バーチャルフィッティングルーム（VFR）市場　2024-2032年

Growth Factors of Virtual Fitting Room (VFR) Market

The virtual fitting room (VFR) market size was valued at USD 4.79 billion in 2023, and the market is now projected to grow from USD 5.71 billion in 2024 to USD 25.11 billion by 2032, exhibiting a CAGR of 20.3% during the forecast period of 2024-2032.

バーチャルフィッティング ルーム (VFR) の市場規模は 2023 年に 47 億 9 千万米ドルと評価され、現在市場は 2024 年の 57 億 1 億米ドルから 2032 年までに 251 億 1 億米ドルに成長すると予測されており、2024 年から 2032 年までの予測期間中に 20.3% の CAGR を示しています。 。

Retail outlets, delivery services and trade barriers driven by the pandemic extended consumer demand for e-commerce. This change resulted in a drastic rise in online purchases and electronic means of payment. The lockdown has forced companies to reflect on their retail strategies and post-pandemic, it has become a major factor behind the virtual fitting room (VFR) market growth. Consequently, this trend will probably intensify when off-store retail transitions.

The increasing trend in online commerce makes consumers demand virtual fitting rooms since fashion retailers allow consumers to engage through mobile apps. Industry leaders such as Shopify, Walmart and Amazon are implementing app-based virtual dressing rooms with augmented reality and artificial intelligence for avatars and 3D product visualization. This trend is further promoted by social networking sites such as TikTok and Instagram since influencers assist consumers in trying on virtual garments. These changes in mobile commerce are expected to drive the virtual fitting room (VFR) market share.

Also, the increase in the volume of online consumers has put pressure on virtual fitting software with such solutions as Mobile Tailor and YourFit that will allow customers to input their body measurements and obtain a photo-realistic fitting of clothes in real time. Companies that have started adopting AR as some of their brands, for instance, Gucci through the Snapchat virtual dressing lens are the ones making customer experience and convenience better. Magic mirrors and 3D avatars are in vogue, enhancing the shopping experience. Companies such as Gap and Snapchat are now adopting virtual fitting technologies to cater for their clients in a more advanced way.

Comprehensive Analysis of Virtual Fitting Room (VFR) Market

The global market in the virtual fitting room (VFR) market and information & communication technology industry is growing exponentially because of the market segmentation. This market expansion also offers a set of detailed regional analyses based on the key supply and demand factors that affect the hardware & software IT services market. These segmentations are by types, by applications, and by end-users. The types include, In-store Virtual Mirrors, App-based Body Scanners, and Sizing Surveys Backed by 3D Body Data. The applications include, Apparel, Eyewear, Cosmetic & Beauty Products, Jewelry & Watches, and Others. The end-users include, Brick-and-Mortar Stores and Virtual/E-commerce Stores.

North America is the largest market and accounts for the highest market share throughout the given timeframe owing to the increasing penetration of augmented reality, virtual reality and artificial intelligence in retail and e-commerce sectors. Such technologies help customers increase conversion through features such as virtual fittings and digital fitting rooms. Large organised retail players are observed integrating with small e-commerce players to gain a wider consumer base and a consolidated brand image. This trend is anticipated to strengthen the leadership position of North America even further in the market.

The prominent leaders in the market are responsible for contributing to the industrial prospectus and the setting of the market trend. These players include, Else Corp (Italy), Fit Analytics (Snapchat) (Germany), FX Gear Inc. (South Korea), Magic Mirror (U.K.), MeMo Labs Inc. (U.S.), 3DLOOK Inc. (U.S.), Zugara, Inc. (U.S.), Visual Look (Spain), triMirror (U.S.) and Sensemi DMCC (UAE). These market players create a competitive structure that ensures a level playing field.

In March 2023, Zilio implemented a Pilot on Denimsmith to create a more encompassing customer experience for male online shoppers, while the company plans to release the tool for women as well.

Segmentation Table

Global Virtual Fitting Room (VFR) Market Scope

Study Period 2019-2032

Base Year 2023

Forecast Period 2024-2032

Growth Rate CAGR of 20.3% from 2024 to 2032

Historical Period 2019-2022

Unit Value (USD Billion)

Segmentation By Type, Application, End-Use, and Region

By Type

• In-store Virtual Mirrors
• App-based Body Scanners
• Sizing Surveys Backed by 3D Body Data

By Application

• Apparel
• Eyewear
• Cosmetic & Beauty Products
• Jewelry & Watches
• Others (Footwear)

By End-use

• Brick-and-Mortar Stores
• Virtual/E-commerce Stores

By Region

• North America (By Type, By Application, By End-use, and By Country)

o U.S. (By Application)

o Canada (By Application)

• Europe (By Type, By Application, By End-use, and By Country)

o U.K. (By Application)

o Germany (By Application)

o France (By Application)

o Italy (By Application)

o Rest of Europe

• Asia Pacific (By Type, By Application, By End-use, and By Country)

o China (By Application)

o Japan (By Application)

o India (By Application)

o Singapore (By Application)

o Rest of Asia Pacific

• Middle East and Africa (By Type, By Application, By End-use, and By Country)

o GCC (By Application)

o South Africa (By Application)

o Rest of Middle East & Africa

• Latin America (By Type, By Application, By End-use, and By Country)

o Brazil (By Application)

o Mexico (By Application)

• Rest of Latin America

Table of Contents

1. Introduction
1.1. Definition, By Segment
1.2. Research Methodology/Approach
1.3. Data Sources
2. Executive Summary
3. Market Dynamics
3.1. Macro and Micro Economic Indicators
3.2. Drivers, Restraints, Opportunities and Trends
4. Competition Landscape
4.1. Business Strategies Adopted by Key Players
4.2. Consolidated SWOT Analysis of Key Players
4.3. Global Virtual Fitting Room Key Players Market Share/Ranking, 2023
5. Global Virtual Fitting Room Market Size Estimates and Forecasts, By Segments, 2019-2032
5.1. Key Findings
5.2. By Type (USD)
5.2.1. In-store Virtual Mirrors
5.2.2. App-based Body Scanners
5.2.3. Sizing Surveys Backed by 3D Body Data
5.3. By Application (USD)
5.3.1. Apparel
5.3.2. Eyewear
5.3.3. Cosmetic & Beauty Products
5.3.4. Jewelry & Watches
5.3.5. Others (Footwear, etc.)
5.4. By End-use (USD)
5.4.1. Brick-and-Mortar Stores
5.4.2. Virtual/e-commerce Stores
5.5. By Region (USD)
5.5.1. North America
5.5.2. Europe
5.5.3. Asia Pacific
5.5.4. Middle East & Africa
5.5.5. Latin America
6. North America Virtual Fitting Room Market Size Estimates and Forecasts, By Segments, 2019-2032
6.1. Key Findings
6.2. By Type (USD)
6.2.1. In-store Virtual Mirrors
6.2.2. App-based Body Scanners
6.2.3. Sizing Surveys Backed by 3D Body Data
6.3. By Application (USD)
6.3.1. Apparel
6.3.2. Eyewear
6.3.3. Cosmetic & Beauty Products
6.3.4. Jewelry & Watches
6.3.5. Others (Footwear, etc.)
6.4. By End-use (USD)
6.4.1. Brick-and-Mortar Stores
6.4.2. Virtual/e-commerce Stores
6.5. By Country (USD)
6.5.1. United States
6.5.1.1. By Application
6.5.2. Canada
6.5.2.1. By Application
7. Europe Virtual Fitting Room Market Size Estimates and Forecasts, By Segments, 2019-2032
7.1. Key Findings
7.2. By Type (USD)
7.2.1. In-store Virtual Mirrors
7.2.2. App-based Body Scanners
7.2.3. Sizing Surveys Backed by 3D Body Data
7.3. By Application (USD)
7.3.1. Apparel
7.3.2. Eyewear
7.3.3. Cosmetic & Beauty Products
7.3.4. Jewelry & Watches
7.3.5. Others (Footwear, etc.)
7.4. By End-use (USD)
7.4.1. Brick-and-Mortar Stores
7.4.2. Virtual/e-commerce Stores
7.5. By Country (USD)
7.5.1. United Kingdom
7.5.1.1. By Application
7.5.2. Germany
7.5.2.1. By Application
7.5.3. France
7.5.3.1. By Application
7.5.4. Italy
7.5.4.1. By Application
7.5.5. Rest of Europe
8. Asia Pacific Virtual Fitting Room Market Size Estimates and Forecasts, By Segments, 2019-2032
8.1. Key Findings
8.2. By Type (USD)
8.2.1. In-store Virtual Mirrors
8.2.2. App-based Body Scanners
8.2.3. Sizing Surveys Backed by 3D Body Data
8.3. By Application (USD)
8.3.1. Apparel
8.3.2. Eyewear
8.3.3. Cosmetic & Beauty Products
8.3.4. Jewelry & Watches
8.3.5. Others (Footwear, etc.)
8.4. By End-use (USD)
8.4.1. Brick-and-Mortar Stores
8.4.2. Virtual/e-commerce Stores
8.5. By Country (USD)
8.5.1. China
8.5.1.1. By Application
8.5.2. Japan
8.5.2.1. By Application
8.5.3. India
8.5.3.1. By Application
8.5.4. Singapore
8.5.4.1. By Application
8.5.5. Rest of Asia Pacific
9. Middle East & Africa Virtual Fitting Room Market Size Estimates and Forecasts, By Segments, 2019-2032
9.1. Key Findings
9.2. By Type (USD)
9.2.1. In-store Virtual Mirrors
9.2.2. App-based Body Scanners
9.2.3. Sizing Surveys Backed by 3D Body Data
9.3. By Application (USD)
9.3.1. Apparel
9.3.2. Eyewear
9.3.3. Cosmetic & Beauty Products
9.3.4. Jewelry & Watches
9.3.5. Others (Footwear, etc.)
9.4. By End-use (USD)
9.4.1. Brick-and-Mortar Stores
9.4.2. Virtual/e-commerce Stores
9.5. By Country (USD)
9.5.1. GCC
9.5.1.1. By Application
9.5.2. South Africa
9.5.2.1. By Application
9.5.3. Rest of MEA
10. Latin America Virtual Fitting Room Market Size Estimates and Forecasts, By Segments, 2019-2032
10.1. Key Findings
10.2. By Type (USD)
10.2.1. In-store Virtual Mirrors
10.2.2. App-based Body Scanners
10.2.3. Sizing Surveys Backed by 3D Body Data
10.3. By Application (USD)
10.3.1. Apparel
10.3.2. Eyewear
10.3.3. Cosmetic & Beauty Products
10.3.4. Jewelry & Watches
10.3.5. Others (Footwear, etc.)
10.4. By End-use (USD)
10.4.1. Brick-and-Mortar Stores
10.4.2. Virtual/e-commerce Stores
10.5. By Country (USD)
10.5.1. Brazil
10.5.1.1. By Application
10.5.2. Mexico
10.5.2.1. By Application
10.5.3. Rest of Latin America
11. Company Profiles for Top 10 Players (Based on data availability in public domain and/or on paid databases)
11.1. Else Corp.
11.1.1. Overview
11.1.1.1. Key Management
11.1.1.2. Headquarters
11.1.1.3. Offerings/Business Segments
11.1.2. Key Details (Key details are consolidated data and not product/service specific)
11.1.2.1. Employee Size
11.1.2.2. Past and Current Revenue
11.1.2.3. Geographical Share
11.1.2.4. Business Segment Share
11.1.2.5. Recent Developments
11.2. Fit Analytics (Snapchat)
11.2.1. Overview
11.2.1.1. Key Management
11.2.1.2. Headquarters
11.2.1.3. Offerings/Business Segments
11.2.2. Key Details (Key details are consolidated data and not product/service specific)
11.2.2.1. Employee Size
11.2.2.2. Past and Current Revenue
11.2.2.3. Geographical Share
11.2.2.4. Business Segment Share
11.2.2.5. Recent Developments
11.3. FX Gear Inc.
11.3.1. Overview
11.3.1.1. Key Management
11.3.1.2. Headquarters
11.3.1.3. Offerings/Business Segments
11.3.2. Key Details (Key details are consolidated data and not product/service specific)
11.3.2.1. Employee Size
11.3.2.2. Past and Current Revenue
11.3.2.3. Geographical Share
11.3.2.4. Business Segment Share
11.3.2.5. Recent Developments
11.4. Magic Mirror
11.4.1. Overview
11.4.1.1. Key Management
11.4.1.2. Headquarters
11.4.1.3. Offerings/Business Segments
11.4.2. Key Details (Key details are consolidated data and not product/service specific)
11.4.2.1. Employee Size
11.4.2.2. Past and Current Revenue
11.4.2.3. Geographical Share
11.4.2.4. Business Segment Share
11.4.2.5. Recent Developments
11.5. MeMo Labs Inc.
11.5.1. Overview
11.5.1.1. Key Management
11.5.1.2. Headquarters
11.5.1.3. Offerings/Business Segments
11.5.2. Key Details (Key details are consolidated data and not product/service specific)
11.5.2.1. Employee Size
11.5.2.2. Past and Current Revenue
11.5.2.3. Geographical Share
11.5.2.4. Business Segment Share
11.5.2.5. Recent Developments
11.6. 3DLOOK Inc.
11.6.1. Overview
11.6.1.1. Key Management
11.6.1.2. Headquarters
11.6.1.3. Offerings/Business Segments
11.6.2. Key Details (Key details are consolidated data and not product/service specific)
11.6.2.1. Employee Size
11.6.2.2. Past and Current Revenue
11.6.2.3. Geographical Share
11.6.2.4. Business Segment Share
11.6.2.5. Recent Developments
11.7. Zugara, Inc.
11.7.1. Overview
11.7.1.1. Key Management
11.7.1.2. Headquarters
11.7.1.3. Offerings/Business Segments
11.7.2. Key Details (Key details are consolidated data and not product/service specific)
11.7.2.1. Employee Size
11.7.2.2. Past and Current Revenue
11.7.2.3. Geographical Share
11.7.2.4. Business Segment Share
11.7.2.5. Recent Developments
11.8. Visual Look
11.8.1. Overview
11.8.1.1. Key Management
11.8.1.2. Headquarters
11.8.1.3. Offerings/Business Segments
11.8.2. Key Details (Key details are consolidated data and not product/service specific)
11.8.2.1. Employee Size
11.8.2.2. Past and Current Revenue
11.8.2.3. Geographical Share
11.8.2.4. Business Segment Share
11.8.2.5. Recent Developments
11.9. triMirror
11.9.1. Overview
11.9.1.1. Key Management
11.9.1.2. Headquarters
11.9.1.3. Offerings/Business Segments
11.9.2. Key Details (Key details are consolidated data and not product/service specific)
11.9.2.1. Employee Size
11.9.2.2. Past and Current Revenue
11.9.2.3. Geographical Share
11.9.2.4. Business Segment Share
11.9.2.5. Recent Developments
11.10. Sensemi DMCC
11.10.1. Overview
11.10.1.1. Key Management
11.10.1.2. Headquarters
11.10.1.3. Offerings/Business Segments
11.10.2. Key Details (Key details are consolidated data and not product/service specific)
11.10.2.1. Employee Size
11.10.2.2. Past and Current Revenue
11.10.2.3. Geographical Share
11.10.2.4. Business Segment Share
11.10.2.5. Recent Developments

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