020 to 2026".
Digitalization in retail is much more than just linking objects. It's about turning data into observations that guide decisions that produce better market results. Retail AI--including machine learning and deep learning--is crucial to developing these insights. This offers retailers incredible consumer interactions, revenue growth prospects, accelerated innovation, and insightful companies, all allowing them to separate themselves from their rivals. In some parts of its operations, several retailers are now using AI. They may automate marketing practices with AI in CRM applications, or predictive analytics to determine which consumers are likely to purchase those goods. The cloud helps AI workloads store and process data volumes from a wide range of sources. For eg, demand prediction and online product reviews are demands for retail cloud workloads.
But operating AI provides benefits in the store itself. The edge retail computing serves as a mechanism for insight, aggregation, or transformation into useful, operational knowledge of vast quantities of raw data. Imagine inventory robotics restoring shelves; digital signs adjusting to the audience; and customer monitoring sensors to alert cross-selling and upselling opportunities. The traction on brick and mortar is a special kind of AI in detail, known as computer vision. And it opens the way for new instances of market usage by consumer engagement, predicting demand, product control, and more.
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Industry Major Market Players
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Global Artificial Intelligence in Retail Market: Growth Factors
Over the years the idea of virtual test rooms has become more common, allowing shoppers to play with their equipment through a tactile GUI. The combination of artificial intelligence and digital mirrors allows shoppers to test and wear diverse dresses, accessories, goggles, and other beauty items. The real-time simulation for computer dressing solutions is delivered in conjunction with other advanced technology, such as virtual realities, artificial intelligence, or visual computing. The technology strengthens both online and offline Shopping's user engagement and loyalty. The need for a digital trial room is expected to increase because of its secure shopping experience since the global COVID-19 pandemic.
Each retail corporation tries to consolidate its loyal client base to remain on the market today in the retained sector. Providing each consumer with improved customized service is a prime tactic for leading brands. Chabot's operated by AI is one of the innovations that can effectively promote consumer interaction. Popularity is also likely to increase in all markets for both online and in-store catboats. The framework lets retailers handle consumer shopping requests with AI-configured chatbots without including humans. Al-Driven Chatbots' fast, customized and on-demand support and feedback add to the consumer experience while favoring the retail sector as a whole.
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Growing awareness about AI and big data & analytics across the globe is driving the market
Different well-known retailers across the globe face rising costs, unhappy buyers, revenue declines, and rivalry. In order to increase organizational performance and consumer interactions, retailers have adopted technical tools. Various retail industries such as stock management, supply chain management, promotions, and branding, as well as customer relations, have considerable technical processing capacity and allow retailers to increase overall efficiency and profitability.
Global Artificial Intelligence in Retail Market: Segmentation
Global Artificial Intelligence in Retail market is segmented into four notable segments which are type, solution, technology, deployment model, service, and application.
Based on type the market is classified into offline, and online. Based on technology the market is classified as machine learning & deep learning, natural language processing, and others. Based on Solution the market is further classified as Visual Search, Payment Services management, Customer Relationship Management, Product Recommendation & Planning, Price Optimization, Virtual Assistant, Supply chain management & Demand Planning, and Others. Based on service the market is further classified as managed services, and professional services. Based on the deployment model the market is further classified as on-premises and cloud. Based on Application the market is further classified as Location-Based Marketing, In-Store Visual Monitoring & Surveillance, Market Forecasting, Programmatic Advertising, Predictive Merchandising, and Others.
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Asia Pacific Region Projected To Be Fastest Growing in Artificial Intelligence in Retail Market Growth
The Asia Pacific is expected to dominate the market with the largest market share mainly because of the presence of several developed economies, such as China and Canada, focusing on enhancing the existing solutions in the retail space. North America hosts the primary AI solution providers and is an early adopter of AI technology.
Many retailers in this region have deployed AI-based solutions to optimize their supply chain operations and inventory. AI is helping retailers in managing and maintaining their customers and understanding the buying patterns of the consumers. To engage customers and improve sales turnover, AI technologies are being adopted by both online and offline retail businesses.
Browse the full "Artificial Intelligence in Retail Market By Type (Offline, and Online), By Technology (Natural Language Processing, Machine Learning and Deep Learning, and Others), By Solution (Customer Relationship Management, Payment Services management, Price Optimization, Product Recommendation, and Planning, Supply chain management and Demand Planning, Virtual Assistant, Visual Search, Others ) By Service (Managed Services, and Professional Services), By Deployment Model (On-Premises, and Cloud), and By Application (In-Store Visual Monitoring and Surveillance, Location-Based Marketing, Market Forecasting, Predictive Merchandising, Programmatic Advertising, and Others): Global Industry Perspective, Comprehensive Analysis, and Forecast, 2020 - 2026" report at https://www.fnfresearch.com/artificial-intelligence-in-retail-market
The global Artificial Intelligence in Retail market is segmented as follows:
-- Natural Language Processing
-- Machine Learning and Deep Learning
-- Customer Relationship Management
-- Payment Services management
-- Price Optimization
-- Product Recommendation and Planning
-- Supply chain management and Demand Planning
-- Virtual Assistant
-- Visual Search
-- Managed Services
-- Professional Services
By Deployment Model:
-- In-Store Visual Monitoring and Surveillance
-- Location-Based Marketing
-- Market Forecasting
-- Predictive Merchandising
-- Programmatic Advertising
KEY REPORT POINTERS & HIGHLIGHTS:
-- Statistically Validated Analysis of Historical, Current, and Projected Industry Trends with Authenticated Market Sizes Information and Data in terms of Value and Volume, wherever applicable
-- Direct and Indirect Factors that Impacted the Industry as well Projected Rationales expected to affect the industry going forward
-- Micro, Meso, Macro, and In-Depth Analysis of Technically relevant and Commercially viable Segments and Sub-segments of the Market
-- Historical and Projected Company / Vendor / OEM / Supplier Market Shares, Competitive Landscape, and Player Positioning Data
-- Historical and Current Demand (Consumption) and Supply (Production) Scenarios as well as Projected Supply-Demand Scenario Analysis
-- Detailed List of Key Buyers and End-Users (Consumers) analyzed as per Regions and Applications
-- Value Chain and Supply Chain Analysis along with Horizontal and Vertical Integration Scenarios
-- Manufacturing and Production Cost Structure Analysis including Labor Cost, Raw Material Expenses, and Other Manufacturing Expenses, wherever relevant
-- Overview of Key Marketing Strategies and Key Sales Channels Adopted in the Market
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