Edison, NJ -- (SBWIRE) -- 04/06/2020 -- Advance Market Analytics released the research report of Global AI in Fashion Market, offers a detailed overview of the factors influencing the global business scope. Global AI in Fashion Market research report shows the latest market insights with upcoming trends and breakdown of the products and services.The report provides key statistics on the market status, size, share, growth factors of the Global AI in Fashion. This Report covers the emerging player's data, including: competitive situation, sales, revenue and global market share of top manufacturers are Microsoft (United States), IBM (United States), Google (United States), AWS (United States), SAP (Germany), Facebook (United States), Adobe (United States), Oracle (United States), Catchoom (Spain), Huawei (China), Vue.ai (United States), Heuritech (France), Wide Eyes (Spain), FINDMINE (United States), Intelistyle (England) and Lily AI (United States).
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Fashion is a growing industry with economic and social implications worldwide. With the advent of modern cognitive computing technologies such as machine learning, deep learning, virtual reality, and natural language processing for analyzing huge amounts of fashion data, the impact of AI in the fashion industry is transforming. Additionally, fashion brands are using machine learning and AI for maximizing customer shopping experience and enhancing the efficiency of sales systems through intelligent process automation using predictive analytics and well-organized sales processes. Moreover, growth in the fast fashion retail industry expected to fuel the growth of AI in the fashion market during the forecasted period. According to Market Analyst at AMA, the Global AI in Fashion market may see a growth rate of 38.19%
Market Drivers
- Rising Customer Demand for Personalized Fashion Experience
- Growing Need for Automated Inventory Management in Fashion Industry
Market Trend
- Increasing Influence of Social Media on the Fashion Industry
- Growing Fast Fashion Retail Industry
Restraints
- Difficult Integration with Legacy Systems
Opportunities
- Emergence of Technologies Such As Machine Learning, Deep Learning, Natural Language Processing, and Virtual Reality in Fashion Industry
- Growing Demand from the Developing Economies
Challenges
- Lack of Awareness among End Users
The Global AI in Fashionis segmented by following Product Types:
Application (Product Recommendation, Product Search and Discovery, Supply Chain Management and Demand Forecasting, Creative Designing and Trend Forecasting, Customer Relationship Management, Virtual Assistants, Others (Fraud Detection, Fabric Waste Reduction, and Price Optimization)), Deployment Mode (Cloud, On-Premises), Category (Apparel, Accessories, Footwear, Beauty & Cosmetics, Jewelry & Watches, Others (Eyewear, Home Decor)), End-User (Fashion Designers, Fashion Stores), Component (Solution (Software Tools, Platforms), Services (Training and Consulting, System Integration and Testing, Support and Maintenance))
Region Included are: North America, Europe, Asia Pacific, Oceania, South America, Middle East & Africa
Country Level Break-Up: United States, Canada, Mexico, Brazil, Argentina, Colombia, Chile, South Africa, Nigeria, Tunisia, Morocco, Germany, United Kingdom (UK), the Netherlands, Spain, Italy, Belgium, Austria, Turkey, Russia, France, Poland, Israel, United Arab Emirates, Qatar, Saudi Arabia, China, Japan, Taiwan, South Korea, Singapore, India, Australia and New Zealand etc.
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Strategic Points Covered in Table of Content of Global AI in Fashion Market:
Chapter 1: Introduction, market driving force product Objective of Study and Research Scope the Global AI in Fashion market
Chapter 2: Exclusive Summary – the basic information of the Global AI in Fashion Market.
Chapter 3: Displayingthe Market Dynamics- Drivers, Trends and Challenges of the Global AI in Fashion
Chapter 4: Presenting the Global AI in Fashion Market Factor Analysis Porters Five Forces, Supply/Value Chain, PESTEL analysis, Market Entropy, Patent/Trademark Analysis.
Chapter 5: Displaying the by Type, End User and Region 2013-2018
Chapter 6: Evaluating the leading manufacturers of the Global AI in Fashion market which consists of its Competitive Landscape, Peer Group Analysis, BCG Matrix & Company Profile
Chapter 7: To evaluate the market by segments, by countries and by manufacturers with revenue share and sales by key countries in these various regions.
Chapter 8 & 9: Displaying the Appendix, Methodology and Data Source
Finally, Global AI in Fashion Market is a valuable source of guidance for individuals and companies.
Data Sources & Methodology
The primary sources involves the industry experts from the Global AI in Fashion Market including the management organizations, processing organizations, analytics service providers of the industry's value chain. All primary sources were interviewed to gather and authenticate qualitative & quantitative information and determine the future prospects.
In the extensive primary research process undertaken for this study, the primary sources – Postal Surveys, telephone, Online & Face-to-Face Survey were considered to obtain and verify both qualitative and quantitative aspects of this research study. When it comes to secondary sources Company's Annual reports, press Releases, Websites, Investor Presentation, Conference Call transcripts, Webinar, Journals, Regulators, National Customs and Industry Associations were given primary weight-age.
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