This statistic presents popular online shopping categories in the United States, sorted by gender. During a November 2017 survey, it was found that 71 percent of female respondents had purchased clothing online in the past 3 months. According to Loqate, a GBG solution, 49 percent of male respondents had bought clothing via internet. Fashion and apparel e-retail sales were also especially popular with Millennial online shoppers.

In the United Kingdom (UK), on a monthly basis, female shoppers were the group purchasing clothing and shoes the most online. A total 50 percent of women reported shopping online for clothes and shoes monthly as of the 2nd quarter of 2023. Male shoppers followed with 41 percent shopping online for their apparel on a monthly basis.

The Online Women's Clothing Sales industry has surged in recent years, riding on the broader wave of growth in the e-commerce sector. An increasing number of consumers are embracing online shopping, moving away from traditional brick-and-mortar stores. This shift has been underpinned by growing comfort levels with digital platforms and favorable economic conditions, such as rising disposable income and consumer spending, all of which have contributed to a robust expansion in online sales. The industry's revenue has grown at a CAGR of 2.9% over the past five years and is expected to total $61.8 billion in 2025, when revenue will climb by an estimated 2.8%. The advent of smartphones and improved internet connectivity has brought digital shopping closer to consumers, resulting in a significant climb in sales. Also, social media penetration has opened up new avenues for online retailers to target their audience with personalized marketing strategies; this, combined with an increasingly fashion-conscious female population, has driven online clothing sales. However, the landscape has become more competitive, with traditional retailers venturing into the online space to recapture their market share. This shift has primarily been driven by low entry barriers, leading to an increase in the number of new companies entering the market. Consequently, intensified price competition and rising operational costs have compressed profit, with industry profitability declining as retailers prioritize market share over sustainable earnings. The industry will continue its upward trajectory. One of the drivers for this growth will be the advent of new technologies like Augmented Reality (AR), Virtual Reality (VR) and Artificial Intelligence (AI), which will revolutionize online shopping by providing immersive and personalized experiences to consumers. Nonetheless, the industry must grapple with challenges associated with sustainability demands, data privacy issues and the continuous inflow of new companies, which will inevitably intensify competition. To remain competitive, online retailers will need to employ more sophisticated marketing strategies and prioritize providing an exceptional shopping experience for consumers. Over the next five years, revenue will hike at a CAGR of 2.5% to reach an estimated $69.8 billion in 2030.

An August 2022 survey in the U.S., UK, France, Germany, and Australia revealed that more women than men shop for fashion products online. Up to ** percent of female digital buyers had purchased clothing via the internet in the previous 12 months before the survey, while only ** percent of the men surveyed had done so.

Graph and download economic data for Producer Price Index by Industry: Women's Clothing Stores (DISCONTINUED) (PCU4481244812) from Dec 2003 to May 2015 about apparel, females, PPI, industry, inflation, price index, indexes, price, and USA.

Abstract Purpose: The general objective of this paper is to evaluate the determinant attributes of the perception of clothing quality by the users of a social network and to verify if there are any differences of evaluation of these determinants between genders. Design/methodology/approach: To achieve the objective, a survey was conducted with a sample of 295 consumers. All participants, regardless of gender, were asked to access the SurveyMonkey site link and to answer the questions regarding the quality of clothing for both men and women. Data analysis was performed using descriptive statistics and variance analysis (ANOVA). Findings: The main results show that: 1. The consumers of garments regard as highly important to take into consideration quality attributes when deciding to buy clothes, especially for women in relation to menswear; 2. Women has a higher perception than men as for the evaluation of the quality attributes of both women’s wear and menswear; and, 3. Clothing consumers, in particular consumers of women’s products, only consider to purchase such products if they have, in particular, style, fabric quality and fair price. Originality/value: This research filled in some theoretical and methodological gaps with regard to giving emphasis to gender differences in clothing quality assessment. This is in line with the conclusions of quality research conducted long ago, such as Olson & Jacoby’s (1972), which findings are specific to the type of product and/or consumer investigated. Therefore, generalizations beyond the product or the consumers examined are of dubious validity.

As of early 2023, men and women in Ireland had similar preferences when it came to shopping channels. Around a third of male and female consumers surveyed said they would prefer to shop mostly online for goods and services, given the choice.

Graph and download economic data for Women Employees, Retail Trade (CES4200000010) from Jan 1972 to Sep 2025 about females, establishment survey, retail trade, sales, retail, employment, and USA.

The market for middle-aged and elderly women's clothing is experiencing significant growth, driven by several key factors. The increasing global population of women aged 50 and above, coupled with rising disposable incomes and a greater emphasis on personal well-being in this demographic, are fueling demand. This segment is demonstrating a shift towards more stylish, comfortable, and functional clothing, moving beyond traditional perceptions of "seniors' fashion." Online sales channels are experiencing rapid expansion, offering convenience and wider product choices to this target audience. However, challenges remain, including maintaining consistent brand image and appeal across different age sub-groups within the target market, and adapting designs to accommodate diverse body types and preferences. The preference for natural fabrics, sustainable practices and ethical sourcing is also becoming increasingly important and influencing purchasing decisions. Competition remains high, with a diverse range of both established and emerging brands vying for market share. Geographic variations in purchasing power and cultural preferences also influence market performance, with regions like North America and Europe demonstrating stronger initial market penetration due to higher disposable income and established e-commerce infrastructure. The Asia-Pacific region, especially China and India, shows immense growth potential as increasing affluence and changing lifestyle patterns drive demand. A focus on providing personalized experiences and targeted marketing will be crucial for brands aiming to maximize success in this expanding market. Successful brands within this market segment are leveraging targeted marketing strategies to highlight the comfort, quality, and style of their products. They are also prioritizing ethical and sustainable practices, increasingly important to environmentally and socially conscious consumers. Product innovation, such as adaptive clothing and specialized designs addressing specific needs (e.g., arthritis-friendly closures), represents a significant opportunity for growth. The integration of technology, such as virtual try-on tools and personalized recommendations, is enhancing the online shopping experience. Future growth will depend on brands' ability to effectively utilize data analytics to understand customer preferences and tailor their offerings, while adapting to evolving fashion trends and maintaining sustainable business practices. A key challenge lies in addressing the diverse needs and preferences across different age subgroups within the middle-aged and elderly women's apparel market, requiring sophisticated segmentation and targeting approaches.

Female consumer spending was expected to reach approximately ** trillion U.S. dollars worldwide in 2018, an increase from around ** trillion U.S. dollars in 2013. This large increase of over *** trillion U.S. dollars is no surprise when you consider the fast development of the world’s population.

What is consumer spending?

Consumer spending is what individuals, or households, spend to satisfy their everyday needs. This can include services such as healthcare and banking, as well as durable and non-durable consumer goods. Durable goods are more hardy goods which do not need to be purchased so often, such as kitchen appliances or furniture. Non-durable goods have a shorter lifespan and need to be purchased more frequently, such as food, apparel and toiletries. Consumer spending is a key driving force of economies worldwide.

Grocery spending

Due to our need to eat and stay hydrated, grocery shopping makes up a large segment of consumer spending. In the United States alone, consumer spending in supermarkets and grocery stores is forecast to reach around **** billion U.S. dollars by 2020. There is also a very large market for eating out at restaurants in the United States, as the country has the highest share of consumer restaurant spending worldwide.

Graph and download economic data for Sectoral Output for Retail Trade: Women's Clothing Stores (NAICS 448120) in the United States (IPUHN448120T300000000) from 1987 to 2021 about apparel, females, NAICS, retail trade, production, sales, retail, and USA.

Graph and download economic data for Employment for Retail Trade: Women's Clothing Stores (NAICS 448120) in the United States (IPUHN448120W201000000) from 1988 to 2021 about apparel, females, NAICS, retail trade, sales, retail, employment, and USA.

Statistics illustrates consumption, production, prices, and trade of Women's or Girls' Clothing (Not Knitted or Crocheted) in Eastern Europe from 2007 to 2024.

About this dataset

Context

The dataset tabulates the population of Commerce by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Commerce across both sexes and to determine which sex constitutes the majority.

Key observations

There is a majority of female population, with 53.66% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Commerce is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Commerce total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Commerce Population by Race & Ethnicity. You can refer the same here

Statistics illustrates consumption, production, prices, and trade of Women's or Girls' Clothing (Not Knitted or Crocheted) in Mali from 2007 to 2024.

Graph and download economic data for Hours Worked for Retail Trade: Women's Clothing Stores (NAICS 448120) in the United States (IPUHN448120L010000000) from 1987 to 2021 about apparel, females, NAICS, hours, retail trade, sales, retail, and USA.

Graph and download economic data for Labor Compensation for Retail Trade: Women's Clothing Stores (NAICS 448120) in the United States (IPUHN448120U110000000) from 1987 to 2021 about apparel, compensation, females, NAICS, retail trade, labor, sales, retail, and USA.

In a 2023 survey, it was found that both men and women frequently encounter products through social media during their shopping journey. More than ** percent of women and over **** of men reported discovering products through social media. Notably, women exhibit a higher tendency to discover new products via social media in comparison to other channels, and they also engage more frequently in product research on these platforms.

About this dataset

Context

The dataset tabulates the population of Commerce by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Commerce. The dataset can be utilized to understand the population distribution of Commerce by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Commerce. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Commerce.

Key observations

Largest age group (population): Male # 0-4 years (133) | Female # 30-34 years (94). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Commerce population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Commerce is shown in the following column.
• Population (Female): The female population in the Commerce is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Commerce for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Commerce Population by Gender. You can refer the same here

Graph and download economic data for Unit Labor Costs for Retail Trade: Women's Clothing Stores (NAICS 44812) in the United States (IPUHN44812U101000000) from 1988 to 2021 about unit labor cost, apparel, females, NAICS, retail trade, sales, retail, and USA.