According to a 2024 survey of executives and experts in the fashion industry, consumers can expect the price of their apparel, footwear, and accessories to increase in 2024. Almost ** percent of respondents said that prices will increase, with *********** of total respondents expecting this increase to be greater than five percent.

The price of clothing made from linen has seen the greatest increase in prices in the United States in 2022, compared to 2021. The cost of such items has risen by almost ** percent. Cotton apparel items also saw a considerable increase in cost. General prices of consumer goods have risen considerably in the United States in 2022, due to high levels of inflation.

US Tariff Impact on Market

U.S. tariffs on imports, especially in the fashion sector, have had a notable impact on the fashion e-commerce market. Tariffs on apparel and accessories, particularly those from China, have increased production costs for many U.S.-based e-commerce retailers.

As a result, the prices of fashion items sold online have risen, which may slow down consumer spending in the short term. U.S. companies relying on international suppliers for manufacturing are feeling the strain, pushing some to seek alternative, tariff-free regions for sourcing.

However, the impact may drive some companies to increase domestic manufacturing, creating local production opportunities. Over the long term, despite tariff-induced cost increases, the demand for fashion e-commerce is expected to remain robust due to the convenience and broad appeal of online shopping.

➤➤➤ Get More Insights about US Tariff Impact Analysis @ https://market.us/report/fashion-e-commerce-market/free-sample/

• Economic Impact: Increased tariffs raise costs for U.S. fashion e-commerce companies, potentially leading to higher prices for consumers and affecting sales.
• Geographical Impact: U.S. fashion retailers are facing higher prices for imported apparel and accessories from China, pushing them to explore other sourcing options.
• Business Impact: Tariffs increase operational costs for fashion e-commerce businesses, leading to potential price hikes and margin pressures, slowing growth in price-sensitive segments.

Impact Percentage on Sectors

• Apparel and Clothing: +7-9%
• Accessories: +5-7%

Graph and download economic data for Consumer Price Index for All Urban Consumers: Apparel in U.S. City Average (CPIAPPSL) from Jan 1947 to Jul 2025 about apparel, urban, consumer, CPI, inflation, price index, indexes, price, and USA.

The price per unit in the apparel market in the United Kingdom was modeled to be **** U.S. dollars in 2024. Between 2018 and 2024, the price per unit rose by **** U.S. dollars, though the increase followed an uneven trajectory rather than a consistent upward trend. The price per unit will steadily rise by **** U.S. dollars over the period from 2024 to 2029, reflecting a clear upward trend.Further information about the methodology, more market segments, and metrics can be found on the dedicated Market Insights page on Apparel.

Monthly indexes and percentage changes for selected sub-groups of the clothing and footwear component of the Consumer Price Index (CPI), not seasonally adjusted, for Canada, provinces, Whitehorse and Yellowknife. Data are presented for the corresponding month of the previous year, the previous month and the current month. The base year for the index is 2002=100.

Latvia Consumer Price Index (CPI): % Change of Same Mth PY: Clothing and Footwear: Clothing: Sewing and Cleaning of Clothing data was reported at 5.200 % in Oct 2018. This records an increase from the previous number of 4.200 % for Sep 2018. Latvia Consumer Price Index (CPI): % Change of Same Mth PY: Clothing and Footwear: Clothing: Sewing and Cleaning of Clothing data is updated monthly, averaging 2.700 % from Jan 1998 (Median) to Oct 2018, with 250 observations. The data reached an all-time high of 32.500 % in Sep 2007 and a record low of -9.300 % in Jan 2010. Latvia Consumer Price Index (CPI): % Change of Same Mth PY: Clothing and Footwear: Clothing: Sewing and Cleaning of Clothing data remains active status in CEIC and is reported by Central Statistical Bureau of Latvia. The data is categorized under Global Database’s Latvia – Table LV.I010: Consumer Price Index: Percentage Change of Same Month Previous Year.

Latvia Consumer Price Index (CPI): % Change of Same Mth PY: Clothing and Footwear: Clothing: Garments data was reported at 1.900 % in Oct 2018. This records an increase from the previous number of -0.300 % for Sep 2018. Latvia Consumer Price Index (CPI): % Change of Same Mth PY: Clothing and Footwear: Clothing: Garments data is updated monthly, averaging 0.200 % from Jan 1998 (Median) to Oct 2018, with 250 observations. The data reached an all-time high of 11.700 % in Feb 1998 and a record low of -10.400 % in Feb 2010. Latvia Consumer Price Index (CPI): % Change of Same Mth PY: Clothing and Footwear: Clothing: Garments data remains active status in CEIC and is reported by Central Statistical Bureau of Latvia. The data is categorized under Global Database’s Latvia – Table LV.I010: Consumer Price Index: Percentage Change of Same Month Previous Year.

Prices of consumer goods have risen considerably in the European Union in 2022. Fashion has not been an exception to this, although some companies are raising prices more than others. In the EU, the average price of Zara products has risen by ** percent in 2022 compared to the previous year.

Clothing retailing revenue is forecast to fall at a compound annual rate of 0.8% over the five years through 2024-25 to £47.3 billion. This decline predominantly stems from weak performance in 2020-21 thanks to the pandemic. Since then, clothing sales have been propped up by the dramatic increase in photos and videos posted online; strong demand for fast, affordable fashion; and the introduction of credit and financing services like buy-now-pay-later platforms, which have allowed consumers to better manage their budgets and splash the cash on new clothes. Despite their recent growth, clothing retailers have faced several challenges. Online-only retailers like ASOS, Shein and Temu have grown in popularity thanks to their versatility, siphoning sales away from the British high street. Further, the fashion industry's success relies on selling mountains of clothing at low prices, but this has come with devasting environmental and social effects – and times are changing. Retailers have also contended with tightening disposable incomes, with the cost-of-living crisis seeing consumers think twice before adding that new outfit to their baskets. Despite consumer confidence improving since the height of the cost-of-living crisis in 2022-23, it remains weak, limiting spending on clothing. Still, in 2024-25, revenue is expected to bump up by 1.5%. The average profit margin has inched down over the past five years thanks to discounting activity. Clothing retailers will face a tough start to 2025-26, with hikes to the National Living Wage and National Insurance contributions set to ramp up costs. Despite this, opportunities for growth remain. Sustainability remains key, with consumers embracing upcycling, rental options and resale schemes, like ITX’s buy-back initiative. Meanwhile, influencer marketing is shifting towards authenticity as consumers favour genuine engagement over polished content and social commerce is set to boom. Despite e-commerce growth, physical stores remain relevant, with brands like Uniqlo and Abercrombie expanding. AI is also transforming retail, enhancing personalisation, inventory management, and sustainability. To stay competitive, retailers are likely to innovate across digital, in-store and operational strategies. Those that fail to adapt risk not benefitting from a potentially lucrative market. Revenue in is slated to grow at a compound annual rate of 1.1% over the five years through 2029-30 to £50.1 billion, when the average industry profit margin is slated to be 5.8%, weighed down by competition and rising investment in efficiency initiatives.

In April 2023, the price of Baby Clothes was $39,215 per ton (CIF, Spain), experiencing a 5.2% increase compared to the previous month.

The global plus-size women's clothing market is experiencing robust growth, driven by increasing awareness of body positivity, evolving fashion trends embracing inclusivity, and a rising number of women identifying as plus-size. Let's assume, for illustrative purposes, a 2025 market size of $50 billion and a Compound Annual Growth Rate (CAGR) of 7% over the forecast period (2025-2033). This suggests a market value exceeding $90 billion by 2033. Key drivers include the expanding plus-size consumer base, increased online shopping accessibility, and the rise of brands specifically catering to this demographic. Growing demand for diverse styles, sizes, and fabrics, along with a shift towards sustainable and ethically sourced clothing, also contribute to market expansion. While challenges such as negative body image perceptions and limited availability in certain regions persist, the overall trajectory indicates significant future potential. The market is segmented by product type (dresses, tops, bottoms, etc.), price range, distribution channel (online vs. offline), and geography. Key players, including Adrianna Papell, ASOS Curve, Eloquii, and H&M, are actively shaping the market landscape through innovative designs, targeted marketing, and expanding their online presence. The continuous evolution of fashion trends is playing a significant role in the market’s growth. A rising preference for comfortable yet stylish clothing, coupled with the increased acceptance of diverse body types in media and popular culture, significantly fuels market expansion. The growth is further accelerated by brands offering inclusive sizing and diverse styles, ensuring there is something for everyone within the plus-size consumer base. While pricing remains a factor for some consumers, the increasing affordability of plus-size clothing across various price points broadens market accessibility. Future growth will likely depend on sustained positive body image promotion, technological advancements in personalized fitting and design, and continued investment in sustainable and ethically produced plus-size apparel.

Certainly! Let's walk through a hypothetical case study on retail price optimization to understand how it can be implemented and its potential benefits.

Case Study: Retail Price Optimization for a Clothing Store

Company Background: Imagine a clothing store called "Fashionista" that sells a wide range of apparel and accessories. Fashionista operates both physical stores and an online e-commerce platform. The company wants to optimize its pricing strategy to maximize revenue and improve competitiveness in the market.

Challenges Faced: Fashionista is facing several challenges in pricing its products effectively:

1. Competitive Landscape: The retail industry is highly competitive, with multiple competitors offering similar products. Fashionista wants to gain a competitive edge by offering attractive prices without sacrificing profitability.

2. Inventory Management: Fashionista needs to manage its inventory effectively by setting prices that balance supply and demand. Optimizing prices based on inventory levels can help prevent overstocking or understocking of products.

3. Seasonal and Trend Variations: Fashion trends change rapidly, and demand for specific items fluctuates throughout the year. Fashionista needs to adapt its prices to reflect these seasonal and trend variations to capture maximum sales opportunities.

Solution: Retail Price Optimization Implementation

1. Data Collection and Analysis: Fashionista collects data on various factors that can influence pricing decisions, such as historical sales data, competitor prices, customer demographics, and website analytics. This data is analyzed to identify patterns, trends, and correlations.

2. Demand Forecasting: Using advanced analytics techniques, Fashionista develops demand forecasting models that consider factors such as seasonality, trends, promotional activities, and external factors (e.g., economic conditions, holidays) to predict customer demand accurately. This helps in estimating the demand for different products at different price points.

3. Price Elasticity Analysis: Fashionista conducts price elasticity analysis to understand how changes in price affect demand for its products. This analysis helps identify price points at which demand becomes more or less responsive, allowing Fashionista to set optimal prices that maximize revenue.

4. Competitor Analysis: Fashionista continuously monitors and analyzes competitor prices and promotions. This information helps them make informed pricing decisions, such as matching or undercutting competitor prices strategically.

5. Dynamic Pricing: With the insights gained from data analysis and demand forecasting, Fashionista implements dynamic pricing. This involves adjusting prices in real-time based on factors like demand, inventory levels, competitor prices, and customer segmentation. Dynamic pricing allows Fashionista to respond quickly to market changes and optimize prices for maximum revenue generation.

Benefits and Outcomes:

1. Increased Revenue: By implementing retail price optimization techniques, Fashionista can set optimal prices that maximize revenue. Adjusting prices based on demand and competitor analysis ensures they remain competitive while still maintaining profitability.

2. Improved Inventory Management: By aligning prices with inventory levels and demand forecasts, Fashionista can optimize stock levels, reducing the risk of overstocking or understocking. This leads to cost savings and improved operational efficiency.

3. Enhanced Competitiveness: Fashionista gains a competitive edge by monitoring competitor prices and adjusting its own prices accordingly. This allows them to attract price-sensitive customers and increase market share.

4. Better Customer Satisfaction: Offering competitive prices based on customer demand and preferences improves customer satisfaction. Fashionista can also leverage dynamic pricing to provide personalized discounts or promotions, enhancing the overall customer experience.

5. Agile and Adaptive Pricing Strategy: With the ability to respond quickly to market changes, Fashionista can adapt its pricing strategy to capitalize on trends, seasonal variations, and other external factors. This flexibility helps them stay ahead of the competition and meet customer expectations.

Conclusion: By implementing retail price optimization techniques, Fashionista successfully addresses pricing challenges and achieves multiple benefits such as increased revenue, improved inventory management, enhanced competitiveness, better customer satisfaction, and an agile pricing strategy. This case study demonstrates how data-driven pricing strategies

can lead to significant improvements in retail operations and overall business performance.

Second-Hand Fashion Dataset

Update Sep. 19th, 2024

• Some problematic and duplicate images have been removed from version 2.- All "gold dataset" data from station1 and station3 has been moved to a single test100 folder.- JSON errors have been fixed - all JSON files should be parsed correctly now.

The new dataset has 31,638 items (+ about 100 items in test100 folder) instead of the 31,997 items in version 2.

Overview

The dataset originates from projects focused on the sorting of used clothes within a sorting facility. The primary objective is to classify each garment into one of several categories to determine its ultimate destination: reuse, reuse outside Sweden (export), recycling, repair, remake, or thermal waste.

The dataset has 31,638 clothing items, a massive update from the 3,000 items in version 1. The dataset collection started under the Vinnova funded project "AI for resource-efficient circular fashion" in Spring, 2022 and involves collaboration among three institutions: RISE Research Institutes of Sweden AB, Wargön Innovation AB, and Myrorna AB. The dataset has received further support through the EU project, CISUTAC (cisutac.eu).

Project page

• Webpage: second-hand-fashion- Contact: farrukh.nauman@ri.se

Dataset Details

• The dataset contains 31,638 clothing items, each with a unique item ID in a datetime format. The items are divided into three stations: station1, station2, and station3. The station1 and station2 folders contain images and annotations from Wargön Innovation AB, while the station3 folder contains data from Myrorna AB. Each clothing item has three images and a JSON file containing annotations.

• Three images are provided for each clothing item: 1. Front view. 2. Back view. 3. Brand label close-up. About 4000-5000 brand images are missing because of privacy concerns: people's hands, faces, etc. Some clothing items did not have a brand label to begin with.

• Image resolutions are primarily in two sizes: 1280x720 and 1920x1080. The background of the images is a table that used a measuring tape prior to January 2023, but later images have a square grid pattern with each square measuring 10x10 cm.

• Each JSON file contains a list of annotations, some of which require nuanced interpretation (see labels.py for the options): - usage: Arguably the most critical label, usage indicates the garment's intended pathway. Options include 'Reuse,' 'Repair,' 'Remake,' 'Recycle,' 'Export' (reuse outside Sweden), and 'Energy recovery' (thermal waste). About 99% of the garments fall into the 'Reuse,' 'Export,' or 'Recycle' categories. - trend: This field refers to the general style of the garment, not a time-dependent trend as in some other datasets (e.g., Visuelle 2.0). It might be more accurately labeled as 'style.' - material: Material annotations are mostly based on the readings from a Near Infrared (NIR) scanner and in some cases from the garment's brand label. - Damage-related attributes include: - condition (1-5 scale, 5 being the best) - pilling (1-5 scale, 5 meaning no pilling) - stains, holes, smell (each with options 'None,' 'Minor,' 'Major'). Note: 'holes' and 'smell' were introduced after November 17th, 2022, and stains previously only had 'Yes'/'No' options. For station1 and station2, we introduced additional damage location labels to assist in damage detection:

    "damageimage": "back",
    "damageloc": "bottom left",
    "damage": "stain ",
    "damage2image": "front",
    "damage2loc": "None",
    "damage2": "",
    "damage3image": "back",
    "damage3loc": "bottom right",
    "damage3": "stain"
  
  Taken from `labels_2024_04_05_08_47_35.json` file. Additionally, we annotated a few hundred images with bounding box annotations that we aim to release at a later date.  - `comments`: The comments field is mostly empty, but sometimes contains important information about the garment, such as a detailed text description of the damage. 
  

• Whenever possible, ISO standards have been followed to define these attributes on a 1-5 scale (e.g., pilling).

• Gold dataset: 100 garments were annotated multiple times by different annotators for annotator agreement comparisons. These 100 garments are placed inside a separate folder test100.

• The data has been annotated by a group of expert second-hand sorters at Wargön Innovation AB and Myrorna AB.

• Some attributes, such as price, should be considered with caution. Many distinct pricing models exist in the second-hand industry: - Price by weight - Price by brand and demand (similar to first-hand fashion) - Generic pricing at a fixed value (e.g., 1 Euro or 10 SEK) Wargön Innovation AB does not set the prices in practice and their prices are suggestive only (station1 and station2). Myrorna AB (station3), in contrast, does resale and sets the prices.

Comments

• We received feedback on our version 1 that some images were too blurry or had poor lighting. The image quality has slightly improved, but largely remains similar to release 1. - Some users did not prefer a tar.gz format that we uploaded in version 1 of the dataset. We have now switched to .zip for convenience.- Extra care was taken not to leak personal information. This is why you will not see any entries for annotator attribute in the JSON files in station1/sep2023 since people used their real names. Since then, we used internally assigned IDs. - Many brand images contained people's hands, faces, or other personal information. We have removed about 4000-5000 brand images for privacy reasons. - Please inform us immediately if you find any personal information revelations in the dataset: - Farrukh Nauman (RISE AB): farrukh.nauman@ri.se, - Susanne Eriksson (Wargön Innovation AB): susanne.eriksson@wargoninnovation.se, - Gabriella Engstrom (Wargön Innovation AB): gabriella.engstrom@wargoninnovation.se.

We went through 100k images four times to ensure no personal information is leaked, but we are human and can make mistakes.

Partners

The data collection for this dataset has been carried out in collaboration with the following partners:

1. RISE Research Institutes of Sweden AB: RISE is a leading research institute dedicated to advancing innovation and sustainability across various sectors, including fashion and textiles.

2. Wargön Innovation AB: Wargön Innovation is an expert in sustainable and circular fashion solutions, contributing valuable insights and expertise to the dataset creation.

3. Myrorna AB: Myrorna is Sweden's oldest chain of stores for collecting clothes and furnishings that can be reused.

License

CC-BY 4.0. Please refer to the LICENSE file for more details.

Acknowledgments

This dataset was made possible through the collaborative efforts of RISE Research Institutes of Sweden AB, Wargön Innovation AB, and Myrorna AB, with funding from Vinnova and support from the EU project CISUTAC. We extend our gratitude to all the expert second-hand sorters and annotators who contributed their expertise to this project.

The second-hand clothing trade sector has been confronted with different developments over the past five years. During the Corona pandemic, sales plummeted in 2020 and 2021. Due to the Corona restrictions, all Second-Hand suppliers could only accept and resell goods to a very limited extent, so that the sale of Second-Hand goods was at times only possible with high price discounts. In particular, the stationary retail trade with used clothing suffered from the interim closures of retail stores. At the same time, demand was burdened by steadily increasing trade barriers, such as import restrictions and punitive tariffs, but also by the sharp rise in logistics costs. Industry sales then grew again in 2022 as secondhand clothing becomes more popular in the face of rising consumer prices and increasing sustainability awareness. The same applies to 2023, when the second-hand market will continue to gain momentum. Against this backdrop, an average annual decline in sales of 1.1% was observed over the past five years. In the current year, sales are expected to increase from €2.8 billion to €2.3 billion compared with the previous year.Over the next five years, average sales are expected to grow by 0.9% per year to €2.4 billion. The positive development of the industry will mainly result from the continuously growing interest of consumers in second-hand fashion. The greatest influence on the development of sales in the industry is the increasing environmental awareness among the population. An increasingly large group of consumers is taking a critical view of apparel manufacturing due to the high water, environmental and worker impacts, especially when produced in low-wage countries. This increases the willingness to resort to well-preserved second-hand fashion, which has the reputation of having a better environmental balance. In addition, increasing urbanization in Germany is also playing a role. In urban centers in particular, consumer willingness to spend is high, a trend from which industry players are also benefiting. Similarly, market penetration will be increased by improving consumer accessibility via online channels, as this will allow consumers outside of metropolitan areas to be increasingly targeted.

India Consumer Price Index (CPI): Clothing and Footwear data was reported at 195.600 2012=100 in Mar 2025. This records an increase from the previous number of 195.400 2012=100 for Feb 2025. India Consumer Price Index (CPI): Clothing and Footwear data is updated monthly, averaging 142.600 2012=100 from Jan 2011 (Median) to Mar 2025, with 171 observations. The data reached an all-time high of 195.600 2012=100 in Mar 2025 and a record low of 82.800 2012=100 in Jan 2011. India Consumer Price Index (CPI): Clothing and Footwear data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under Global Database’s India – Table IN.QG003: Memo Items: Consumer Price Index. [COVID-19-IMPACT]

Learn about the forecasted growth of the baby clothes market in the UK, with an anticipated increase in market volume and value over the next decade.

According to a survey from January 2023, the strategy of nearly ********** of the online clothing stores in Czechia was to keep the prices the same in 2023. However, ** percent of them already knew the prices of their products would increase.

The Thai clothing market, while exhibiting a relatively modest Compound Annual Growth Rate (CAGR) of 0.70% from 2019-2033, presents a complex landscape shaped by various dynamic factors. With a market size measured in millions (exact figures require further specification), this sector is driven by several key elements. The rise of e-commerce platforms has significantly broadened market access for both domestic and international brands, fueling growth, particularly in the younger demographic. Tourism, a crucial component of the Thai economy, also boosts demand, especially for casual wear and traditional Thai clothing. Furthermore, increasing disposable incomes among the burgeoning middle class contribute to higher consumer spending on apparel. However, several trends are reshaping the market. Sustainability concerns are growing, pushing consumers towards eco-friendly and ethically produced clothing. The increasing popularity of fast fashion, while offering affordability, also presents challenges related to waste management and ethical sourcing. Furthermore, the rise of personalized and customized clothing options is diversifying the market, catering to individual preferences. Restraints on growth include fluctuating raw material prices (particularly cotton), increasing labor costs, and intense competition from both regional and international brands. The market is segmented into production, consumption, import/export (both value and volume), and price trends, providing detailed insights into specific market dynamics. Analyzing these segments reveals insights into areas such as domestic production capabilities, the reliance on imports for certain fabrics or finished products, and the pricing strategies employed by various players. Key players in the Thai clothing market include Textile Prestige Public Co Ltd, Nan Yang Textile Group, Thai Toray Textile Mills Public Co Ltd, Thanulux Public Co Ltd, Hong Seng Knitting Co Ltd, Luckytex (Thailand) Public Co Ltd, and Thai Acrylic Fibre Co Ltd, among others. These companies represent a range of specializations, from textile production to apparel manufacturing and retail. Regional data focused specifically on Thailand allows for a granular understanding of market performance across different geographical areas within the country. The study period of 2019-2033, with a base year of 2025, provides a comprehensive perspective on both historical performance and future projections. Understanding the market’s historical performance (2019-2024) is crucial for forecasting accurately. By analyzing the interplay between drivers, trends, and restraints, along with a detailed segmentation and analysis of key players, stakeholders can develop informed strategies to navigate the complexities and capitalize on opportunities within the Thai clothing market. Further research into specific market size figures, import/export details, and a deeper dive into regional variations will allow for a more precise and actionable market analysis. Recent developments include: In 2020, Thanulux officially launched Erawan Uniforms & Workwear Center and expanded its business into the Uniforms & Workwear product market.. Key drivers for this market are: Rising Disposable Income is Driving the Market, Urbanisation is Driving the Market. Potential restraints include: Supply Chain Disruptions are Restraining the Market. Notable trends are: Non-woven Textiles Segment is Expected to Witness a High Growth.

Snapshot img

Secondhand Apparel Market Size 2025-2029

The secondhand apparel market size is forecast to increase by USD 212.1 billion, at a CAGR of 14.9% between 2024 and 2029.

Major Market Trends & Insights

By End-user - Women segment was valued at USD 48.70 billion in 2023
By Type - TTSD segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 274.67 billion
Market Future Opportunities: USD 212.10 billion 
CAGR : 14.9%

Market Summary

The market is experiencing a significant shift in consumer behavior, with an increasing number of individuals opting for pre-owned clothing. According to recent studies, the global secondhand clothing market is projected to reach a value of USD 77 billion by 2025, growing at a steady pace. This growth can be attributed to the rise of resale platforms, which have made it easier for consumers to buy and sell used clothes. These platforms have also contributed to the complexity of the secondhand apparel supply chain, allowing for a more efficient and sustainable way of trading pre-owned items.
Additionally, the environmental benefits of buying secondhand clothing, such as reduced carbon emissions and waste, have become increasingly important to consumers. As a result, the market is expected to continue growing, offering businesses opportunities to tap into this expanding market and cater to the evolving needs of consumers.

What will be the size of the Secondhand Apparel Market during the forecast period?

Get Key Insights on Market Forecast (PDF) Request Free Sample

The market exhibits a consistent growth trajectory, with current sales representing approximately 30% of the global apparel market share. Looking forward, this sector is projected to expand by around 15% annually, outpacing the growth rate of the new apparel market. Notably, the market's appeal lies in its cost savings, sustainability, and access to unique and vintage items. In comparison, the new apparel market, which includes sales from retailers and manufacturers, accounts for the remaining 70% of the market share.
Despite this larger market share, the secondhand sector's growth rate surpasses that of the new apparel market, highlighting its potential significance. This trend underscores the increasing consumer preference for affordable, sustainable, and unique clothing options.

How is this Secondhand Apparel Market segmented?

The secondhand apparel industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

End-user

  Women
  Men
  Kids


Type

  TTSD
  Resale


Product Types

  Casual Wear
  Formal Wear
  Sportswear
  Vintage Clothing


Price

  Low-End
  Mid-Range
  Premium


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By End-user Insights

The women segment is estimated to witness significant growth during the forecast period.

Women dominate the market, driving its significant expansion. Sustainability and circular economy models have become increasingly popular, leading more women to purchase pre-owned clothing. This shift is influenced by factors such as environmental consciousness, the quest for unique fashion statements, and cost savings. Women can find a diverse selection of secondhand apparel on clothing resale platforms, fashion rental services, and online consignment shops. The acceptance and normalization of secondhand clothing within the fashion industry have strengthened the market's position, contributing to the growth of sustainable fashion consumption. The pre-owned clothing market is experiencing a substantial increase in customer lifetime value, with women accounting for a large portion.

The textile recycling process plays a crucial role in the industry, ensuring that clothing is authenticated, refurbished, and graded before being resold. Payment processing systems facilitate seamless transactions, while inventory management and data-driven fashion retail enable efficient operations. The market's future growth is expected to continue, with a projected increase in clothing donation programs and the integration of e-commerce platforms. Consumer behavior towards secondhand clothing is evolving, with a growing emphasis on ethical fashion consumption and return rate optimization. Garment quality assessment and apparel upcycling techniques are becoming more prevalent, contributing to the circular fashion economy. Customer segmentation in the secondhand fashion market is essential for understanding the diverse needs and preferences of various demographics.

Online brand reputation, clothing condition scoring, and supply cha