Global AI in Fashion Market By Component (Solutions, Services); By Application (Fashion Trend Forecasting, Spotting Winning Products and Automatic Tagging, Demand Forecasting, Similar Recommendations and Visual Search, Inventory optimization across the value chain, Customer Experience Management and Retail Automation, Content Management, Localizing assortment for a store, Others); By Organization Size (Startups, Small and Medium Organizations, Large Organizations); By Category (Apparel, Accessories, Footwear, Beauty and Cosmetics, Others); By End User (Designers, Manufacturers, Retailers, Planners, Market researchers and Merchandisers, Category Heads, Store Frontend Employees/ Fashion stores, Others); By Region (North America (U.S., Canada, Mexico, Rest Of North America), Europe (France, The UK, Spain, Germany, Italy, Denmark, Finland, Iceland, Sweden, Norway, Belgium, The Netherlands, Luxembourg, Rest of Europe), Asia Pacific (China, Japan, India, New Zealand, Australia, South Korea, Southeast Asia, Indonesia, Thailand, Malaysia, Singapore, Rest of Southeast Asia, Rest of Asia Pacific, Middle East & Africa (Saudi Arabia, UAE, Egypt, Kuwait, South Africa, Rest of Middle East & Africa) Latin America (Brazil, Argentina, Rest of Latin America)) - Global Insights, Growth, Size, Comparative Analysis, Trends and Forecast, 2022 – 2030
Industry Trends
In terms of revenue, global AI in fashion market was valued at US$ 982.45 Mn in 2021 and is growing at an estimated CAGR of 40.9% over the forecast period (2022 – 2030). Artificial intelligence (AI) has revolutionized almost every industry, and this also includes the very glamorous fashion industry. The buzzing social media platforms are driving the fashion market and this is forcing this industry to extensively use latest technology to stay with the trends. By using artificial intelligence (AI), fashion companies can easily identify upcoming trends on the basis of consumer behaviour analysis.
The coronavirus pandemic that left the global economy in a shock has benefited the growth of the global AI in fashion market. Social platforms were used extensively during the COVID-19 lockdown and the use of AI helped fashion companies gauge what their customers are up to. As majority of fashion brands have virtual presence, they not only managed to sustain the pandemic but also emerged profitable.
Component Outlook
On the basis of component, the global AI in fashion market has been divided into solutions and services. The solutions segment dominates in terms of market share as majority of fashion companies are rapidly adopting artificial intelligence-based technology in an attempt to streamline their trade policies and understand the psyche of their consumers.
Application Outlook
The application segment of the global AI in fashion market has been segregated into fashion trend forecasting, spotting winning products and automatic tagging, demand forecasting, similar recommendations and visual search, inventory optimization across the value chain, customer experience management and retail automation, content management, localizing assortment for a store, and others. The AI technology is majorly being used for fashion trend forecasting. Every fashion brand wants to stay ahead of the market and AI technology helps them achieve it. This is the basic reason why this segment mints maximum money for this market.
Organization Size Outlook
On the basis of organization size, the global AI in fashion market has been bifurcated into start-ups, small and medium organizations, and large organizations. Considering the size of consumer-base and continuously increasing competition, the large organizations segment generates majority of revenue for this market.
Category Outlook
Category-wise, the global AI in fashion market is segmented into apparel, accessories, footwear, beauty and cosmetics. The beauty and cosmetics segment has been a hit since decades and is forecasted to remain the same. Due to rising social media influence, the beauty and cosmetics segment makes most of the money for the market.
End User Outlook
The end user segment of the global AI in fashion market has been divided into designers, manufacturers, retailers, planners, market researchers and merchandisers, category heads, store fronted employees/ fashion stores and others. Market researchers and merchandisers are extensively relying on AI technology, and this is exactly why this segment accounts for most of revenue generated by this market.
Region Outlook
On the basis of region, the global AI in fashion market has been divided into Latin America, Europe, North America, Middle East & Africa, Asia-Pacific. The region of North America dominates in terms of market share as technological advancement witnessed by countries like the United States and Canada is the highest. The amount of money spent for integrating tech like AI in fashion industry is at all-time high.
Global AI in Fashion Market Revenue & Forecast, (US$ Million), 2022 – 2030
Competitive Landscape
The report provides both, qualitative and quantitative research of global AI in fashion market as well as provides comprehensive insights and development methods adopted by the key contenders. The report also offers extensive research on the key players in this market and details on the competitiveness of these players. Key business strategies such as mergers and acquisitions (M&A), affiliations, collaborations, and contacts adopted by these major market participants are also recognized and analysed in the report. For each company, the report studies their global presence, competitors, service offerings and specification amongst others.
Some of the major players operating in the global AI in fashion market are listed below:
- Adobe
- AWS
- Heuritech
- IBM
- Kloud9
- Lily AI
- Mad Street Den Inc
- Microsoft
- Oracle
- SAP SE
- Stylumia Intelligence Technology Pvt Ltd
- Others
Global AI in Fashion Market
By Component
- Solutions
- Services
By Application
- Fashion trend forecasting
- Spotting winning products and Automatic Tagging
- Demand forecasting
- Similar Recommendations and Visual Search
- Inventory optimization across the value chain
- Customer Experience Management and Retail Automation
- Content Management
- Localizing assortment for a store
- Others
By Organization
- Startups
- Small and Medium Organizations
- Large Organizations
By Category
- Apparel
- Accessories
- Footwear
- Beauty and Cosmetics
- Others
By End User
- Designers
- Manufacturers
- Retailers
- Planners
- Market researchers and Merchandisers
- Category Heads
- Store Frontend Employees/ Fashion stores
- Others
By Region
- North America
- U.S
- Canada
- Mexico
- Rest of North America
- Europe
- France
- The UK
- Spain
- Germany
- Italy
- Nordic Countries
- Denmark
- Finland
- Iceland
- Sweden
- Norway
- Benelux Union
- Belgium
- The Netherlands
- Luxembourg
- Rest of Europe
- Asia Pacific
- China
- Japan
- India
- New Zealand
- Australia
- South Korea
- Southeast Asia
- Indonesia
- Thailand
- Malaysia
- Singapore
- Rest of Southeast Asia
- Rest of Asia Pacific
- Middle East and Africa
- Saudi Arabia
- UAE
- Egypt
- Kuwait
- South Africa
- Rest of Middle East & Africa
- Latin America
- Brazil
- Argentina
- Rest of Latin America
Table of Contents
1.
Market
Scope
1.1. Market Segmentation
1.2. Years Considered
1.2.1. Historic Years: 2015 - 2020
1.2.2. Base Year: 2021
1.2.3. Forecast Years: 2022 – 2030
2.
Key
Target Audiences
3.
Research
Methodology
3.1. Primary Research
3.1.1. Research Questionnaire
3.1.2. Global Percentage Breakdown
3.1.3. Primary Interviews: Key Opinion Leaders
(KOLs)
3.2. Secondary Research
3.2.1. Paid Databases
3.2.2. Secondary Sources
3.3. Market Size Estimates
3.3.1. Top-Down Approach
3.3.2. Bottom-Up Approach
3.4. Data Triangulation Methodology
3.5. Research Assumptions
4.
Recommendations
and Insights from AMI’s Perspective**
5.
Holistic
Overview of AI in Fashion Market
6.
Market
Synopsis: AI in Fashion Market
7.
AI in
Fashion Market Analysis: Qualitative Perspective
7.1. Introduction
7.1.1. Product Definition
7.1.2. Industry Development
7.2. Market Dynamics
7.2.1. Drivers
7.2.2. Restraints
7.2.3. Opportunities
7.2.4. Challenges
7.3. Trends in AI in Fashion Market
7.4. Market Determinants Radar Chart
7.5. Macro-Economic and Micro-Economic Indicators:
AI in Fashion Market
7.6. Porter’s Five Force Analysis
7.7. Impact of Covid-19 on AI in Fashion Market
8.
Global
AI in Fashion Market Analysis and Forecasts, 2022 – 2030
8.1. Overview
8.1.1. Global AI in Fashion Market Revenue (US$ Mn)
8.2. Global AI in Fashion Market Revenue (US$ Mn)
and Forecasts, By Component
8.2.1. Solutions
8.2.1.1.
Definition
8.2.1.2.
Market
Estimation and Penetration, 2015 - 2021
8.2.1.3.
Market
Forecast, 2022 – 2030
8.2.1.4.
Compound
Annual Growth Rate (CAGR)
8.2.1.5.
Regional
Bifurcation
8.2.1.5.1.
North
America
8.2.1.5.1.1. Market Estimation, 2015 - 2021
8.2.1.5.1.2. Market Forecast, 2022 – 2030
8.2.1.5.2.
Europe
8.2.1.5.2.1. Market Estimation, 2015 - 2021
8.2.1.5.2.2. Market Forecast, 2022 – 2030
8.2.1.5.3.
Asia
Pacific
8.2.1.5.3.1. Market Estimation, 2015 - 2021
8.2.1.5.3.2. Market Forecast, 2022 – 2030
8.2.1.5.4.
Middle
East and Africa
8.2.1.5.4.1. Market Estimation, 2015 - 2021
8.2.1.5.4.2. Market Forecast, 2022 – 2030
8.2.1.5.5.
Latin
America
8.2.1.5.5.1. Market Estimation, 2015 - 2021
8.2.1.5.5.2. Market Forecast, 2022 – 2030
8.2.2. Services
8.2.2.1.
Definition
8.2.2.2.
Market
Estimation and Penetration, 2015 - 2021
8.2.2.3.
Market
Forecast, 2022 – 2030
8.2.2.4.
Compound
Annual Growth Rate (CAGR)
8.2.2.5.
Regional
Bifurcation
8.2.2.5.1.
North
America
8.2.2.5.1.1. Market Estimation, 2015 - 2021
8.2.2.5.1.2. Market Forecast, 2022 – 2030
8.2.2.5.2.
Europe
8.2.2.5.2.1. Market Estimation, 2015 - 2021
8.2.2.5.2.2. Market Forecast, 2022 – 2030
8.2.2.5.3.
Asia
Pacific
8.2.2.5.3.1. Market Estimation, 2015 - 2021
8.2.2.5.3.2. Market Forecast, 2022 – 2030
8.2.2.5.4.
Middle
East and Africa
8.2.2.5.4.1. Market Estimation, 2015 - 2021
8.2.2.5.4.2. Market Forecast, 2022 – 2030
8.2.2.5.5.
Latin
America
8.2.2.5.5.1. Market Estimation, 2015 - 2021
8.2.2.5.5.2. Market Forecast, 2022 – 2030
8.3. Key Segment for Channeling Investments
8.3.1. By Component
9.
Global
AI in Fashion Market Analysis and Forecasts, 2022 – 2030
9.1. Overview
9.2. Global AI in Fashion Market Revenue (US$ Mn)
and Forecasts, By Application
9.2.1. Fashion trend forecasting
9.2.1.1.
Definition
9.2.1.2.
Market
Estimation and Penetration, 2015 - 2021
9.2.1.3.
Market
Forecast, 2022 – 2030
9.2.1.4.
Compound
Annual Growth Rate (CAGR)
9.2.1.5.
Regional
Bifurcation
9.2.1.5.1.
North
America
9.2.1.5.1.1. Market Estimation, 2015 - 2021
9.2.1.5.1.2. Market Forecast, 2022 – 2030
9.2.1.5.2.
Europe
9.2.1.5.2.1. Market Estimation, 2015 - 2021
9.2.1.5.2.2. Market Forecast, 2022 – 2030
9.2.1.5.3.
Asia
Pacific
9.2.1.5.3.1. Market Estimation, 2015 - 2021
9.2.1.5.3.2. Market Forecast, 2022 – 2030
9.2.1.5.4.
Middle
East and Africa
9.2.1.5.4.1. Market Estimation, 2015 - 2021
9.2.1.5.4.2. Market Forecast, 2022 – 2030
9.2.1.5.5.
Latin
America
9.2.1.5.5.1. Market Estimation, 2015 - 2021
9.2.1.5.5.2. Market Forecast, 2022 – 2030
9.2.2. Spotting winning products and Automatic
Tagging
9.2.2.1.
Definition
9.2.2.2.
Market
Estimation and Penetration, 2015 - 2021
9.2.2.3.
Market
Forecast, 2022 – 2030
9.2.2.4.
Compound
Annual Growth Rate (CAGR)
9.2.2.5.
Regional
Bifurcation
9.2.2.5.1.
North
America
9.2.2.5.1.1. Market Estimation, 2015 - 2021
9.2.2.5.1.2. Market Forecast, 2022 – 2030
9.2.2.5.2.
Europe
9.2.2.5.2.1. Market Estimation, 2015 - 2021
9.2.2.5.2.2. Market Forecast, 2022 – 2030
9.2.2.5.3.
Asia
Pacific
9.2.2.5.3.1. Market Estimation, 2015 - 2021
9.2.2.5.3.2. Market Forecast, 2022 – 2030
9.2.2.5.4.
Middle
East and Africa
9.2.2.5.4.1. Market Estimation, 2015 - 2021
9.2.2.5.4.2. Market Forecast, 2022 – 2030
9.2.2.5.5.
Latin
America
9.2.2.5.5.1. Market Estimation, 2015 - 2021
9.2.2.5.5.2. Market Forecast, 2022 – 2030
9.2.3. Demand forecasting
9.2.3.1.
Definition
9.2.3.2.
Market
Estimation and Penetration, 2015 - 2021
9.2.3.3.
Market
Forecast, 2022 – 2030
9.2.3.4.
Compound
Annual Growth Rate (CAGR)
9.2.3.5.
Regional
Bifurcation
9.2.3.5.1.
North
America
9.2.3.5.1.1. Market Estimation, 2015 - 2021
9.2.3.5.1.2. Market Forecast, 2022 – 2030
9.2.3.5.2.
Europe
9.2.3.5.2.1. Market Estimation, 2015 - 2021
9.2.3.5.2.2. Market Forecast, 2022 – 2030
9.2.3.5.3.
Asia
Pacific
9.2.3.5.3.1. Market Estimation, 2015 - 2021
9.2.3.5.3.2. Market Forecast, 2022 – 2030
9.2.3.5.4.
Middle
East and Africa
9.2.3.5.4.1. Market Estimation, 2015 - 2021
9.2.3.5.4.2. Market Forecast, 2022 – 2030
9.2.3.5.5.
Latin
America
9.2.3.5.5.1. Market Estimation, 2015 - 2021
9.2.3.5.5.2. Market Forecast, 2022 – 2030
9.2.4. Similar Recommendations and Visual Search
9.2.4.1.
Definition
9.2.4.2.
Market
Estimation and Penetration, 2015 - 2021
9.2.4.3.
Market
Forecast, 2022 – 2030
9.2.4.4.
Compound
Annual Growth Rate (CAGR)
9.2.4.5.
Regional
Bifurcation
9.2.4.5.1.
North
America
9.2.4.5.1.1. Market Estimation, 2015 - 2021
9.2.4.5.1.2. Market Forecast, 2022 – 2030
9.2.4.5.2.
Europe
9.2.4.5.2.1. Market Estimation, 2015 - 2021
9.2.4.5.2.2. Market Forecast, 2022 – 2030
9.2.4.5.3.
Asia
Pacific
9.2.4.5.3.1. Market Estimation, 2015 - 2021
9.2.4.5.3.2. Market Forecast, 2022 – 2030
9.2.4.5.4.
Middle
East and Africa
9.2.4.5.4.1. Market Estimation, 2015 - 2021
9.2.4.5.4.2. Market Forecast, 2022 – 2030
9.2.4.5.5.
Latin
America
9.2.4.5.5.1. Market Estimation, 2015 - 2021
9.2.4.5.5.2. Market Forecast, 2022 – 2030
9.2.5. Inventory optimization across the value chain
9.2.5.1.
Definition
9.2.5.2.
Market
Estimation and Penetration, 2015 - 2021
9.2.5.3.
Market
Forecast, 2022 – 2030
9.2.5.4.
Compound
Annual Growth Rate (CAGR)
9.2.5.5.
Regional
Bifurcation
9.2.5.5.1.
North
America
9.2.5.5.1.1. Market Estimation, 2015 - 2021
9.2.5.5.1.2. Market Forecast, 2022 – 2030
9.2.5.5.2.
Europe
9.2.5.5.2.1. Market Estimation, 2015 - 2021
9.2.5.5.2.2. Market Forecast, 2022 – 2030
9.2.5.5.3.
Asia
Pacific
9.2.5.5.3.1. Market Estimation, 2015 - 2021
9.2.5.5.3.2. Market Forecast, 2022 – 2030
9.2.5.5.4.
Middle
East and Africa
9.2.5.5.4.1. Market Estimation, 2015 - 2021
9.2.5.5.4.2. Market Forecast, 2022 – 2030
9.2.5.5.5.
Latin
America
9.2.5.5.5.1. Market Estimation, 2015 - 2021
9.2.5.5.5.2. Market Forecast, 2022 – 2030
9.2.6. Customer Experience Management and Retail
Automation
9.2.6.1.
Definition
9.2.6.2.
Market
Estimation and Penetration, 2015 - 2021
9.2.6.3.
Market
Forecast, 2022 – 2030
9.2.6.4.
Compound
Annual Growth Rate (CAGR)
9.2.6.5.
Regional
Bifurcation
9.2.6.5.1.
North
America
9.2.6.5.1.1. Market Estimation, 2015 - 2021
9.2.6.5.1.2. Market Forecast, 2022 – 2030
9.2.6.5.2.
Europe
9.2.6.5.2.1. Market Estimation, 2015 - 2021
9.2.6.5.2.2. Market Forecast, 2022 – 2030
9.2.6.5.3.
Asia
Pacific
9.2.6.5.3.1. Market Estimation, 2015 - 2021
9.2.6.5.3.2. Market Forecast, 2022 – 2030
9.2.6.5.4.
Middle
East and Africa
9.2.6.5.4.1. Market Estimation, 2015 - 2021
9.2.6.5.4.2. Market Forecast, 2022 – 2030
9.2.6.5.5.
Latin
America
9.2.6.5.5.1. Market Estimation, 2015 - 2021
9.2.6.5.5.2. Market Forecast, 2022 – 2030
9.2.7. Content Management
9.2.7.1.
Definition
9.2.7.2.
Market
Estimation and Penetration, 2015 - 2021
9.2.7.3.
Market
Forecast, 2022 – 2030
9.2.7.4.
Compound
Annual Growth Rate (CAGR)
9.2.7.5.
Regional
Bifurcation
9.2.7.5.1.
North
America
9.2.7.5.1.1. Market Estimation, 2015 - 2021
9.2.7.5.1.2. Market Forecast, 2022 – 2030
9.2.7.5.2.
Europe
9.2.7.5.2.1. Market Estimation, 2015 - 2021
9.2.7.5.2.2. Market Forecast, 2022 – 2030
9.2.7.5.3.
Asia
Pacific
9.2.7.5.3.1. Market Estimation, 2015 - 2021
9.2.7.5.3.2. Market Forecast, 2022 – 2030
9.2.7.5.4.
Middle
East and Africa
9.2.7.5.4.1. Market Estimation, 2015 - 2021
9.2.7.5.4.2. Market Forecast, 2022 – 2030
9.2.7.5.5.
Latin
America
9.2.7.5.5.1. Market Estimation, 2015 - 2021
9.2.7.5.5.2. Market Forecast, 2022 – 2030
9.2.8. Localizing assortment for a store
9.2.8.1.
Definition
9.2.8.2.
Market
Estimation and Penetration, 2015 - 2021
9.2.8.3.
Market
Forecast, 2022 – 2030
9.2.8.4.
Compound
Annual Growth Rate (CAGR)
9.2.8.5.
Regional
Bifurcation
9.2.8.5.1.
North
America
9.2.8.5.1.1. Market Estimation, 2015 - 2021
9.2.8.5.1.2. Market Forecast, 2022 – 2030
9.2.8.5.2.
Europe
9.2.8.5.2.1. Market Estimation, 2015 - 2021
9.2.8.5.2.2. Market Forecast, 2022 – 2030
9.2.8.5.3.
Asia
Pacific
9.2.8.5.3.1. Market Estimation, 2015 - 2021
9.2.8.5.3.2. Market Forecast, 2022 – 2030
9.2.8.5.4.
Middle
East and Africa
9.2.8.5.4.1. Market Estimation, 2015 - 2021
9.2.8.5.4.2. Market Forecast, 2022 – 2030
9.2.8.5.5.
Latin
America
9.2.8.5.5.1. Market Estimation, 2015 - 2021
9.2.8.5.5.2. Market Forecast, 2022 – 2030
9.2.9. Others
9.2.9.1.
Definition
9.2.9.2.
Market
Estimation and Penetration, 2015 - 2021
9.2.9.3.
Market
Forecast, 2022 – 2030
9.2.9.4.
Compound
Annual Growth Rate (CAGR)
9.2.9.5.
Regional
Bifurcation
9.2.9.5.1.
North
America
9.2.9.5.1.1. Market Estimation, 2015 - 2021
9.2.9.5.1.2. Market Forecast, 2022 – 2030
9.2.9.5.2.
Europe
9.2.9.5.2.1. Market Estimation, 2015 - 2021
9.2.9.5.2.2. Market Forecast, 2022 – 2030
9.2.9.5.3.
Asia
Pacific
9.2.9.5.3.1. Market Estimation, 2015 - 2021
9.2.9.5.3.2. Market Forecast, 2022 – 2030
9.2.9.5.4.
Middle
East and Africa
9.2.9.5.4.1. Market Estimation, 2015 - 2021
9.2.9.5.4.2. Market Forecast, 2022 – 2030
9.2.9.5.5.
Latin
America
9.2.9.5.5.1. Market Estimation, 2015 - 2021
9.2.9.5.5.2. Market Forecast, 2022 – 2030
9.3. Key Segment for Channeling Investments
9.3.1. By Application
10. Global AI in Fashion Market Analysis and
Forecasts, 2022 – 2030
10.1. Overview
10.2. Global AI in Fashion Market Revenue (US$ Mn)
and Forecasts, By Organization Size
10.2.1. Startups
10.2.1.1.
Definition
10.2.1.2.
Market
Estimation and Penetration, 2015 - 2021
10.2.1.3.
Market
Forecast, 2022 – 2030
10.2.1.4.
Compound
Annual Growth Rate (CAGR)
10.2.1.5.
Regional
Bifurcation
10.2.1.5.1.
North
America
10.2.1.5.1.1. Market Estimation, 2015 - 2021
10.2.1.5.1.2. Market Forecast, 2022 – 2030
10.2.1.5.2.
Europe
10.2.1.5.2.1. Market Estimation, 2015 - 2021
10.2.1.5.2.2. Market Forecast, 2022 – 2030
10.2.1.5.3.
Asia
Pacific
10.2.1.5.3.1. Market Estimation, 2015 - 2021
10.2.1.5.3.2. Market Forecast, 2022 – 2030
10.2.1.5.4.
Middle East
and Africa
10.2.1.5.4.1. Market Estimation, 2015 - 2021
10.2.1.5.4.2. Market Forecast, 2022 – 2030
10.2.1.5.5.
Latin
America
10.2.1.5.5.1. Market Estimation, 2015 - 2021
10.2.1.5.5.2. Market Forecast, 2022 – 2030
10.2.2. Small and Medium Organizations
10.2.2.1.
Definition
10.2.2.2.
Market
Estimation and Penetration, 2015 - 2021
10.2.2.3.
Market
Forecast, 2022 – 2030
10.2.2.4.
Compound
Annual Growth Rate (CAGR)
10.2.2.5.
Regional
Bifurcation
10.2.2.5.1.
North
America
10.2.2.5.1.1. Market Estimation, 2015 - 2021
10.2.2.5.1.2. Market Forecast, 2022 – 2030
10.2.2.5.2.
Europe
10.2.2.5.2.1. Market Estimation, 2015 - 2021
10.2.2.5.2.2. Market Forecast, 2022 – 2030
10.2.2.5.3.
Asia
Pacific
10.2.2.5.3.1. Market Estimation, 2015 - 2021
10.2.2.5.3.2. Market Forecast, 2022 – 2030
10.2.2.5.4.
Middle
East and Africa
10.2.2.5.4.1. Market Estimation, 2015 - 2021
10.2.2.5.4.2. Market Forecast, 2022 – 2030
10.2.2.5.5.
Latin
America
10.2.2.5.5.1. Market Estimation, 2015 - 2021
10.2.2.5.5.2. Market Forecast, 2022 – 2030
10.2.3. Large Organizations
10.2.3.1.
Definition
10.2.3.2.
Market
Estimation and Penetration, 2015 - 2021
10.2.3.3.
Market
Forecast, 2022 – 2030
10.2.3.4.
Compound
Annual Growth Rate (CAGR)
10.2.3.5.
Regional
Bifurcation
10.2.3.5.1.
North
America
10.2.3.5.1.1. Market Estimation, 2015 - 2021
10.2.3.5.1.2. Market Forecast, 2022 – 2030
10.2.3.5.2.
Europe
10.2.3.5.2.1. Market Estimation, 2015 - 2021
10.2.3.5.2.2. Market Forecast, 2022 – 2030
10.2.3.5.3.
Asia Pacific
10.2.3.5.3.1. Market Estimation, 2015 - 2021
10.2.3.5.3.2. Market Forecast, 2022 – 2030
10.2.3.5.4.
Middle
East and Africa
10.2.3.5.4.1. Market Estimation, 2015 - 2021
10.2.3.5.4.2. Market Forecast, 2022 – 2030
10.2.3.5.5.
Latin
America
10.2.3.5.5.1. Market Estimation, 2015 - 2021
10.2.3.5.5.2. Market Forecast, 2022 – 2030
10.3. Key Segment for Channeling Investments
10.3.1. By Organization Size
11. Global AI in Fashion Market Analysis and
Forecasts, 2022 – 2030
11.1. Overview
11.2. Global AI in Fashion Market Revenue (US$ Mn)
and Forecasts, By Category
11.2.1. Apparel
11.2.1.1.
Definition
11.2.1.2.
Market
Estimation and Penetration, 2015 - 2021
11.2.1.3.
Market
Forecast, 2022 – 2030
11.2.1.4.
Compound
Annual Growth Rate (CAGR)
11.2.1.5.
Regional
Bifurcation
11.2.1.5.1.
North
America
11.2.1.5.1.1. Market Estimation, 2015 - 2021
11.2.1.5.1.2. Market Forecast, 2022 – 2030
11.2.1.5.2.
Europe
11.2.1.5.2.1. Market Estimation, 2015 - 2021
11.2.1.5.2.2. Market Forecast, 2022 – 2030
11.2.1.5.3.
Asia
Pacific
11.2.1.5.3.1. Market Estimation, 2015 - 2021
11.2.1.5.3.2. Market Forecast, 2022 – 2030
11.2.1.5.4.
Middle
East and Africa
11.2.1.5.4.1. Market Estimation, 2015 - 2021
11.2.1.5.4.2. Market Forecast, 2022 – 2030
11.2.1.5.5.
Latin
America
11.2.1.5.5.1. Market Estimation, 2015 - 2021
11.2.1.5.5.2. Market Forecast, 2022 – 2030
11.2.2. Accessories
11.2.2.1.
Definition
11.2.2.2.
Market
Estimation and Penetration, 2015 - 2021
11.2.2.3.
Market
Forecast, 2022 – 2030
11.2.2.4.
Compound
Annual Growth Rate (CAGR)
11.2.2.5.
Regional
Bifurcation
11.2.2.5.1.
North
America
11.2.2.5.1.1. Market Estimation, 2015 - 2021
11.2.2.5.1.2. Market Forecast, 2022 – 2030
11.2.2.5.2.
Europe
11.2.2.5.2.1. Market Estimation, 2015 - 2021
11.2.2.5.2.2. Market Forecast, 2022 – 2030
11.2.2.5.3.
Asia
Pacific
11.2.2.5.3.1. Market Estimation, 2015 - 2021
11.2.2.5.3.2. Market Forecast, 2022 – 2030
11.2.2.5.4.
Middle
East and Africa
11.2.2.5.4.1. Market Estimation, 2015 - 2021
11.2.2.5.4.2. Market Forecast, 2022 – 2030
11.2.2.5.5.
Latin
America
11.2.2.5.5.1. Market Estimation, 2015 - 2021
11.2.2.5.5.2. Market Forecast, 2022 – 2030
11.2.3. Footwear
11.2.3.1.
Definition
11.2.3.2.
Market
Estimation and Penetration, 2015 - 2021
11.2.3.3.
Market
Forecast, 2022 – 2030
11.2.3.4.
Compound
Annual Growth Rate (CAGR)
11.2.3.5.
Regional
Bifurcation
11.2.3.5.1.
North
America
11.2.3.5.1.1. Market Estimation, 2015 - 2021
11.2.3.5.1.2. Market Forecast, 2022 – 2030
11.2.3.5.2.
Europe
11.2.3.5.2.1. Market Estimation, 2015 - 2021
11.2.3.5.2.2. Market Forecast, 2022 – 2030
11.2.3.5.3.
Asia
Pacific
11.2.3.5.3.1. Market Estimation, 2015 - 2021
11.2.3.5.3.2. Market Forecast, 2022 – 2030
11.2.3.5.4.
Middle
East and Africa
11.2.3.5.4.1. Market Estimation, 2015 - 2021
11.2.3.5.4.2. Market Forecast, 2022 – 2030
11.2.3.5.5.
Latin
America
11.2.3.5.5.1. Market Estimation, 2015 - 2021
11.2.3.5.5.2. Market Forecast, 2022 – 2030
11.2.4. Beauty and Cosmetics
11.2.4.1.
Definition
11.2.4.2.
Market
Estimation and Penetration, 2015 - 2021
11.2.4.3.
Market
Forecast, 2022 – 2030
11.2.4.4.
Compound
Annual Growth Rate (CAGR)
11.2.4.5.
Regional
Bifurcation
11.2.4.5.1.
North
America
11.2.4.5.1.1. Market Estimation, 2015 - 2021
11.2.4.5.1.2. Market Forecast, 2022 – 2030
11.2.4.5.2.
Europe
11.2.4.5.2.1. Market Estimation, 2015 - 2021
11.2.4.5.2.2. Market Forecast, 2022 – 2030
11.2.4.5.3.
Asia
Pacific
11.2.4.5.3.1. Market Estimation, 2015 - 2021
11.2.4.5.3.2. Market Forecast, 2022 – 2030
11.2.4.5.4.
Middle
East and Africa
11.2.4.5.4.1. Market Estimation, 2015 - 2021
11.2.4.5.4.2. Market Forecast, 2022 – 2030
11.2.4.5.5.
Latin
America
11.2.4.5.5.1. Market Estimation, 2015 - 2021
11.2.4.5.5.2. Market Forecast, 2022 – 2030
11.2.5. Others
11.2.5.1.
Definition
11.2.5.2.
Market
Estimation and Penetration, 2015 - 2021
11.2.5.3.
Market
Forecast, 2022 – 2030
11.2.5.4.
Compound
Annual Growth Rate (CAGR)
11.2.5.5.
Regional
Bifurcation
11.2.5.5.1.
North
America
11.2.5.5.1.1. Market Estimation, 2015 - 2021
11.2.5.5.1.2. Market Forecast, 2022 – 2030
11.2.5.5.2.
Europe
11.2.5.5.2.1. Market Estimation, 2015 - 2021
11.2.5.5.2.2. Market Forecast, 2022 – 2030
11.2.5.5.3.
Asia
Pacific
11.2.5.5.3.1. Market Estimation, 2015 - 2021
11.2.5.5.3.2. Market Forecast, 2022 – 2030
11.2.5.5.4.
Middle
East and Africa
11.2.5.5.4.1. Market Estimation, 2015 - 2021
11.2.5.5.4.2. Market Forecast, 2022 – 2030
11.2.5.5.5.
Latin
America
11.2.5.5.5.1. Market Estimation, 2015 - 2021
11.2.5.5.5.2. Market Forecast, 2022 – 2030
11.3. Key Segment for Channeling Investments
11.3.1. By Category
12. Global AI in Fashion Market Analysis and
Forecasts, 2022 – 2030
12.1. Overview
12.2. Global AI in Fashion Market Revenue (US$ Mn)
and Forecasts, By End User
12.2.1. Designers
12.2.1.1.
Definition
12.2.1.2.
Market
Estimation and Penetration, 2015 - 2021
12.2.1.3.
Market
Forecast, 2022 – 2030
12.2.1.4.
Compound
Annual Growth Rate (CAGR)
12.2.1.5.
Regional
Bifurcation
12.2.1.5.1.
North
America
12.2.1.5.1.1. Market Estimation, 2015 - 2021
12.2.1.5.1.2. Market Forecast, 2022 – 2030
12.2.1.5.2.
Europe
12.2.1.5.2.1. Market Estimation, 2015 - 2021
12.2.1.5.2.2. Market Forecast, 2022 – 2030
12.2.1.5.3.
Asia
Pacific
12.2.1.5.3.1. Market Estimation, 2015 - 2021
12.2.1.5.3.2. Market Forecast, 2022 – 2030
12.2.1.5.4.
Middle
East and Africa
12.2.1.5.4.1. Market Estimation, 2015 - 2021
12.2.1.5.4.2. Market Forecast, 2022 – 2030
12.2.1.5.5.
Latin
America
12.2.1.5.5.1. Market Estimation, 2015 - 2021
12.2.1.5.5.2. Market Forecast, 2022 – 2030
12.2.2. Manufacturers
12.2.2.1.
Definition
12.2.2.2.
Market
Estimation and Penetration, 2015 - 2021
12.2.2.3.
Market
Forecast, 2022 – 2030
12.2.2.4.
Compound
Annual Growth Rate (CAGR)
12.2.2.5.
Regional
Bifurcation
12.2.2.5.1.
North
America
12.2.2.5.1.1. Market Estimation, 2015 - 2021
12.2.2.5.1.2. Market Forecast, 2022 – 2030
12.2.2.5.2.
Europe
12.2.2.5.2.1. Market Estimation, 2015 - 2021
12.2.2.5.2.2. Market Forecast, 2022 – 2030
12.2.2.5.3.
Asia
Pacific
12.2.2.5.3.1. Market Estimation, 2015 - 2021
12.2.2.5.3.2. Market Forecast, 2022 – 2030
12.2.2.5.4.
Middle
East and Africa
12.2.2.5.4.1. Market Estimation, 2015 - 2021
12.2.2.5.4.2. Market Forecast, 2022 – 2030
12.2.2.5.5.
Latin America
12.2.2.5.5.1. Market Estimation, 2015 - 2021
12.2.2.5.5.2. Market Forecast, 2022 – 2030
12.2.3. Retailers
12.2.3.1.
Definition
12.2.3.2.
Market
Estimation and Penetration, 2015 - 2021
12.2.3.3.
Market
Forecast, 2022 – 2030
12.2.3.4.
Compound
Annual Growth Rate (CAGR)
12.2.3.5.
Regional
Bifurcation
12.2.3.5.1.
North
America
12.2.3.5.1.1. Market Estimation, 2015 - 2021
12.2.3.5.1.2. Market Forecast, 2022 – 2030
12.2.3.5.2.
Europe
12.2.3.5.2.1. Market Estimation, 2015 - 2021
12.2.3.5.2.2. Market Forecast, 2022 – 2030
12.2.3.5.3.
Asia
Pacific
12.2.3.5.3.1. Market Estimation, 2015 - 2021
12.2.3.5.3.2. Market Forecast, 2022 – 2030
12.2.3.5.4.
Middle
East and Africa
12.2.3.5.4.1. Market Estimation, 2015 - 2021
12.2.3.5.4.2. Market Forecast, 2022 – 2030
12.2.3.5.5.
Latin
America
12.2.3.5.5.1. Market Estimation, 2015 - 2021
12.2.3.5.5.2. Market Forecast, 2022 – 2030
12.2.4. Planners
12.2.4.1.
Definition
12.2.4.2.
Market
Estimation and Penetration, 2015 - 2021
12.2.4.3.
Market
Forecast, 2022 – 2030
12.2.4.4.
Compound
Annual Growth Rate (CAGR)
12.2.4.5.
Regional
Bifurcation
12.2.4.5.1.
North America
12.2.4.5.1.1. Market Estimation, 2015 - 2021
12.2.4.5.1.2. Market Forecast, 2022 – 2030
12.2.4.5.2.
Europe
12.2.4.5.2.1. Market Estimation, 2015 - 2021
12.2.4.5.2.2. Market Forecast, 2022 – 2030
12.2.4.5.3.
Asia
Pacific
12.2.4.5.3.1. Market Estimation, 2015 - 2021
12.2.4.5.3.2. Market Forecast, 2022 – 2030
12.2.4.5.4.
Middle
East and Africa
12.2.4.5.4.1. Market Estimation, 2015 - 2021
12.2.4.5.4.2. Market Forecast, 2022 – 2030
12.2.4.5.5.
Latin
America
12.2.4.5.5.1. Market Estimation, 2015 - 2021
12.2.4.5.5.2. Market Forecast, 2022 – 2030
12.2.5. Market researchers and Merchandisers
12.2.5.1.
Definition
12.2.5.2.
Market
Estimation and Penetration, 2015 - 2021
12.2.5.3.
Market
Forecast, 2022 – 2030
12.2.5.4.
Compound
Annual Growth Rate (CAGR)
12.2.5.5.
Regional
Bifurcation
12.2.5.5.1.
North
America
12.2.5.5.1.1. Market Estimation, 2015 - 2021
12.2.5.5.1.2. Market Forecast, 2022 – 2030
12.2.5.5.2.
Europe
12.2.5.5.2.1. Market Estimation, 2015 - 2021
12.2.5.5.2.2. Market Forecast, 2022 – 2030
12.2.5.5.3.
Asia
Pacific
12.2.5.5.3.1. Market Estimation, 2015 - 2021
12.2.5.5.3.2. Market Forecast, 2022 – 2030
12.2.5.5.4.
Middle
East and Africa
12.2.5.5.4.1. Market Estimation, 2015 - 2021
12.2.5.5.4.2. Market Forecast, 2022 – 2030
12.2.5.5.5.
Latin
America
12.2.5.5.5.1. Market Estimation, 2015 - 2021
12.2.5.5.5.2. Market Forecast, 2022 – 2030
12.2.6. Category Heads
12.2.6.1.
Definition
12.2.6.2.
Market
Estimation and Penetration, 2015 - 2021
12.2.6.3.
Market
Forecast, 2022 – 2030
12.2.6.4.
Compound
Annual Growth Rate (CAGR)
12.2.6.5.
Regional
Bifurcation
12.2.6.5.1.
North
America
12.2.6.5.1.1. Market Estimation, 2015 - 2021
12.2.6.5.1.2. Market Forecast, 2022 – 2030
12.2.6.5.2.
Europe
12.2.6.5.2.1. Market Estimation, 2015 - 2021
12.2.6.5.2.2. Market Forecast, 2022 – 2030
12.2.6.5.3.
Asia
Pacific
12.2.6.5.3.1. Market Estimation, 2015 - 2021
12.2.6.5.3.2. Market Forecast, 2022 – 2030
12.2.6.5.4.
Middle
East and Africa
12.2.6.5.4.1. Market Estimation, 2015 - 2021
12.2.6.5.4.2. Market Forecast, 2022 – 2030
12.2.6.5.5.
Latin
America
12.2.6.5.5.1. Market Estimation, 2015 - 2021
12.2.6.5.5.2. Market Forecast, 2022 – 2030
12.2.7. Store Frontend Employees / Fashion stores
12.2.7.1.
Definition
12.2.7.2.
Market
Estimation and Penetration, 2015 - 2021
12.2.7.3.
Market
Forecast, 2022 – 2030
12.2.7.4.
Compound
Annual Growth Rate (CAGR)
12.2.7.5.
Regional
Bifurcation
12.2.7.5.1.
North
America
12.2.7.5.1.1. Market Estimation, 2015 - 2021
12.2.7.5.1.2. Market Forecast, 2022 – 2030
12.2.7.5.2.
Europe
12.2.7.5.2.1. Market Estimation, 2015 - 2021
12.2.7.5.2.2. Market Forecast, 2022 – 2030
12.2.7.5.3.
Asia
Pacific
12.2.7.5.3.1. Market Estimation, 2015 - 2021
12.2.7.5.3.2. Market Forecast, 2022 – 2030
12.2.7.5.4.
Middle
East and Africa
12.2.7.5.4.1. Market Estimation, 2015 - 2021
12.2.7.5.4.2. Market Forecast, 2022 – 2030
12.2.7.5.5.
Latin
America
12.2.7.5.5.1. Market Estimation, 2015 - 2021
12.2.7.5.5.2. Market Forecast, 2022 – 2030
12.2.8. Others
12.2.8.1.
Definition
12.2.8.2.
Market
Estimation and Penetration, 2015 - 2021
12.2.8.3.
Market
Forecast, 2022 – 2030
12.2.8.4.
Compound
Annual Growth Rate (CAGR)
12.2.8.5.
Regional
Bifurcation
12.2.8.5.1.
North
America
12.2.8.5.1.1. Market Estimation, 2015 - 2021
12.2.8.5.1.2. Market Forecast, 2022 – 2030
12.2.8.5.2.
Europe
12.2.8.5.2.1. Market Estimation, 2015 - 2021
12.2.8.5.2.2. Market Forecast, 2022 – 2030
12.2.8.5.3.
Asia
Pacific
12.2.8.5.3.1. Market Estimation, 2015 - 2021
12.2.8.5.3.2. Market Forecast, 2022 – 2030
12.2.8.5.4.
Middle
East and Africa
12.2.8.5.4.1. Market Estimation, 2015 - 2021
12.2.8.5.4.2. Market Forecast, 2022 – 2030
12.2.8.5.5.
Latin
America
12.2.8.5.5.1. Market Estimation, 2015 - 2021
12.2.8.5.5.2. Market Forecast, 2022 – 2030
12.3. Key Segment for Channeling Investments
12.3.1. By End User
13. North America AI in Fashion Market Analysis
and Forecasts, 2022 – 2030
13.1. Overview
13.1.1. North America AI in Fashion Market Revenue
(US$ Mn)
13.2. North America AI in Fashion Market Revenue
(US$ Mn) and Forecasts, By Component
13.2.1. Solutions
13.2.2. Services
13.3. North America AI in Fashion Market Revenue
(US$ Mn) and Forecasts, By Application
13.3.1. Fashion trend forecasting
13.3.2. Spotting winning products and Automatic
Tagging
13.3.3. Demand forecasting
13.3.4. Similar Recommendations and Visual Search
13.3.5. Inventory optimization across the value chain
13.3.6. Customer Experience Management and Retail
Automation
13.3.7. Content Management
13.3.8. Localizing assortment for a store
13.3.9. Others
13.4. North America AI in Fashion Market Revenue
(US$ Mn) and Forecasts, By Organization Size
13.4.1. Startups
13.4.2. Small and Medium Organizations
13.4.3. Large Organizations
13.5. North America AI in Fashion Market Revenue
(US$ Mn) and Forecasts, By Category
13.5.1. Apparel
13.5.2. Accessories
13.5.3. Footwear
13.5.4. Beauty and Cosmetics
13.5.5. Others
13.6. North America AI in Fashion Market Revenue (US$
Mn) and Forecasts, By End User
13.6.1. Designers
13.6.2. Manufacturers
13.6.3. Retailers
13.6.4. Planners
13.6.5. Market researchers and Merchandisers
13.6.6. Category Heads
13.6.7. Store Frontend Employees / Fashion stores
13.6.8. Others
13.7. North America AI in Fashion Market Revenue
(US$ Mn) and Forecasts, By Country
13.7.1. U.S
13.7.1.1.
U.S AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
13.7.1.1.1.
Solutions
13.7.1.1.2.
Services
13.7.1.2.
U.S AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
13.7.1.2.1.
Fashion
trend forecasting
13.7.1.2.2.
Spotting
winning products and Automatic Tagging
13.7.1.2.3.
Demand forecasting
13.7.1.2.4.
Similar
Recommendations and Visual Search
13.7.1.2.5.
Inventory
optimization across the value chain
13.7.1.2.6.
Customer
Experience Management and Retail Automation
13.7.1.2.7.
Content
Management
13.7.1.2.8.
Localizing
assortment for a store
13.7.1.2.9.
Others
13.7.1.3.
U.S AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
13.7.1.3.1.
Startups
13.7.1.3.2.
Small
and Medium Organizations
13.7.1.3.3.
Large
Organizations
13.7.1.4.
U.S AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
13.7.1.4.1.
Apparel
13.7.1.4.2.
Accessories
13.7.1.4.3.
Footwear
13.7.1.4.4.
Beauty
and Cosmetics
13.7.1.4.5.
Others
13.7.1.5.
U.S AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
13.7.1.5.1.
Designers
13.7.1.5.2.
Manufacturers
13.7.1.5.3.
Retailers
13.7.1.5.4.
Planners
13.7.1.5.5.
Market
researchers and Merchandisers
13.7.1.5.6.
Category
Heads
13.7.1.5.7.
Store
Frontend Employees / Fashion stores
13.7.1.5.8.
Others
13.7.2. Canada
13.7.2.1.
Canada
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
13.7.2.1.1.
Solutions
13.7.2.1.2.
Services
13.7.2.2.
Canada
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
13.7.2.2.1.
Fashion
trend forecasting
13.7.2.2.2.
Spotting
winning products and Automatic Tagging
13.7.2.2.3.
Demand
forecasting
13.7.2.2.4.
Similar
Recommendations and Visual Search
13.7.2.2.5.
Inventory
optimization across the value chain
13.7.2.2.6.
Customer
Experience Management and Retail Automation
13.7.2.2.7.
Content
Management
13.7.2.2.8.
Localizing
assortment for a store
13.7.2.2.9.
Others
13.7.2.3.
Canada
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
13.7.2.3.1.
Startups
13.7.2.3.2.
Small
and Medium Organizations
13.7.2.3.3.
Large
Organizations
13.7.2.4.
Canada
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
13.7.2.4.1.
Apparel
13.7.2.4.2.
Accessories
13.7.2.4.3.
Footwear
13.7.2.4.4.
Beauty
and Cosmetics
13.7.2.4.5.
Others
13.7.2.5.
Canada
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
13.7.2.5.1.
Designers
13.7.2.5.2.
Manufacturers
13.7.2.5.3.
Retailers
13.7.2.5.4.
Planners
13.7.2.5.5.
Market
researchers and Merchandisers
13.7.2.5.6.
Category
Heads
13.7.2.5.7.
Store
Frontend Employees / Fashion stores
13.7.2.5.8.
Others
13.7.3. Mexico
13.7.3.1.
Mexico
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
13.7.3.1.1.
Solutions
13.7.3.1.2.
Services
13.7.3.2.
Mexico
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
13.7.3.2.1.
Fashion
trend forecasting
13.7.3.2.2.
Spotting
winning products and Automatic Tagging
13.7.3.2.3.
Demand
forecasting
13.7.3.2.4.
Similar
Recommendations and Visual Search
13.7.3.2.5.
Inventory
optimization across the value chain
13.7.3.2.6.
Customer
Experience Management and Retail Automation
13.7.3.2.7.
Content
Management
13.7.3.2.8.
Localizing
assortment for a store
13.7.3.2.9.
Others
13.7.3.3.
Mexico
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
13.7.3.3.1.
Startups
13.7.3.3.2.
Small
and Medium Organizations
13.7.3.3.3.
Large
Organizations
13.7.3.4.
Mexico
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
13.7.3.4.1.
Apparel
13.7.3.4.2.
Accessories
13.7.3.4.3.
Footwear
13.7.3.4.4.
Beauty
and Cosmetics
13.7.3.4.5.
Others
13.7.3.5.
Mexico
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
13.7.3.5.1.
Designers
13.7.3.5.2.
Manufacturers
13.7.3.5.3.
Retailers
13.7.3.5.4.
Planners
13.7.3.5.5.
Market
researchers and Merchandisers
13.7.3.5.6.
Category
Heads
13.7.3.5.7.
Store Frontend
Employees / Fashion stores
13.7.3.5.8.
Others
13.7.4. Rest of North America
13.7.4.1.
Rest of
North America AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
13.7.4.1.1.
Solutions
13.7.4.1.2.
Services
13.7.4.2.
Rest of
North America AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
13.7.4.2.1.
Fashion
trend forecasting
13.7.4.2.2.
Spotting
winning products and Automatic Tagging
13.7.4.2.3.
Demand
forecasting
13.7.4.2.4.
Similar
Recommendations and Visual Search
13.7.4.2.5.
Inventory
optimization across the value chain
13.7.4.2.6.
Customer
Experience Management and Retail Automation
13.7.4.2.7.
Content Management
13.7.4.2.8.
Localizing
assortment for a store
13.7.4.2.9.
Others
13.7.4.3.
Rest of
North America AI in Fashion Market Revenue (US$ Mn) and Forecasts, By
Organization Size
13.7.4.3.1.
Startups
13.7.4.3.2.
Small
and Medium Organizations
13.7.4.3.3.
Large
Organizations
13.7.4.4.
Rest of
North America AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
13.7.4.4.1.
Apparel
13.7.4.4.2.
Accessories
13.7.4.4.3.
Footwear
13.7.4.4.4.
Beauty
and Cosmetics
13.7.4.4.5.
Others
13.7.4.5.
Rest of
North America AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
13.7.4.5.1.
Designers
13.7.4.5.2.
Manufacturers
13.7.4.5.3.
Retailers
13.7.4.5.4.
Planners
13.7.4.5.5.
Market
researchers and Merchandisers
13.7.4.5.6.
Category
Heads
13.7.4.5.7.
Store
Frontend Employees / Fashion stores
13.7.4.5.8.
Others
13.8. Key Segment for Channeling Investments
13.8.1. By Country
13.8.2. By Component
13.8.3. By Application
13.8.4. By Organization Size
13.8.5. By Category
13.8.6. By End User
14. Europe AI in Fashion Market Analysis and
Forecasts, 2022 – 2030
14.1. Overview
14.1.1. Europe AI in Fashion Market Revenue (US$ Mn)
14.2. Europe AI in Fashion Market Revenue (US$ Mn)
and Forecasts, By Component
14.2.1. Solutions
14.2.2. Services
14.3. Europe AI in Fashion Market Revenue (US$ Mn)
and Forecasts, By Application
14.3.1. Fashion trend forecasting
14.3.2. Spotting winning products and Automatic
Tagging
14.3.3. Demand forecasting
14.3.4. Similar Recommendations and Visual Search
14.3.5. Inventory optimization across the value chain
14.3.6. Customer Experience Management and Retail
Automation
14.3.7. Content Management
14.3.8. Localizing assortment for a store
14.3.9. Others
14.4. Europe AI in Fashion Market Revenue (US$ Mn)
and Forecasts, By Organization Size
14.4.1. Startups
14.4.2. Small and Medium Organizations
14.4.3. Large Organizations
14.5. Europe AI in Fashion Market Revenue (US$ Mn)
and Forecasts, By Category
14.5.1. Apparel
14.5.2. Accessories
14.5.3. Footwear
14.5.4. Beauty and Cosmetics
14.5.5. Others
14.6. Europe AI in Fashion Market Revenue (US$ Mn)
and Forecasts, By End User
14.6.1. Designers
14.6.2. Manufacturers
14.6.3. Retailers
14.6.4. Planners
14.6.5. Market researchers and Merchandisers
14.6.6. Category Heads
14.6.7. Store Frontend Employees / Fashion stores
14.6.8. Others
14.7. Europe AI in Fashion Market Revenue (US$ Mn)
and Forecasts, By Country
14.7.1. France
14.7.1.1.
France
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
14.7.1.1.1.
Solutions
14.7.1.1.2.
Services
14.7.1.2.
France
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
14.7.1.2.1.
Fashion
trend forecasting
14.7.1.2.2.
Spotting
winning products and Automatic Tagging
14.7.1.2.3.
Demand
forecasting
14.7.1.2.4.
Similar
Recommendations and Visual Search
14.7.1.2.5.
Inventory
optimization across the value chain
14.7.1.2.6.
Customer
Experience Management and Retail Automation
14.7.1.2.7.
Content
Management
14.7.1.2.8.
Localizing
assortment for a store
14.7.1.2.9.
Others
14.7.1.3.
France
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
14.7.1.3.1.
Startups
14.7.1.3.2.
Small
and Medium Organizations
14.7.1.3.3.
Large
Organizations
14.7.1.4.
France
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
14.7.1.4.1.
Apparel
14.7.1.4.2.
Accessories
14.7.1.4.3.
Footwear
14.7.1.4.4.
Beauty
and Cosmetics
14.7.1.4.5.
Others
14.7.1.5.
France
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
14.7.1.5.1.
Designers
14.7.1.5.2.
Manufacturers
14.7.1.5.3.
Retailers
14.7.1.5.4.
Planners
14.7.1.5.5.
Market
researchers and Merchandisers
14.7.1.5.6.
Category
Heads
14.7.1.5.7.
Store
Frontend Employees / Fashion stores
14.7.1.5.8.
Others
14.7.2. The UK
14.7.2.1.
The UK
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
14.7.2.1.1.
Solutions
14.7.2.1.2.
Services
14.7.2.2.
The UK
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
14.7.2.2.1.
Fashion
trend forecasting
14.7.2.2.2.
Spotting
winning products and Automatic Tagging
14.7.2.2.3.
Demand
forecasting
14.7.2.2.4.
Similar
Recommendations and Visual Search
14.7.2.2.5.
Inventory
optimization across the value chain
14.7.2.2.6.
Customer
Experience Management and Retail Automation
14.7.2.2.7.
Content
Management
14.7.2.2.8.
Localizing
assortment for a store
14.7.2.2.9.
Others
14.7.2.3.
The UK
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
14.7.2.3.1.
Startups
14.7.2.3.2.
Small
and Medium Organizations
14.7.2.3.3.
Large
Organizations
14.7.2.4.
The UK
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
14.7.2.4.1.
Apparel
14.7.2.4.2.
Accessories
14.7.2.4.3.
Footwear
14.7.2.4.4.
Beauty
and Cosmetics
14.7.2.4.5.
Others
14.7.2.5.
The UK
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
14.7.2.5.1.
Designers
14.7.2.5.2.
Manufacturers
14.7.2.5.3.
Retailers
14.7.2.5.4.
Planners
14.7.2.5.5.
Market
researchers and Merchandisers
14.7.2.5.6.
Category
Heads
14.7.2.5.7.
Store
Frontend Employees / Fashion stores
14.7.2.5.8.
Others
14.7.3. Spain
14.7.3.1.
Spain AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
14.7.3.1.1.
Solutions
14.7.3.1.2.
Services
14.7.3.2.
Spain AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
14.7.3.2.1.
Fashion
trend forecasting
14.7.3.2.2.
Spotting
winning products and Automatic Tagging
14.7.3.2.3.
Demand
forecasting
14.7.3.2.4.
Similar
Recommendations and Visual Search
14.7.3.2.5.
Inventory
optimization across the value chain
14.7.3.2.6.
Customer
Experience Management and Retail Automation
14.7.3.2.7.
Content
Management
14.7.3.2.8.
Localizing
assortment for a store
14.7.3.2.9.
Others
14.7.3.3.
Spain AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
14.7.3.3.1.
Startups
14.7.3.3.2.
Small
and Medium Organizations
14.7.3.3.3.
Large
Organizations
14.7.3.4.
Spain AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
14.7.3.4.1.
Apparel
14.7.3.4.2.
Accessories
14.7.3.4.3.
Footwear
14.7.3.4.4.
Beauty
and Cosmetics
14.7.3.4.5.
Others
14.7.3.5.
Spain AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
14.7.3.5.1.
Designers
14.7.3.5.2.
Manufacturers
14.7.3.5.3.
Retailers
14.7.3.5.4.
Planners
14.7.3.5.5.
Market
researchers and Merchandisers
14.7.3.5.6.
Category
Heads
14.7.3.5.7.
Store
Frontend Employees / Fashion stores
14.7.3.5.8.
Others
14.7.4. Germany
14.7.4.1.
Germany
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
14.7.4.1.1.
Solutions
14.7.4.1.2.
Services
14.7.4.2.
Germany
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
14.7.4.2.1.
Fashion
trend forecasting
14.7.4.2.2.
Spotting
winning products and Automatic Tagging
14.7.4.2.3.
Demand
forecasting
14.7.4.2.4.
Similar
Recommendations and Visual Search
14.7.4.2.5.
Inventory
optimization across the value chain
14.7.4.2.6.
Customer
Experience Management and Retail Automation
14.7.4.2.7.
Content
Management
14.7.4.2.8.
Localizing
assortment for a store
14.7.4.2.9.
Others
14.7.4.3.
Germany
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
14.7.4.3.1.
Startups
14.7.4.3.2.
Small
and Medium Organizations
14.7.4.3.3.
Large
Organizations
14.7.4.4.
Germany
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
14.7.4.4.1.
Apparel
14.7.4.4.2.
Accessories
14.7.4.4.3.
Footwear
14.7.4.4.4.
Beauty
and Cosmetics
14.7.4.4.5.
Others
14.7.4.5.
Germany
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
14.7.4.5.1.
Designers
14.7.4.5.2.
Manufacturers
14.7.4.5.3.
Retailers
14.7.4.5.4.
Planners
14.7.4.5.5.
Market
researchers and Merchandisers
14.7.4.5.6.
Category
Heads
14.7.4.5.7.
Store
Frontend Employees / Fashion stores
14.7.4.5.8.
Others
14.7.5. Italy
14.7.5.1.
Italy AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
14.7.5.1.1.
Solutions
14.7.5.1.2.
Services
14.7.5.2.
Italy AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
14.7.5.2.1.
Fashion
trend forecasting
14.7.5.2.2.
Spotting
winning products and Automatic Tagging
14.7.5.2.3.
Demand
forecasting
14.7.5.2.4.
Similar
Recommendations and Visual Search
14.7.5.2.5.
Inventory
optimization across the value chain
14.7.5.2.6.
Customer
Experience Management and Retail Automation
14.7.5.2.7.
Content
Management
14.7.5.2.8.
Localizing
assortment for a store
14.7.5.2.9.
Others
14.7.5.3.
Italy AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
14.7.5.3.1.
Startups
14.7.5.3.2.
Small
and Medium Organizations
14.7.5.3.3.
Large
Organizations
14.7.5.4.
Italy AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
14.7.5.4.1.
Apparel
14.7.5.4.2.
Accessories
14.7.5.4.3.
Footwear
14.7.5.4.4.
Beauty
and Cosmetics
14.7.5.4.5.
Others
14.7.5.5.
Italy AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
14.7.5.5.1.
Designers
14.7.5.5.2.
Manufacturers
14.7.5.5.3.
Retailers
14.7.5.5.4.
Planners
14.7.5.5.5.
Market
researchers and Merchandisers
14.7.5.5.6.
Category
Heads
14.7.5.5.7.
Store
Frontend Employees / Fashion stores
14.7.5.5.8.
Others
14.7.6. Nordic Countries
14.7.6.1.
Nordic Countries
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
14.7.6.1.1.
Solutions
14.7.6.1.2.
Services
14.7.6.2.
Nordic
Countries AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
14.7.6.2.1.
Fashion
trend forecasting
14.7.6.2.2.
Spotting
winning products and Automatic Tagging
14.7.6.2.3.
Demand
forecasting
14.7.6.2.4.
Similar
Recommendations and Visual Search
14.7.6.2.5.
Inventory
optimization across the value chain
14.7.6.2.6.
Customer
Experience Management and Retail Automation
14.7.6.2.7.
Content
Management
14.7.6.2.8.
Localizing
assortment for a store
14.7.6.2.9.
Others
14.7.6.3.
Nordic
Countries AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization
Size
14.7.6.3.1.
Startups
14.7.6.3.2.
Small
and Medium Organizations
14.7.6.3.3.
Large
Organizations
14.7.6.4.
Nordic
Countries AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
14.7.6.4.1.
Apparel
14.7.6.4.2.
Accessories
14.7.6.4.3.
Footwear
14.7.6.4.4.
Beauty
and Cosmetics
14.7.6.4.5.
Others
14.7.6.5.
Nordic
Countries AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
14.7.6.5.1.
Designers
14.7.6.5.2.
Manufacturers
14.7.6.5.3.
Retailers
14.7.6.5.4.
Planners
14.7.6.5.5.
Market
researchers and Merchandisers
14.7.6.5.6.
Category
Heads
14.7.6.5.7.
Store
Frontend Employees / Fashion stores
14.7.6.5.8.
Others
14.7.6.6.
Nordic
Countries AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Country
14.7.6.6.1.
Denmark
14.7.6.6.2.
Finland
14.7.6.6.3.
Iceland
14.7.6.6.4.
Sweden
14.7.6.6.5.
Norway
14.7.7. Benelux Union
14.7.7.1.
Benelux
Union AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
14.7.7.1.1.
Solutions
14.7.7.1.2.
Services
14.7.7.2.
Benelux
Union AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
14.7.7.2.1.
Fashion
trend forecasting
14.7.7.2.2.
Spotting
winning products and Automatic Tagging
14.7.7.2.3.
Demand
forecasting
14.7.7.2.4.
Similar
Recommendations and Visual Search
14.7.7.2.5.
Inventory
optimization across the value chain
14.7.7.2.6.
Customer
Experience Management and Retail Automation
14.7.7.2.7.
Content
Management
14.7.7.2.8.
Localizing
assortment for a store
14.7.7.2.9.
Others
14.7.7.3.
Benelux
Union AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
14.7.7.3.1.
Startups
14.7.7.3.2.
Small
and Medium Organizations
14.7.7.3.3.
Large
Organizations
14.7.7.4.
Benelux
Union AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
14.7.7.4.1.
Apparel
14.7.7.4.2.
Accessories
14.7.7.4.3.
Footwear
14.7.7.4.4.
Beauty
and Cosmetics
14.7.7.4.5.
Others
14.7.7.5.
Benelux
Union AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
14.7.7.5.1.
Designers
14.7.7.5.2.
Manufacturers
14.7.7.5.3.
Retailers
14.7.7.5.4.
Planners
14.7.7.5.5.
Market
researchers and Merchandisers
14.7.7.5.6.
Category
Heads
14.7.7.5.7.
Store
Frontend Employees / Fashion stores
14.7.7.5.8.
Others
14.7.7.6.
Benelux
Union AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Country
14.7.7.6.1.
Belgium
14.7.7.6.2.
The
Netherlands
14.7.7.6.3.
Luxembourg
14.7.8. Rest of Europe
14.7.8.1.
Rest of
Europe AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
14.7.8.1.1.
Solutions
14.7.8.1.2.
Services
14.7.8.2.
Rest of
Europe AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
14.7.8.2.1.
Fashion
trend forecasting
14.7.8.2.2.
Spotting
winning products and Automatic Tagging
14.7.8.2.3.
Demand
forecasting
14.7.8.2.4.
Similar
Recommendations and Visual Search
14.7.8.2.5.
Inventory
optimization across the value chain
14.7.8.2.6.
Customer
Experience Management and Retail Automation
14.7.8.2.7.
Content
Management
14.7.8.2.8.
Localizing
assortment for a store
14.7.8.2.9.
Others
14.7.8.3.
Rest of
Europe AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization
Size
14.7.8.3.1.
Startups
14.7.8.3.2.
Small
and Medium Organizations
14.7.8.3.3.
Large
Organizations
14.7.8.4.
Rest of
Europe AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
14.7.8.4.1.
Apparel
14.7.8.4.2.
Accessories
14.7.8.4.3.
Footwear
14.7.8.4.4.
Beauty
and Cosmetics
14.7.8.4.5.
Others
14.7.8.5.
Rest of
Europe AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
14.7.8.5.1.
Designers
14.7.8.5.2.
Manufacturers
14.7.8.5.3.
Retailers
14.7.8.5.4.
Planners
14.7.8.5.5.
Market
researchers and Merchandisers
14.7.8.5.6.
Category
Heads
14.7.8.5.7.
Store
Frontend Employees / Fashion stores
14.7.8.5.8.
Others
14.8. Key Segment for Channeling Investments
14.8.1. By Country
14.8.2. By Component
14.8.3. By Application
14.8.4. By Organization Size
14.8.5. By Category
14.8.6. By End User
15. Asia Pacific AI in Fashion Market Analysis
and Forecasts, 2022 – 2030
15.1. Overview
15.1.1. Asia Pacific AI in Fashion Market Revenue
(US$ Mn)
15.2. Asia Pacific AI in Fashion Market Revenue
(US$ Mn) and Forecasts, By Component
15.2.1. Solutions
15.2.2. Services
15.3. Asia Pacific AI in Fashion Market Revenue
(US$ Mn) and Forecasts, By Application
15.3.1. Fashion trend forecasting
15.3.2. Spotting winning products and Automatic
Tagging
15.3.3. Demand forecasting
15.3.4. Similar Recommendations and Visual Search
15.3.5. Inventory optimization across the value chain
15.3.6. Customer Experience Management and Retail
Automation
15.3.7. Content Management
15.3.8. Localizing assortment for a store
15.3.9. Others
15.4. Asia Pacific AI in Fashion Market Revenue
(US$ Mn) and Forecasts, By Organization Size
15.4.1. Startups
15.4.2. Small and Medium Organizations
15.4.3. Large Organizations
15.5. Asia Pacific AI in Fashion Market Revenue
(US$ Mn) and Forecasts, By Category
15.5.1. Apparel
15.5.2. Accessories
15.5.3. Footwear
15.5.4. Beauty and Cosmetics
15.5.5. Others
15.6. Asia Pacific AI in Fashion Market Revenue
(US$ Mn) and Forecasts, By End User
15.6.1. Designers
15.6.2. Manufacturers
15.6.3. Retailers
15.6.4. Planners
15.6.5. Market researchers and Merchandisers
15.6.6. Category Heads
15.6.7. Store Frontend Employees / Fashion stores
15.6.8. Others
15.7. Asia Pacific AI in Fashion Market Revenue
(US$ Mn) and Forecasts, By Country
15.7.1. China
15.7.1.1.
China AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
15.7.1.1.1.
Solutions
15.7.1.1.2.
Services
15.7.1.2.
China AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
15.7.1.2.1.
Fashion
trend forecasting
15.7.1.2.2.
Spotting
winning products and Automatic Tagging
15.7.1.2.3.
Demand
forecasting
15.7.1.2.4.
Similar
Recommendations and Visual Search
15.7.1.2.5.
Inventory
optimization across the value chain
15.7.1.2.6.
Customer
Experience Management and Retail Automation
15.7.1.2.7.
Content
Management
15.7.1.2.8.
Localizing
assortment for a store
15.7.1.2.9.
Others
15.7.1.3.
China AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
15.7.1.3.1.
Startups
15.7.1.3.2.
Small
and Medium Organizations
15.7.1.3.3.
Large
Organizations
15.7.1.4.
China AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
15.7.1.4.1.
Apparel
15.7.1.4.2.
Accessories
15.7.1.4.3.
Footwear
15.7.1.4.4.
Beauty
and Cosmetics
15.7.1.4.5.
Others
15.7.1.5.
China AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
15.7.1.5.1.
Designers
15.7.1.5.2.
Manufacturers
15.7.1.5.3.
Retailers
15.7.1.5.4.
Planners
15.7.1.5.5.
Market
researchers and Merchandisers
15.7.1.5.6.
Category
Heads
15.7.1.5.7.
Store
Frontend Employees / Fashion stores
15.7.1.5.8.
Others
15.7.2. Japan
15.7.2.1.
Japan AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
15.7.2.1.1.
Solutions
15.7.2.1.2.
Services
15.7.2.2.
Japan AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
15.7.2.2.1.
Fashion
trend forecasting
15.7.2.2.2.
Spotting
winning products and Automatic Tagging
15.7.2.2.3.
Demand
forecasting
15.7.2.2.4.
Similar
Recommendations and Visual Search
15.7.2.2.5.
Inventory
optimization across the value chain
15.7.2.2.6.
Customer
Experience Management and Retail Automation
15.7.2.2.7.
Content
Management
15.7.2.2.8.
Localizing
assortment for a store
15.7.2.2.9.
Others
15.7.2.3.
Japan AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
15.7.2.3.1.
Startups
15.7.2.3.2.
Small
and Medium Organizations
15.7.2.3.3.
Large
Organizations
15.7.2.4.
Japan AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
15.7.2.4.1.
Apparel
15.7.2.4.2.
Accessories
15.7.2.4.3.
Footwear
15.7.2.4.4.
Beauty
and Cosmetics
15.7.2.4.5.
Others
15.7.2.5.
Japan AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
15.7.2.5.1.
Designers
15.7.2.5.2.
Manufacturers
15.7.2.5.3.
Retailers
15.7.2.5.4.
Planners
15.7.2.5.5.
Market
researchers and Merchandisers
15.7.2.5.6.
Category
Heads
15.7.2.5.7.
Store
Frontend Employees / Fashion stores
15.7.2.5.8.
Others
15.7.3. India
15.7.3.1.
India AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
15.7.3.1.1.
Solutions
15.7.3.1.2.
Services
15.7.3.2.
India AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
15.7.3.2.1.
Fashion
trend forecasting
15.7.3.2.2.
Spotting
winning products and Automatic Tagging
15.7.3.2.3.
Demand
forecasting
15.7.3.2.4.
Similar
Recommendations and Visual Search
15.7.3.2.5.
Inventory
optimization across the value chain
15.7.3.2.6.
Customer
Experience Management and Retail Automation
15.7.3.2.7.
Content
Management
15.7.3.2.8.
Localizing
assortment for a store
15.7.3.2.9.
Others
15.7.3.3.
India AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
15.7.3.3.1.
Startups
15.7.3.3.2.
Small
and Medium Organizations
15.7.3.3.3.
Large
Organizations
15.7.3.4.
India AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
15.7.3.4.1.
Apparel
15.7.3.4.2.
Accessories
15.7.3.4.3.
Footwear
15.7.3.4.4.
Beauty
and Cosmetics
15.7.3.4.5.
Others
15.7.3.5.
India AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
15.7.3.5.1.
Designers
15.7.3.5.2.
Manufacturers
15.7.3.5.3.
Retailers
15.7.3.5.4.
Planners
15.7.3.5.5.
Market
researchers and Merchandisers
15.7.3.5.6.
Category
Heads
15.7.3.5.7.
Store
Frontend Employees / Fashion stores
15.7.3.5.8.
Others
15.7.4. New Zealand
15.7.4.1.
New
Zealand AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
15.7.4.1.1.
Solutions
15.7.4.1.2.
Services
15.7.4.2.
New
Zealand AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
15.7.4.2.1.
Fashion
trend forecasting
15.7.4.2.2.
Spotting
winning products and Automatic Tagging
15.7.4.2.3.
Demand
forecasting
15.7.4.2.4.
Similar
Recommendations and Visual Search
15.7.4.2.5.
Inventory
optimization across the value chain
15.7.4.2.6.
Customer
Experience Management and Retail Automation
15.7.4.2.7.
Content
Management
15.7.4.2.8.
Localizing
assortment for a store
15.7.4.2.9.
Others
15.7.4.3.
New
Zealand AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization
Size
15.7.4.3.1.
Startups
15.7.4.3.2.
Small
and Medium Organizations
15.7.4.3.3.
Large
Organizations
15.7.4.4.
New
Zealand AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
15.7.4.4.1.
Apparel
15.7.4.4.2.
Accessories
15.7.4.4.3.
Footwear
15.7.4.4.4.
Beauty
and Cosmetics
15.7.4.4.5.
Others
15.7.4.5.
New
Zealand AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
15.7.4.5.1.
Designers
15.7.4.5.2.
Manufacturers
15.7.4.5.3.
Retailers
15.7.4.5.4.
Planners
15.7.4.5.5.
Market
researchers and Merchandisers
15.7.4.5.6.
Category
Heads
15.7.4.5.7.
Store
Frontend Employees / Fashion stores
15.7.4.5.8.
Others
15.7.5. Australia
15.7.5.1.
Australia
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
15.7.5.1.1.
Solutions
15.7.5.1.2.
Services
15.7.5.2.
Australia
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
15.7.5.2.1.
Fashion
trend forecasting
15.7.5.2.2.
Spotting
winning products and Automatic Tagging
15.7.5.2.3.
Demand
forecasting
15.7.5.2.4.
Similar
Recommendations and Visual Search
15.7.5.2.5.
Inventory
optimization across the value chain
15.7.5.2.6.
Customer
Experience Management and Retail Automation
15.7.5.2.7.
Content
Management
15.7.5.2.8.
Localizing
assortment for a store
15.7.5.2.9.
Others
15.7.5.3.
Australia
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
15.7.5.3.1.
Startups
15.7.5.3.2.
Small
and Medium Organizations
15.7.5.3.3.
Large
Organizations
15.7.5.4.
Australia
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
15.7.5.4.1.
Apparel
15.7.5.4.2.
Accessories
15.7.5.4.3.
Footwear
15.7.5.4.4.
Beauty
and Cosmetics
15.7.5.4.5.
Others
15.7.5.5.
Australia
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
15.7.5.5.1.
Designers
15.7.5.5.2.
Manufacturers
15.7.5.5.3.
Retailers
15.7.5.5.4.
Planners
15.7.5.5.5.
Market
researchers and Merchandisers
15.7.5.5.6.
Category
Heads
15.7.5.5.7.
Store
Frontend Employees / Fashion stores
15.7.5.5.8.
Others
15.7.6. South Korea
15.7.6.1.
South
Korea AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
15.7.6.1.1.
Solutions
15.7.6.1.2.
Services
15.7.6.2.
South
Korea AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
15.7.6.2.1.
Fashion
trend forecasting
15.7.6.2.2.
Spotting
winning products and Automatic Tagging
15.7.6.2.3.
Demand
forecasting
15.7.6.2.4.
Similar
Recommendations and Visual Search
15.7.6.2.5.
Inventory
optimization across the value chain
15.7.6.2.6.
Customer
Experience Management and Retail Automation
15.7.6.2.7.
Content
Management
15.7.6.2.8.
Localizing
assortment for a store
15.7.6.2.9.
Others
15.7.6.3.
South
Korea AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
15.7.6.3.1.
Startups
15.7.6.3.2.
Small
and Medium Organizations
15.7.6.3.3.
Large Organizations
15.7.6.4.
South
Korea AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
15.7.6.4.1.
Apparel
15.7.6.4.2.
Accessories
15.7.6.4.3.
Footwear
15.7.6.4.4.
Beauty
and Cosmetics
15.7.6.4.5.
Others
15.7.6.5.
South
Korea AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
15.7.6.5.1.
Designers
15.7.6.5.2.
Manufacturers
15.7.6.5.3.
Retailers
15.7.6.5.4.
Planners
15.7.6.5.5.
Market
researchers and Merchandisers
15.7.6.5.6.
Category
Heads
15.7.6.5.7.
Store
Frontend Employees / Fashion stores
15.7.6.5.8.
Others
15.7.7. Southeast Asia
15.7.7.1.
Southeast
Asia AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
15.7.7.1.1.
Solutions
15.7.7.1.2.
Services
15.7.7.2.
Southeast
Asia AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
15.7.7.2.1.
Fashion
trend forecasting
15.7.7.2.2.
Spotting
winning products and Automatic Tagging
15.7.7.2.3.
Demand
forecasting
15.7.7.2.4.
Similar
Recommendations and Visual Search
15.7.7.2.5.
Inventory
optimization across the value chain
15.7.7.2.6.
Customer
Experience Management and Retail Automation
15.7.7.2.7.
Content
Management
15.7.7.2.8.
Localizing
assortment for a store
15.7.7.2.9.
Others
15.7.7.3.
Southeast
Asia AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
15.7.7.3.1.
Startups
15.7.7.3.2.
Small
and Medium Organizations
15.7.7.3.3.
Large
Organizations
15.7.7.4.
Southeast
Asia AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
15.7.7.4.1.
Apparel
15.7.7.4.2.
Accessories
15.7.7.4.3.
Footwear
15.7.7.4.4.
Beauty
and Cosmetics
15.7.7.4.5.
Others
15.7.7.5.
Southeast
Asia AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
15.7.7.5.1.
Designers
15.7.7.5.2.
Manufacturers
15.7.7.5.3.
Retailers
15.7.7.5.4.
Planners
15.7.7.5.5.
Market researchers
and Merchandisers
15.7.7.5.6.
Category
Heads
15.7.7.5.7.
Store
Frontend Employees / Fashion stores
15.7.7.5.8.
Others
15.7.7.6.
Southeast
Asia AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Country
15.7.7.6.1.
Indonesia
15.7.7.6.2.
Thailand
15.7.7.6.3.
Malaysia
15.7.7.6.4.
Singapore
15.7.7.6.5.
Rest of
Southeast Asia
15.7.8. Rest of Asia Pacific
15.7.8.1.
Rest of
Asia Pacific AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
15.7.8.1.1.
Solutions
15.7.8.1.2.
Services
15.7.8.2.
Rest of
Asia Pacific AI in Fashion Market Revenue (US$ Mn) and Forecasts, By
Application
15.7.8.2.1.
Fashion
trend forecasting
15.7.8.2.2.
Spotting
winning products and Automatic Tagging
15.7.8.2.3.
Demand
forecasting
15.7.8.2.4.
Similar
Recommendations and Visual Search
15.7.8.2.5.
Inventory
optimization across the value chain
15.7.8.2.6.
Customer
Experience Management and Retail Automation
15.7.8.2.7.
Content
Management
15.7.8.2.8.
Localizing
assortment for a store
15.7.8.2.9.
Others
15.7.8.3.
Rest of
Asia Pacific AI in Fashion Market Revenue (US$ Mn) and Forecasts, By
Organization Size
15.7.8.3.1.
Startups
15.7.8.3.2.
Small
and Medium Organizations
15.7.8.3.3.
Large
Organizations
15.7.8.4.
Rest of
Asia Pacific AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
15.7.8.4.1.
Apparel
15.7.8.4.2.
Accessories
15.7.8.4.3.
Footwear
15.7.8.4.4.
Beauty and
Cosmetics
15.7.8.4.5.
Others
15.7.8.5.
Rest of
Asia Pacific AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
15.7.8.5.1.
Designers
15.7.8.5.2.
Manufacturers
15.7.8.5.3.
Retailers
15.7.8.5.4.
Planners
15.7.8.5.5.
Market
researchers and Merchandisers
15.7.8.5.6.
Category
Heads
15.7.8.5.7.
Store
Frontend Employees / Fashion stores
15.7.8.5.8.
Others
15.8. Key Segment for Channeling Investments
15.8.1. By Country
15.8.2. By Component
15.8.3. By Application
15.8.4. By Organization Size
15.8.5. By Category
15.8.6. By End User
16. Middle East and Africa AI in Fashion Market
Analysis and Forecasts, 2022 – 2030
16.1. Overview
16.1.1. Middle East and Africa AI in Fashion Market Revenue
(US$ Mn)
16.2. Middle East and Africa AI in Fashion Market
Revenue (US$ Mn) and Forecasts, By Component
16.2.1. Solutions
16.2.2. Services
16.3. Middle East and Africa AI in Fashion Market
Revenue (US$ Mn) and Forecasts, By Application
16.3.1. Fashion trend forecasting
16.3.2. Spotting winning products and Automatic
Tagging
16.3.3. Demand forecasting
16.3.4. Similar Recommendations and Visual Search
16.3.5. Inventory optimization across the value chain
16.3.6. Customer Experience Management and Retail
Automation
16.3.7. Content Management
16.3.8. Localizing assortment for a store
16.3.9. Others
16.4. Middle East and Africa AI in Fashion Market
Revenue (US$ Mn) and Forecasts, By Organization Size
16.4.1. Startups
16.4.2. Small and Medium Organizations
16.4.3. Large Organizations
16.5. Middle East and Africa AI in Fashion Market
Revenue (US$ Mn) and Forecasts, By Category
16.5.1. Apparel
16.5.2. Accessories
16.5.3. Footwear
16.5.4. Beauty and Cosmetics
16.5.5. Others
16.6. Middle East and Africa AI in Fashion Market
Revenue (US$ Mn) and Forecasts, By End User
16.6.1. Designers
16.6.2. Manufacturers
16.6.3. Retailers
16.6.4. Planners
16.6.5. Market researchers and Merchandisers
16.6.6. Category Heads
16.6.7. Store Frontend Employees / Fashion stores
16.6.8. Others
16.7. Middle East and Africa AI in Fashion Market
Revenue (US$ Mn) and Forecasts, By Country
16.7.1. Saudi Arabia
16.7.1.1.
Saudi
Arabia AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
16.7.1.1.1.
Solutions
16.7.1.1.2.
Services
16.7.1.2.
Saudi
Arabia AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
16.7.1.2.1.
Fashion
trend forecasting
16.7.1.2.2.
Spotting
winning products and Automatic Tagging
16.7.1.2.3.
Demand
forecasting
16.7.1.2.4.
Similar
Recommendations and Visual Search
16.7.1.2.5.
Inventory
optimization across the value chain
16.7.1.2.6.
Customer
Experience Management and Retail Automation
16.7.1.2.7.
Content
Management
16.7.1.2.8.
Localizing
assortment for a store
16.7.1.2.9.
Others
16.7.1.3.
Saudi
Arabia AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization
Size
16.7.1.3.1.
Startups
16.7.1.3.2.
Small
and Medium Organizations
16.7.1.3.3.
Large
Organizations
16.7.1.4.
Saudi
Arabia AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
16.7.1.4.1.
Apparel
16.7.1.4.2.
Accessories
16.7.1.4.3.
Footwear
16.7.1.4.4.
Beauty
and Cosmetics
16.7.1.4.5.
Others
16.7.1.5.
Saudi
Arabia AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
16.7.1.5.1.
Designers
16.7.1.5.2.
Manufacturers
16.7.1.5.3.
Retailers
16.7.1.5.4.
Planners
16.7.1.5.5.
Market researchers
and Merchandisers
16.7.1.5.6.
Category
Heads
16.7.1.5.7.
Store
Frontend Employees / Fashion stores
16.7.1.5.8.
Others
16.7.2. UAE
16.7.2.1.
UAE AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
16.7.2.1.1.
Solutions
16.7.2.1.2.
Services
16.7.2.2.
UAE AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
16.7.2.2.1.
Fashion
trend forecasting
16.7.2.2.2.
Spotting
winning products and Automatic Tagging
16.7.2.2.3.
Demand
forecasting
16.7.2.2.4.
Similar
Recommendations and Visual Search
16.7.2.2.5.
Inventory
optimization across the value chain
16.7.2.2.6.
Customer
Experience Management and Retail Automation
16.7.2.2.7.
Content
Management
16.7.2.2.8.
Localizing
assortment for a store
16.7.2.2.9.
Others
16.7.2.3.
UAE AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
16.7.2.3.1.
Startups
16.7.2.3.2.
Small
and Medium Organizations
16.7.2.3.3.
Large
Organizations
16.7.2.4.
UAE AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
16.7.2.4.1.
Apparel
16.7.2.4.2.
Accessories
16.7.2.4.3.
Footwear
16.7.2.4.4.
Beauty
and Cosmetics
16.7.2.4.5.
Others
16.7.2.5.
UAE AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
16.7.2.5.1.
Designers
16.7.2.5.2.
Manufacturers
16.7.2.5.3.
Retailers
16.7.2.5.4.
Planners
16.7.2.5.5.
Market
researchers and Merchandisers
16.7.2.5.6.
Category
Heads
16.7.2.5.7.
Store
Frontend Employees / Fashion stores
16.7.2.5.8.
Others
16.7.3. Egypt
16.7.3.1.
Egypt AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
16.7.3.1.1.
Solutions
16.7.3.1.2.
Services
16.7.3.2.
Egypt AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
16.7.3.2.1.
Fashion
trend forecasting
16.7.3.2.2.
Spotting
winning products and Automatic Tagging
16.7.3.2.3.
Demand
forecasting
16.7.3.2.4.
Similar
Recommendations and Visual Search
16.7.3.2.5.
Inventory
optimization across the value chain
16.7.3.2.6.
Customer
Experience Management and Retail Automation
16.7.3.2.7.
Content
Management
16.7.3.2.8.
Localizing
assortment for a store
16.7.3.2.9.
Others
16.7.3.3.
Egypt AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
16.7.3.3.1.
Startups
16.7.3.3.2.
Small
and Medium Organizations
16.7.3.3.3.
Large
Organizations
16.7.3.4.
Egypt AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
16.7.3.4.1.
Apparel
16.7.3.4.2.
Accessories
16.7.3.4.3.
Footwear
16.7.3.4.4.
Beauty
and Cosmetics
16.7.3.4.5.
Others
16.7.3.5.
Egypt AI
in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
16.7.3.5.1.
Designers
16.7.3.5.2.
Manufacturers
16.7.3.5.3.
Retailers
16.7.3.5.4.
Planners
16.7.3.5.5.
Market
researchers and Merchandisers
16.7.3.5.6.
Category
Heads
16.7.3.5.7.
Store
Frontend Employees / Fashion stores
16.7.3.5.8.
Others
16.7.4. Kuwait
16.7.4.1.
Kuwait
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
16.7.4.1.1.
Solutions
16.7.4.1.2.
Services
16.7.4.2.
Kuwait
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
16.7.4.2.1.
Fashion
trend forecasting
16.7.4.2.2.
Spotting
winning products and Automatic Tagging
16.7.4.2.3.
Demand
forecasting
16.7.4.2.4.
Similar
Recommendations and Visual Search
16.7.4.2.5.
Inventory
optimization across the value chain
16.7.4.2.6.
Customer
Experience Management and Retail Automation
16.7.4.2.7.
Content
Management
16.7.4.2.8.
Localizing
assortment for a store
16.7.4.2.9.
Others
16.7.4.3.
Kuwait
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
16.7.4.3.1.
Startups
16.7.4.3.2.
Small
and Medium Organizations
16.7.4.3.3.
Large
Organizations
16.7.4.4.
Kuwait
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
16.7.4.4.1.
Apparel
16.7.4.4.2.
Accessories
16.7.4.4.3.
Footwear
16.7.4.4.4.
Beauty
and Cosmetics
16.7.4.4.5.
Others
16.7.4.5.
Kuwait
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
16.7.4.5.1.
Designers
16.7.4.5.2.
Manufacturers
16.7.4.5.3.
Retailers
16.7.4.5.4.
Planners
16.7.4.5.5.
Market
researchers and Merchandisers
16.7.4.5.6.
Category
Heads
16.7.4.5.7.
Store
Frontend Employees / Fashion stores
16.7.4.5.8.
Others
16.7.5. South Africa
16.7.5.1.
South
Africa AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
16.7.5.1.1.
Solutions
16.7.5.1.2.
Services
16.7.5.2.
South
Africa AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
16.7.5.2.1.
Fashion
trend forecasting
16.7.5.2.2.
Spotting
winning products and Automatic Tagging
16.7.5.2.3.
Demand
forecasting
16.7.5.2.4.
Similar
Recommendations and Visual Search
16.7.5.2.5.
Inventory
optimization across the value chain
16.7.5.2.6.
Customer
Experience Management and Retail Automation
16.7.5.2.7.
Content
Management
16.7.5.2.8.
Localizing
assortment for a store
16.7.5.2.9.
Others
16.7.5.3.
South
Africa AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization
Size
16.7.5.3.1.
Startups
16.7.5.3.2.
Small
and Medium Organizations
16.7.5.3.3.
Large
Organizations
16.7.5.4.
South
Africa AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
16.7.5.4.1.
Apparel
16.7.5.4.2.
Accessories
16.7.5.4.3.
Footwear
16.7.5.4.4.
Beauty
and Cosmetics
16.7.5.4.5.
Others
16.7.5.5.
South
Africa AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
16.7.5.5.1.
Designers
16.7.5.5.2.
Manufacturers
16.7.5.5.3.
Retailers
16.7.5.5.4.
Planners
16.7.5.5.5.
Market researchers
and Merchandisers
16.7.5.5.6.
Category
Heads
16.7.5.5.7.
Store
Frontend Employees / Fashion stores
16.7.5.5.8.
Others
16.7.6. Rest of Middle East & Africa
16.7.6.1.
Rest of
Middle East & Africa AI in Fashion Market Revenue (US$ Mn) and Forecasts,
By Component
16.7.6.1.1.
Solutions
16.7.6.1.2.
Services
16.7.6.2.
Rest of
Middle East & Africa AI in Fashion Market Revenue (US$ Mn) and Forecasts,
By Application
16.7.6.2.1.
Fashion
trend forecasting
16.7.6.2.2.
Spotting
winning products and Automatic Tagging
16.7.6.2.3.
Demand
forecasting
16.7.6.2.4.
Similar
Recommendations and Visual Search
16.7.6.2.5.
Inventory
optimization across the value chain
16.7.6.2.6.
Customer
Experience Management and Retail Automation
16.7.6.2.7.
Content
Management
16.7.6.2.8.
Localizing
assortment for a store
16.7.6.2.9.
Others
16.7.6.3.
Rest of
Middle East & Africa AI in Fashion Market Revenue (US$ Mn) and Forecasts,
By Organization Size
16.7.6.3.1.
Startups
16.7.6.3.2.
Small
and Medium Organizations
16.7.6.3.3.
Large
Organizations
16.7.6.4.
Rest of
Middle East & Africa AI in Fashion Market Revenue (US$ Mn) and Forecasts,
By Category
16.7.6.4.1.
Apparel
16.7.6.4.2.
Accessories
16.7.6.4.3.
Footwear
16.7.6.4.4.
Beauty
and Cosmetics
16.7.6.4.5.
Others
16.7.6.5.
Rest of
Middle East & Africa AI in Fashion Market Revenue (US$ Mn) and Forecasts, By
End User
16.7.6.5.1.
Designers
16.7.6.5.2.
Manufacturers
16.7.6.5.3.
Retailers
16.7.6.5.4.
Planners
16.7.6.5.5.
Market
researchers and Merchandisers
16.7.6.5.6.
Category
Heads
16.7.6.5.7.
Store
Frontend Employees / Fashion stores
16.7.6.5.8.
Others
16.8. Key Segment for Channeling Investments
16.8.1. By Country
16.8.2. By Component
16.8.3. By Application
16.8.4. By Organization Size
16.8.5. By Category
16.8.6. By End User
17. Latin America AI in Fashion Market Analysis
and Forecasts, 2022 – 2030
17.1. Overview
17.1.1. Latin America AI in Fashion Market Revenue
(US$ Mn)
17.2. Latin America AI in Fashion Market Revenue
(US$ Mn) and Forecasts, By Component
17.2.1. Solutions
17.2.2. Services
17.3. Latin America AI in Fashion Market Revenue
(US$ Mn) and Forecasts, By Application
17.3.1. Fashion trend forecasting
17.3.2. Spotting winning products and Automatic
Tagging
17.3.3. Demand forecasting
17.3.4. Similar Recommendations and Visual Search
17.3.5. Inventory optimization across the value chain
17.3.6. Customer Experience Management and Retail
Automation
17.3.7. Content Management
17.3.8. Localizing assortment for a store
17.3.9. Others
17.4. Latin America AI in Fashion Market Revenue
(US$ Mn) and Forecasts, By Organization Size
17.4.1. Startups
17.4.2. Small and Medium Organizations
17.4.3. Large Organizations
17.5. Latin America AI in Fashion Market Revenue
(US$ Mn) and Forecasts, By Category
17.5.1. Apparel
17.5.2. Accessories
17.5.3. Footwear
17.5.4. Beauty and Cosmetics
17.5.5. Others
17.6. Latin America AI in Fashion Market Revenue
(US$ Mn) and Forecasts, By End User
17.6.1. Designers
17.6.2. Manufacturers
17.6.3. Retailers
17.6.4. Planners
17.6.5. Market researchers and Merchandisers
17.6.6. Category Heads
17.6.7. Store Frontend Employees / Fashion stores
17.6.8. Others
17.7. Latin America AI in Fashion Market Revenue
(US$ Mn) and Forecasts, By Country
17.7.1. Brazil
17.7.1.1.
Brazil
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
17.7.1.1.1.
Solutions
17.7.1.1.2.
Services
17.7.1.2.
Brazil
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
17.7.1.2.1.
Fashion
trend forecasting
17.7.1.2.2.
Spotting
winning products and Automatic Tagging
17.7.1.2.3.
Demand
forecasting
17.7.1.2.4.
Similar
Recommendations and Visual Search
17.7.1.2.5.
Inventory
optimization across the value chain
17.7.1.2.6.
Customer
Experience Management and Retail Automation
17.7.1.2.7.
Content
Management
17.7.1.2.8.
Localizing
assortment for a store
17.7.1.2.9.
Others
17.7.1.3.
Brazil
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
17.7.1.3.1.
Startups
17.7.1.3.2.
Small and
Medium Organizations
17.7.1.3.3.
Large
Organizations
17.7.1.4.
Brazil
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
17.7.1.4.1.
Apparel
17.7.1.4.2.
Accessories
17.7.1.4.3.
Footwear
17.7.1.4.4.
Beauty
and Cosmetics
17.7.1.4.5.
Others
17.7.1.5.
Brazil
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
17.7.1.5.1.
Designers
17.7.1.5.2.
Manufacturers
17.7.1.5.3.
Retailers
17.7.1.5.4.
Planners
17.7.1.5.5.
Market
researchers and Merchandisers
17.7.1.5.6.
Category
Heads
17.7.1.5.7.
Store
Frontend Employees / Fashion stores
17.7.1.5.8.
Others
17.7.2. Argentina
17.7.2.1.
Argentina
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
17.7.2.1.1.
Solutions
17.7.2.1.2.
Services
17.7.2.2.
Argentina
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Application
17.7.2.2.1.
Fashion
trend forecasting
17.7.2.2.2.
Spotting
winning products and Automatic Tagging
17.7.2.2.3.
Demand
forecasting
17.7.2.2.4.
Similar
Recommendations and Visual Search
17.7.2.2.5.
Inventory
optimization across the value chain
17.7.2.2.6.
Customer
Experience Management and Retail Automation
17.7.2.2.7.
Content
Management
17.7.2.2.8.
Localizing
assortment for a store
17.7.2.2.9.
Others
17.7.2.3.
Argentina
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Organization Size
17.7.2.3.1.
Startups
17.7.2.3.2.
Small
and Medium Organizations
17.7.2.3.3.
Large
Organizations
17.7.2.4.
Argentina
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
17.7.2.4.1.
Apparel
17.7.2.4.2.
Accessories
17.7.2.4.3.
Footwear
17.7.2.4.4.
Beauty
and Cosmetics
17.7.2.4.5.
Others
17.7.2.5.
Argentina
AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
17.7.2.5.1.
Designers
17.7.2.5.2.
Manufacturers
17.7.2.5.3.
Retailers
17.7.2.5.4.
Planners
17.7.2.5.5.
Market
researchers and Merchandisers
17.7.2.5.6.
Category
Heads
17.7.2.5.7.
Store
Frontend Employees / Fashion stores
17.7.2.5.8.
Others
17.7.3. Rest of Latin America
17.7.3.1.
Rest of
Latin America AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Component
17.7.3.1.1.
Solutions
17.7.3.1.2.
Services
17.7.3.2.
Rest of
Latin America AI in Fashion Market Revenue (US$ Mn) and Forecasts, By
Application
17.7.3.2.1.
Fashion
trend forecasting
17.7.3.2.2.
Spotting
winning products and Automatic Tagging
17.7.3.2.3.
Demand
forecasting
17.7.3.2.4.
Similar
Recommendations and Visual Search
17.7.3.2.5.
Inventory
optimization across the value chain
17.7.3.2.6.
Customer
Experience Management and Retail Automation
17.7.3.2.7.
Content
Management
17.7.3.2.8.
Localizing
assortment for a store
17.7.3.2.9.
Others
17.7.3.3.
Rest of
Latin America AI in Fashion Market Revenue (US$ Mn) and Forecasts, By
Organization Size
17.7.3.3.1.
Startups
17.7.3.3.2.
Small
and Medium Organizations
17.7.3.3.3.
Large
Organizations
17.7.3.4.
Rest of
Latin America AI in Fashion Market Revenue (US$ Mn) and Forecasts, By Category
17.7.3.4.1.
Apparel
17.7.3.4.2.
Accessories
17.7.3.4.3.
Footwear
17.7.3.4.4.
Beauty
and Cosmetics
17.7.3.4.5.
Others
17.7.3.5.
Rest of
Latin America AI in Fashion Market Revenue (US$ Mn) and Forecasts, By End User
17.7.3.5.1.
Designers
17.7.3.5.2.
Manufacturers
17.7.3.5.3.
Retailers
17.7.3.5.4.
Planners
17.7.3.5.5.
Market
researchers and Merchandisers
17.7.3.5.6.
Category
Heads
17.7.3.5.7.
Store
Frontend Employees / Fashion stores
17.7.3.5.8.
Others
17.8. Key Segment for Channeling Investments
17.8.1. By Country
17.8.2. By Component
17.8.3. By Application
17.8.4. By Organization Size
17.8.5. By Category
17.8.6. By End User
18. Competitive Benchmarking
18.1. Brand Benchmarking
18.2. Market Share Analysis, 2021
18.3. Global Presence and Growth Strategies
18.3.1. Mergers and Acquisitions
18.3.2. Product Launches
18.3.3. Investments Trends
18.3.4. R&D Initiatives
19. Player Profiles
19.1. Adobe
19.1.1. Company Details
19.1.2. Company Overview
19.1.3. Product Offerings
19.1.4. Key Developments
19.1.5. Financial Analysis
19.1.6. SWOT Analysis
19.1.7. Business Strategies
19.2. AWS
19.2.1. Company Details
19.2.2. Company Overview
19.2.3. Product Offerings
19.2.4. Key Developments
19.2.5. Financial Analysis
19.2.6. SWOT Analysis
19.2.7. Business Strategies
19.3. Meta (Facebook)
19.3.1. Company Details
19.3.2. Company Overview
19.3.3. Product Offerings
19.3.4. Key Developments
19.3.5. Financial Analysis
19.3.6. SWOT Analysis
19.3.7. Business Strategies
19.4. FINDMINE
19.4.1. Company Details
19.4.2. Company Overview
19.4.3. Product Offerings
19.4.4. Key Developments
19.4.5. Financial Analysis
19.4.6. SWOT Analysis
19.4.7. Business Strategies
19.5. Google
19.5.1. Company Details
19.5.2. Company Overview
19.5.3. Product Offerings
19.5.4. Key Developments
19.5.5. Financial Analysis
19.5.6. SWOT Analysis
19.5.7. Business Strategies
19.6. Heuritech
19.6.1. Company Details
19.6.2. Company Overview
19.6.3. Product Offerings
19.6.4. Key Developments
19.6.5. Financial Analysis
19.6.6. SWOT Analysis
19.6.7. Business Strategies
19.7. IBM
19.7.1. Company Details
19.7.2. Company Overview
19.7.3. Product Offerings
19.7.4. Key Developments
19.7.5. Financial Analysis
19.7.6. SWOT Analysis
19.7.7. Business Strategies
19.8. kloud9
19.8.1. Company Details
19.8.2. Company Overview
19.8.3. Product Offerings
19.8.4. Key Developments
19.8.5. Financial Analysis
19.8.6. SWOT Analysis
19.8.7. Business Strategies
19.9. Lily AI
19.9.1. Company Details
19.9.2. Company Overview
19.9.3. Product Offerings
19.9.4. Key Developments
19.9.5. Financial Analysis
19.9.6. SWOT Analysis
19.9.7. Business Strategies
19.10. Mad Street Den Inc
19.10.1. Company Details
19.10.2. Company Overview
19.10.3. Product Offerings
19.10.4. Key Developments
19.10.5. Financial Analysis
19.10.6. SWOT Analysis
19.10.7. Business Strategies
19.11. Microsoft
19.11.1. Company Details
19.11.2. Company Overview
19.11.3. Product Offerings
19.11.4. Key Developments
19.11.5. Financial Analysis
19.11.6. SWOT Analysis
19.11.7. Business Strategies
19.12. Oracle
19.12.1. Company Details
19.12.2. Company Overview
19.12.3. Product Offerings
19.12.4. Key Developments
19.12.5. Financial Analysis
19.12.6. SWOT Analysis
19.12.7. Business Strategies
19.13. SAP SE
19.13.1. Company Details
19.13.2. Company Overview
19.13.3. Product Offerings
19.13.4. Key Developments
19.13.5. Financial Analysis
19.13.6. SWOT Analysis
19.13.7. Business Strategies
19.14. Stylumia Intelligence Technology Pvt Ltd
19.14.1. Company Details
19.14.2. Company Overview
19.14.3. Product Offerings
19.14.4. Key Developments
19.14.5. Financial Analysis
19.14.6. SWOT Analysis
19.14.7. Business Strategies
19.15. Other Market Participants
20. Key Findings
Note: This ToC is tentative
and can be changed according to the research study conducted during the course
of report completion.
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and Enterprise User.
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