In 2024, retail e-commerce revenues from apparel and accessories sales in the United States amounted to ***** billion U.S. dollars, an increase compared to previous years. Statista Market Insights estimates that by 2029 the market revenue will increase to nearly *** billion U.S. dollars.

In the fashion market worldwide in 2024, the apparel segment generated the highest revenue, reaching approximately 457.23 billion U.S. dollars. The accessories segment ranked second with around 185.6 billion U.S. dollars, while footwear followed with about 128.06 billion U.S. dollars.

Dataset Overview

Over 10000 entries of ethically mined female fashion data (clothing).

Column Descirptors

name,brand,sizes,skus,originalPrice,promotionalPrice,discountPercentage

Image Credits

Generated using Adobe firefly.

In the measured time period, June 2025 saw the highest figures for online traffic to the fashion retail website zara.com. According to the data, desktop and mobile visits to zara.com reached 98 million visits that month.

The revenue change in the fashion e-commerce market in the United States was forecast to decrease between 2024 and 2029 by in total *** percentage points. This overall decrease does not happen continuously, notably not in 2026. According to this forecast, in 2029, the indicator will have decreased for the third consecutive year to **** percent. Find more information concerning the Nordics and Israel.The Statista Market Insights cover a broad range of additional markets.

16,000 Zara UK Fashion Products in CSV Format

Unlock fashion retail intelligence with our comprehensive Zara UK products dataset. This premium collection contains 16,000 products from Zara's UK online store, providing detailed insights into one of the world's leading fast-fashion retailers. Perfect for fashion trend analysis, pricing strategies, competitive research, and machine learning applications.

Dataset Overview

• Language: English
• Coverage: Men's, women's, and children's fashion
• File Size: ~30MB
• Data Freshness: Recently collected (2025)

Complete Data Fields Included

Product Information

• name: Complete product titles and descriptions
• brand: Brand identification (Zara)
• category: Product categories (tops, bottoms, dresses, accessories)
• description: Detailed item descriptions and features
• composition: Fabric composition and material details
• breadcrumbs: Navigation path and product hierarchy

Pricing and Promotions

• price: Current prices in GBP
• old_price: Original prices before discounts
• discount: Discount percentages and savings
• promotions: Active promotional campaigns
• currency: GBP for UK market analysis

Product Attributes

• color: Available color variations
• sizes: Size ranges and availability
• images: High-resolution product image URLs
• url: Direct product page links

Technical Fields

• uniq_id: Unique product identifiers
• scraped_at: Data collection timestamps

Key Use Cases

Fashion Trend Analysis

• Track seasonal trends and popular styles
• Analyze color preferences and combinations
• Monitor fashion trend evolution
• Predict upcoming fashion movements

Competitive Intelligence

• Study Zara's pricing strategies
• Analyze product mix and category focus
• Monitor inventory and availability patterns
• Compare market positioning

E-commerce Analytics

• Category performance analysis
• Price optimization strategies
• Inventory planning insights
• Customer preference mapping

Machine Learning Applications

• Fashion recommendation systems
• Price prediction models
• Trend forecasting algorithms
• Image recognition training data

Data Quality Features

• Clean, Validated Data: Pre-processed and error-checked
• Consistent Formatting: Standardized structure across records
• No Duplicates: Unique products only
• Complete Coverage: Entire Zara UK catalog included
• Fresh Collection: Recently scraped for current relevance

Target Industries

Fashion Retailers

• Competitive benchmarking
• Trend adoption strategies
• Pricing optimization
• Product development insights

Technology Companies

• AI training datasets
• Fashion analytics platforms
• E-commerce enhancement
• Style recommendation engines

Market Research

• Industry analysis reports
• Brand performance tracking
• Consumer behavior studies
• Trend forecasting services

Academic Research

• Fashion industry studies
• Business case studies
• Data science applications
• Sustainability research

Licensing Options

Commercial License

• Full business usage rights
• Team sharing permissions
• Resale of processed insights
• API integration allowed

Academic License

• Non-commercial research use
• Educational institution sharing
• Publication rights included
• Discounted pricing available

Delivery Methods

• Instant

Kuwait E-Commerce Transactions: Value: Lifestyle: Fashion & Apparel data was reported at 842.063 USD in 01 Dec 2024. This records an increase from the previous number of 129.972 USD for 28 Nov 2024. Kuwait E-Commerce Transactions: Value: Lifestyle: Fashion & Apparel data is updated daily, averaging 29,429.615 USD from Dec 2018 (Median) to 01 Dec 2024, with 2016 observations. The data reached an all-time high of 228,908.590 USD in 26 Nov 2021 and a record low of 129.972 USD in 28 Nov 2024. Kuwait E-Commerce Transactions: Value: Lifestyle: Fashion & Apparel data remains active status in CEIC and is reported by Grips Intelligence Inc.. The data is categorized under Global Database’s Kuwait – Table KW.GI.EC: E-Commerce Transactions: by Category.

The revenue in the fashion e-commerce market in Europe was modeled to be******* ******* U.S. dollars in 2024. Between 2017 and 2024, the revenue rose by ************* U.S. dollars, though the increase followed an uneven trajectory rather than a consistent upward trend. The revenue will steadily rise by ************* U.S. dollars over the period from 2024 to 2030, 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 Fashion.

Snapshot img

US Online Fashion Retail Market Size 2025-2029

The us online fashion retail market size is forecast to increase by USD 303.9 billion at a CAGR of 15.6% between 2024 and 2029.

The Online Fashion Retail Market in the US is experiencing significant growth, driven by the rising trend of online shopping and the increasing popularity of sports apparel and footwear. Consumers are increasingly turning to the convenience and accessibility of online platforms to meet their fashion needs. The sports apparel and footwear industry's growth is further fueling market expansion, as consumers seek out the latest trends and styles in athletic wear. However, this market is not without challenges. Security and privacy concerns related to consumer data have emerged as a significant obstacle. With the increasing amount of personal information being shared online, retailers must prioritize data protection and privacy to maintain consumer trust. Failure to do so could result in reputational damage and lost sales. Retailers must invest in robust cybersecurity measures and transparent data handling practices to mitigate these risks and capitalize on the market's potential.

What will be the size of the US Online Fashion Retail Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

In the dynamic US online fashion retail market, high-end fashion brands are embracing e-commerce optimization, leveraging data analytics tools to personalize shopping experiences and boost sales. Blockchain technology is revolutionizing the industry by ensuring supply chain transparency and ethical production, resonating with consumers' growing demand for sustainable sourcing. Resale platforms and second-hand clothing are gaining traction, as unisex fashion and body positivity continue to influence purchasing decisions. Performance marketing, affiliate marketing, and social commerce are key strategies driving growth, with fashion photography and fashion blogging shaping consumer trends. Brands prioritize customer data privacy while implementing customer loyalty programs and subscription services. Trend analysis, size inclusivity, and fashion forecasting are essential components of successful digital marketing automation. Luxury goods and vintage fashion are thriving, with mobile wallet integration streamlining transactions. Omnichannel retail, fashion journalism, fashion styling, and live streaming are shaping the future of the industry.

How is this market segmented?

The market 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-userWomenMenKidsProductApparelFootwearsBags and accessoriesTypeMass marketPremiumLuxuryPlatformMobile AppsWeb PortalsPrice RangeEconomyMid-RangePremiumGeographyNorth AmericaUS

By End-user Insights

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

The online fashion retail market in the US is experiencing significant growth, driven by several key trends and factors. Product reviews and customer satisfaction play a crucial role in influencing purchasing decisions, with consumers relying on authentic feedback to make informed choices. Influencer marketing is also a major force, as fashion influencers and celebrities shape trends and promote products through social media channels. Virtual reality and augmented reality technologies are transforming the shopping experience, allowing customers to virtually try on clothes and visualize how they would look. Big data and recommendation algorithms are being leveraged to personalize shopping experiences, while trend forecasting ensures that retailers stay ahead of the curve. Content marketing, machine learning, and data analytics are essential tools for fashion brands, helping them to understand customer preferences and tailor their offerings accordingly. Textile suppliers and apparel manufacturers are integrating sustainable practices to cater to the growing demand for eco-friendly fashion. Mobile commerce and mobile app development are critical for reaching customers on the go, with mobile responsiveness and user interface design key considerations. Conversion rate optimization, data security, and payment gateways are essential for ensuring a seamless shopping experience. Customer service, inventory management, order fulfillment, and shipping logistics are all crucial components of a successful online fashion retail business. Social media marketing, email marketing, and fashion designers collaborations are effective strategies for reaching and engaging customers. Size and fit, fast fashion, and formal wear are popular categories, with quality control and brand loyalty key differentiators.

1) Data introduction • Womens-ecommerce-clothing-reviews dataset is a dataset containing 23,000 customer reviews and ratings.

2) Data utilization (1) Womens-ecommerce-clothing-reviews data has characteristics that: • We aim for high-quality NLP and multivariate analysis with a dataset consisting of 10 functional variables such as clothing, age, and review title and 23,486 rows. (2) Womens-ecommerce-clothing-reviews data can be used to: • Rating prediction: Develop machine learning models to predict the ratings customers might give based on review text and support automated review analysis. • Trend analysis: Companies can analyze data to identify trends and patterns in customer preferences and support inventory management and marketing strategies.

The global e-commerce apparel market size was USD 691.29 billion in 2024 & is projected to grow from USD 745.55 billion in 2025 to USD 1364.71 billion by 2033.
Report Scope:

Global C2C Fashion Store User Behaviour Analysis

Analyzing Buyer and Seller Profiles across Countries

By Jeffrey Mvutu Mabilama [source]

About this dataset

Welcome to an exciting exploration of global C2C fashion store user behaviour! This dataset seeks to serve as a benchmark by providing valuable insights into e-commerce users, enabling you to make informed decisions and effectively grow your business. Let's dive right into the data!

This dataset contains records on over 9 million registered users from a successful online C2C fashion store launched in Europe around 2009 and later expanded worldwide. It includes metrics such as country, gender, active users, top buyers/sellers/ratio*, products bought/sold/listed* and social network features (likes/follows). Furthermore this is just a preview of much larger data set which contains more detailed information including product listings, comments from listed products etc.

E-commerce has become an essential part of our lives - people are now accustomed to buying anything with a few clicks online. With so many unknown elements that come with not only selling but also providing good customer service - understanding user behavior is key for success in this domain. By utilizing this dataset you can answer questions such as 'how many customers are likely to drop off after years of using my service?,' 'are my users active enough compared to those in this dataset?,” or “how likely are people from other countries signing up in a C2C website?' In addition, if you think this kind odf dataset may be useful don't forget do show your support or appreciation by leaving an upvote or comment on the page!

My Telegram bot will answer any queries regarding the datasets as well allow you see contact me directly if necessary; also please don't forget check out the *[data.world page](https://data.world/jfreex/e-commerce-users-of-a-french-c2c

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For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

This dataset provides a useful overview of global users' behavior in an online C2C fashion store. The data includes metrics such as buyers, top buyers, top buyer ratio, female buyers and their respective ratios, etc., per country. This dataset can be used to gain insights into how global audiences interact with the store and draw conclusions from comparison between different countries.

In order to make use of this dataset, one must first familiarize themselves with the various metrics included in it. These include: country; number of overall buyers; number of top buyers; ratio(s) of them (top buyer to total buyer); female-related data (buyers, top female buyers); bought-to-wish/like ration (top and non-top separately); overall products bought/wished/liked; total products sold by tops sellers in the same country versus what they sold outside the country; mean value for product stats (sold/listed/etc...) from looking at the whole population or just users that make those actions multiple times; average days for user offline /lurking around on the site without posting anything or buying anything etc.; mean follower(s) count(s).

Using this data one could generate reports about user behavior within particular countries either manually by computing all statistics or by using libraries like Pandas or SQL with queries made toward this datasets which consists of columns representing individual countries with all values necessary to answer any questions you might have regarding how many people buy something out there per region and what type they are –– Are they Top Buyer? Female? Etc.

Further potential work could involve utilising machine learning tools such as clustering algorithms to group similar customers together based on certain traits like age group, profession etc., so that personalised marketing promotions can be targetted at these customer clusters rather than aiming more generic ads at everyone!

Finally combined with other related product datasets which is available upon request via JfreexDatasets_bot provided by Jfreex team , this dataset can become another powerful tool providing you actionable insights into customers today — allowing you build better strategies towards improving customer experience tomorrow!

Research Ideas

• Analyzing the conversion rate of users on a website - Comparing user metrics like the overall number of buyers, female buyers, top buyers ratio and top buyer gender can help determine if users in certain countries are more or less likely to convert into customers. Additionally, comparing average metrics like products bought or offl...

France E-Commerce Transactions: Value: Lifestyle: Fashion & Apparel data was reported at 964,589.996 USD in 10 May 2025. This records a decrease from the previous number of 980,729.172 USD for 09 May 2025. France E-Commerce Transactions: Value: Lifestyle: Fashion & Apparel data is updated daily, averaging 960,141.370 USD from Dec 2018 (Median) to 10 May 2025, with 2324 observations. The data reached an all-time high of 5,457,158.004 USD in 06 Dec 2020 and a record low of 267,433.360 USD in 16 Mar 2020. France E-Commerce Transactions: Value: Lifestyle: Fashion & Apparel data remains active status in CEIC and is reported by Grips Intelligence Inc.. The data is categorized under Global Database’s France – Table FR.GI.EC: E-Commerce Transactions: by Category.

Asos E-Commerce Dataset - 30,845 products, text classification dataset

Using web scraping, we collected information on over 30,845 clothing items from the Asos website. The dataset can be applied in E-commerce analytics in the fashion industry. The dataset is similar to SheIn E-Commerce Dataset.

💴 For Commercial Usage: To discuss your requirements, learn about the price and buy the dataset, leave a request on our website to buy the dataset

Dataset Info

For each item, we extracted:

• url - link to the item on the website
• name - item's name
• size - sizes available on the website
• category - product's category
• price - item's price
• color - item's color
• SKU - unique identifier of the item
• date - date of web scraping; for all items - March 11, 2023
• description - additional description, including product's brand, composition, and care instructions, in JSON format
• images - photographs from the item description

🧩 This is just an example of the data. Leave a request here to learn more

🚀 You can learn more about our high-quality unique datasets here

keywords: web scraping dataset, dataset marketplace, web scraping data, e-commerce dataset, e-commerce marketplace, e-commerce marketplace scraping dataset, e-commerce sales dataset, ecommerce clothing site, e-commerce user behavior dataset, e-commerce text dataset, e-commerce product dataset, text dataset, ratings, product recommendation, text classification, text mining dataset, text data

Snapshot img

India Online Fashion Retail Market Size 2025-2029

The India online fashion retail market size is forecast to increase by USD 36.01 billion, at a CAGR of 22.2% between 2024 and 2029.

Major Market Trends & Insights

By Product - Apparel segment was valued at USD 8.26 billion in 2022
By Gender - Women segment accounted for the largest market revenue share in 2022

Market Size & Forecast

Market Opportunities: USD 314.31 billion
Market Future Opportunities: USD 36.01 billion 
CAGR : 22.2%

Market Summary

The market has witnessed significant growth, fueled by the increasing adoption of digital technologies and the rise in internet and smartphone penetration. According to recent reports, India's online fashion market is projected to reach USD 35 billion by 2025, growing at a steady pace. This expansion is driven by the convenience and accessibility offered by e-commerce platforms, which allow consumers to shop from the comfort of their homes. Moreover, the presence of various payment options, including credit/debit cards, digital wallets, and cash on delivery, has further boosted the market's growth. In contrast, traditional brick-and-mortar stores face challenges such as high rental costs and limited product offerings, making e-commerce an attractive alternative.
The fashion industry's online segment includes various categories, such as apparel, footwear, and accessories, with apparel being the largest and fastest-growing segment. As the market continues to evolve, we can expect to see increased competition, innovative marketing strategies, and personalized shopping experiences.

What will be the size of the India Online Fashion Retail Market during the forecast period?

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

The market exhibits a significant presence in the country's burgeoning e-commerce sector. According to recent estimates, the market currently accounts for over 3% of India's total retail sector, with a growth rate of approximately 25% year-on-year. Looking forward, this figure is projected to reach nearly 5% by 2025. A comparison of key performance indicators reveals that online fashion retailers in India have achieved impressive customer engagement. For instance, the average customer lifetime value stands at INR 25,000, while the conversion rate for mobile commerce reaches 35%. Furthermore, the market's growth is driven by factors such as increasing internet penetration, improving digital infrastructure, and the rising popularity of social commerce.
In terms of competition, players in the online fashion retail space continue to invest in various strategies to differentiate themselves. These include website traffic analysis, customer segmentation models, and personalization algorithms, among others. Despite challenges such as payment processing fees, e-commerce logistics, and returns and exchanges, the market's potential for growth remains strong. In conclusion, the market presents a compelling opportunity for businesses looking to expand their reach and capitalize on the country's growing digital economy. With a projected growth rate of 25% year-on-year and a customer lifetime value of INR 25,000, the market's potential for revenue generation is significant.
Furthermore, the increasing popularity of mobile commerce and social commerce trends underscores the importance of a robust digital presence for fashion retailers.

How is this India Online Fashion Retail Market segmented?

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

Product

  Apparel
  Footwear
  Bags and accessories


Gender

  Women
  Men
  Children


Price Range

  Economy
  Mid-Range
  Premium


Platform

  Mobile Apps
  Web Portals


Geography

  APAC

    India

By Product Insights

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

In the dynamic and evolving online fashion retail landscape in India, the apparel segment experiences consistent growth. Consumers prioritize fashionable and comfortable clothing, driving retailers to cater to diverse consumer segments. The market encompasses a wide range of clothing categories for men, women, children, and infants. Top wear apparel, including tops, blouses, dresses, casual shirts, formal shirts, T-shirts, sweaters, sweatshirts, tank tops, and vests, currently accounts for a significant market share. Meanwhile, bottom wear, consisting of trousers, jeans, jeggings, pants, shorts, and skirts, also experiences steady demand. Intimates and sleepwear, such as pajamas, bathrobes, shapewear, slips, socks, underwear, and briefs, are essential categories that cater to consumers' daily needs.

Children's and inf

In 2024, Asia ranked first by revenue in the fashion e-commerce market among the 5 regions presented in the ranking. Asia's revenue amounted to ************** U.S. dollars, while the Americas and Europe, the second and third regions, had records amounting to ************** U.S. dollars and ************** U.S. dollars, respectively.Further information about the methodology, more market segments, and metrics can be found on the dedicated Market Insights page on Fashion.

Context

This dataset contains product listings from SSENSE. SSENSE is a multi-brand retailer specializing in the sales of designer fashion and high-end streetwear. The data, extracted from their websites via Python and Beautiful Soup, provides a snapshot of current trends, prices, and offerings in the luxury fashion e-commerce sector.

Content

Each entry in the dataset contains the following information:
Brand: The fashion brand or designer of the product.
Description: A brief description of the product, highlighting key features.
Price_USD: The retail price of the product in US dollars.
Type: Indicates the target gender for the product, classified as 'men' or 'women'.

Inspiration

Trend Analysis in Luxury Fashion: Investigate current trends in luxury fashion, including popular brands, product types, and pricing.
Gender-Based Market Insights: Explore differences in product offerings and pricing strategies between men's and women's fashion.
Brand and Price Segmentation: Analyze how different brands are positioned within SSENSE's portfolio in terms of pricing and target audience.

Argentina E-Commerce Transactions: Value: Lifestyle: Fashion & Apparel data was reported at 160.711 USD in 16 Dec 2024. This records an increase from the previous number of 153.669 USD for 10 Dec 2024. Argentina E-Commerce Transactions: Value: Lifestyle: Fashion & Apparel data is updated daily, averaging 23,132.001 USD from Dec 2018 (Median) to 16 Dec 2024, with 2110 observations. The data reached an all-time high of 209,717.424 USD in 01 Nov 2022 and a record low of 153.505 USD in 03 Dec 2024. Argentina E-Commerce Transactions: Value: Lifestyle: Fashion & Apparel data remains active status in CEIC and is reported by Grips Intelligence Inc.. The data is categorized under Global Database’s Argentina – Table AR.GI.EC: E-Commerce Transactions: by Category.

Success.ai’s Fashion & Apparel Dataset for Latin America unlocks access to verified contact data in a high-growth region. Target buyers, merchandisers, e-commerce leads, and brand managers in fashion houses, retail chains, marketplaces, and suppliers throughout LATAM.
Ideal for B2B SaaS, logistics, manufacturing, and cross-border trade targeting this vibrant industry.

Why Use Success.ai for LATAM Fashion Data?
- Focused by Region: Brazil, Mexico, Argentina, Colombia, Chile & more.
- Cross-Channel Roles: E-commerce, retail, luxury sales, sourcing, and design.
- Verified Data with LinkedIn Matches

Data Points Include:
- Contact name, job title, company
- Work email, phone number (where available)
- Country, city, and region
- Fashion category (e.g. footwear, accessories, apparel, beauty)
- LinkedIn profile (if available)

Use Cases:
- B2B Sales to Apparel Brands
- Wholesale & Export Partnerships
- SaaS & POS Tools for Retail
- Logistics & Fulfillment Services
- Fashion Event Promotion

Industries Served:
- Fashion & Apparel
- Luxury Goods
- Beauty & Wellness
- Retail Tech
- Logistics & Sourcing

Why Success.ai?
- Best Price Guarantee
- High-quality LATAM market intelligence
- GDPR & Local Regulation Compliant
- Custom Filters: Role, Country, Category

The Plus-Size Fashion E-commerce market has witnessed remarkable growth over recent years, emerging as a vital segment within the broader fashion industry. With a current market size estimated at $X billion and a historical growth rate of approximately X% over the past five years, it reflects a significant shift tow