From 2023 to 2024 the share of returned clothing items purchased online slightly increased by *** percentage points. By 2027, the online return rate of clothing orders is expected to reach *** percent.

An online store offers many advantages over a physical store. Online stores allow people to shop anywhere, any time. Customers can read reviews about the product before making a purchase decision. And there are typically more payment options available. Yet, despite all these advantages, online stores see a higher return rate than physical stores. According […]

The return order volume for purchases made online was at **** percent in 2022 in India. This was a decrease as compared to the previous year when the return volume stood at over ** percent. Moreover, the majority of the returns belonged to the fashion segment under apparel and footwear.

Spain was the country with the highest return rate of online retail purchases in 2023 according to aggregate data of the Mastercard Economic Institute. In 2023, Spaniards returned a quarter of e-commerce retail purchases, while Germans returned over 20 percent, more than doubling their return rate from 2019.

When asked about "Most returned online purchases by category", most U.S. respondents pick "Clothing" as an answer. 25 percent did so in our online survey in 2025. Looking to gain valuable insights about customers of online shops across the globe? Check out our reports about consumers of online shops worldwide. These reports offer the readers a comprehensive overview of customers of eCommerce brands: who they are; what they like; what they think; and how to reach them.

Note:- Only publicly available data can be worked upon

In today's ever-evolving Ecommerce landscape, success hinges on the ability to harness the power of data. APISCRAPY is your strategic ally, dedicated to providing a comprehensive solution for extracting critical Ecommerce data, including Ecommerce market data, Ecommerce product data, and Ecommerce datasets. With the Ecommerce arena being more competitive than ever, having a data-driven approach is no longer a luxury but a necessity.

APISCRAPY's forte lies in its ability to unearth valuable Ecommerce market data. We recognize that understanding the market dynamics, trends, and fluctuations is essential for making informed decisions.

APISCRAPY's AI-driven ecommerce data scraping service presents several advantages for individuals and businesses seeking comprehensive insights into the ecommerce market. Here are key benefits associated with their advanced data extraction technology:

1. Ecommerce Product Data: APISCRAPY's AI-driven approach ensures the extraction of detailed Ecommerce Product Data, including product specifications, images, and pricing information. This comprehensive data is valuable for market analysis and strategic decision-making.

2. Data Customization: APISCRAPY enables users to customize the data extraction process, ensuring that the extracted ecommerce data aligns precisely with their informational needs. This customization option adds versatility to the service.

3. Efficient Data Extraction: APISCRAPY's technology streamlines the data extraction process, saving users time and effort. The efficiency of the extraction workflow ensures that users can obtain relevant ecommerce data swiftly and consistently.

4. Realtime Insights: Businesses can gain real-time insights into the dynamic Ecommerce Market by accessing rapidly extracted data. This real-time information is crucial for staying ahead of market trends and making timely adjustments to business strategies.

5. Scalability: The technology behind APISCRAPY allows scalable extraction of ecommerce data from various sources, accommodating evolving data needs and handling increased volumes effortlessly.

Beyond the broader market, a deeper dive into specific products can provide invaluable insights. APISCRAPY excels in collecting Ecommerce product data, enabling businesses to analyze product performance, pricing strategies, and customer reviews.

To navigate the complexities of the Ecommerce world, you need access to robust datasets. APISCRAPY's commitment to providing comprehensive Ecommerce datasets ensures businesses have the raw materials required for effective decision-making.

Our primary focus is on Amazon data, offering businesses a wealth of information to optimize their Amazon presence. By doing so, we empower our clients to refine their strategies, enhance their products, and make data-backed decisions.

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In 2021, European online shoppers aged 18 to 24 returned the highest proportion of items purchased on the web. With an online return rate of over 20 percent, young adults located in Switzerland were the most prolific returners out of the six countries analyzed.

Graph and download economic data for E-Commerce Retail Sales as a Percent of Total Sales (ECOMPCTSA) from Q4 1999 to Q1 2025 about e-commerce, retail trade, percent, sales, retail, and USA.

In 2024, returns on online purchases in the United States amounted to nearly *** billion U.S. dollars. That is a significant increase compared to the previous year when the cost of e-commerce returns was approximately *** billion U.S. dollars. The impact of free returns Numerous factors contribute to a shopper's decision to return items bought online, with varying preferences guiding their return process. Nonetheless, certain consumer preferences hold greater significance than others. In 2022, nearly ** percent of United States consumers who returned an online order listed free returns as a one of their main e-commerce returns preference. The impact of free returns on consumer shopping behavior in the U.S. is considerable, with roughly **** out of ten consumers indicating a strong likelihood of discontinuing purchases from a brand if it were to remove the option of free returns. Paying for returns: U.S. vs. EU The willingness of consumers to pay for e-commerce returns varies across countries. Despite resistance from many U.S. online shoppers, the North American country still boasts one of the largest shares of consumers willing to invest in online returns. Moreover, a 2022 survey conducted among consumers in the U.S. and selected European countries revealed that the percentage of shoppers anticipating free online returns was higher in Italy, Belgium, France, and Spain compared to the United States.

Returns processing, or reverse logistics, has become vital to the sale of physical products, driving the growth of the Product Returns Management Services industry. The surge in e-commerce has led to higher return rates, necessitating more robust and efficient return processes. A seamless returns process is crucial for businesses to maintain customer loyalty. Rising disposable income has further bolstered consumer spending at brick-and-mortar and online outlets, enhancing the need for effective returns management. Despite the pandemic-induced volatility in consumer spending habits, returns processors' revenue is forecast to expand at a CAGR of 4.5% over the past five years to cover the influx of returns, reaching $12.7 billion in 2024, including growth of 4.2% in 2024 alone. The resale market, driven by a recent rise in sustainable shopping, offers businesses opportunities to directly recoup losses from returned items. Returns processors have taken advantage of a thriving consumer electronics industry, assisting electronics manufacturers in the salvage and resale of returned parts to liquidators and other secondary markets. Amazon's Warehouse re-commerce efforts have led to the resale of returns, displaying returned items beside new models, assigning a consistent quality grade and offering the same high-speed shipping. These efforts contribute to steady profit across the industry. Returns processors will continue to follow many of the trends experienced by retailers in the coming years. Omnichannel returns, where customers can buy online and return in-store or vice versa, require businesses to integrate their return processes across different sales channels. Omnichannel operations add complexity to inventory management and logistics but can reduce shipping expenses dramatically by aggregating returned items. Simultaneously, an increasing need for sophisticated return fraud prevention strategies has become critical. The rise in online shopping has made fraud, such as wardrobing or counterfeit returns, more prevalent. Businesses will invest in software fraud detection tools, package scanners and other techniques to combat these practices while ensuring a smooth returns experience for legitimate customers. Returns processors' revenue is forecast to rise at a CAGR of 3.5% to $15.1 billion in 2029.

Dataset Description

The E-commerce Order Dataset provides comprehensive information related to orders, items within orders, customers, payments, and products for an e-commerce platform. This dataset is structured with multiple tables, each containing specific information about various aspects of the e-commerce operations.

Dataset Features

Orders Table:

• order_id: Unique identifier for an order, acting as the primary key.
• customer_id: Unique identifier for a customer. This table may not be unique at this level.
• order_status: Indicates the status of an order (e.g., delivered, cancelled, processing, etc.).
• order_purchase_timestamp: Timestamp when the order was made by the customer.
• order_approved_at: Timestamp when the order was approved from the seller's side.
• order_delivered_timestamp: Timestamp when the order was delivered at the customer's location.
• order_estimated_delivery_date: Estimated date of delivery shared with the customer while placing the order.

Order Items Table

• order_id: Unique identifier for an order.
• order_item_id: Item number in each order, acting as part of the primary key along with the order_id.
• product_id: Unique identifier for a product.
• seller_id: Unique identifier for the seller.
• price: Selling price of the product.
• shipping_charges: Charges associated with the shipping of the product.

Customers Table

• customer_id: Unique identifier for a customer, acting as the primary key.
• customer_zip_code_prefix: Customer's Zip code.
• customer_city: Customer's city.
• customer_state: Customer's state.

Payments Table

• order_id: Unique identifier for an order.
• payment_sequential: Provides information about the sequence of payments for the given order.
• payment_type: Type of payment (e.g., credit_card, debit_card, etc.).
• payment_installments: Payment installment number in case of credit cards.
• payment_value: Transaction value.

Products Table

• product_id: Unique identifier for each product, acting as the primary key.
• product_category_name: Name of the category the product belongs to.
• product_weight_g: Product weight in grams.
• product_length_cm: Product length in centimeters.
• product_height_cm: Product height in centimeters.
• product_width_cm: Product width in centimeters.

Cross Border B2C E-Commerce Market Outlook

The global Cross Border B2C E-Commerce market size is projected to grow from $900 billion in 2023 to $2.3 trillion by 2032, reflecting a Compound Annual Growth Rate (CAGR) of 11%. This growth is driven by the expanding internet penetration, increasing consumer preference for online shopping, and advancements in payment and logistics infrastructure.

The primary growth factor for this market is the proliferation of internet and smartphone usage, which has revolutionized the way consumers shop. With increasing internet penetration and the widespread availability of affordable smartphones, more people are accessing online platforms to purchase goods and services from international markets. Additionally, improvements in digital payment methods, such as the use of digital wallets and secure online payment gateways, have made cross-border transactions more seamless and secure, further boosting consumer confidence in international e-commerce.

Another significant growth factor is the rise of social media and digital marketing, which has enabled businesses to reach a global audience more effectively. Social media platforms like Instagram, Facebook, and TikTok have become powerful marketing tools that allow brands to target specific demographics and regions with tailored advertising. This has not only increased brand awareness but has also facilitated direct engagement with consumers, leading to higher conversion rates and increased sales in the cross-border B2C e-commerce market.

Additionally, the advancements in logistics and supply chain management have played a crucial role in the growth of this market. Innovations such as real-time tracking, faster shipping options, and efficient return policies have enhanced the overall shopping experience for consumers. Companies are investing heavily in logistics infrastructure to ensure timely and cost-effective delivery of products across borders, thereby improving customer satisfaction and driving repeat purchases.

From a regional perspective, Asia Pacific is expected to dominate the cross-border B2C e-commerce market during the forecast period. The region's large population, growing middle class, and increasing disposable income levels are key factors contributing to this growth. Countries like China, India, and Japan are witnessing significant e-commerce growth due to favorable government policies, improved internet connectivity, and a burgeoning tech-savvy population. North America and Europe are also substantial markets, driven by advanced digital infrastructure and high consumer spending power.

Product Category Analysis

The apparel and accessories segment holds a significant share in the cross-border B2C e-commerce market. The increasing demand for international fashion brands and the availability of a wide range of products online have contributed to the growth of this segment. Consumers are attracted to the unique styles, higher quality, and exclusive collections offered by international brands. Moreover, the presence of large online fashion retailers and marketplaces, such as ASOS and Zalando, has made it easier for consumers to purchase apparel and accessories from different countries. Additionally, the convenience of comparing prices and reading reviews online has further fueled the growth of this segment.

Consumer electronics is another major segment in the cross-border B2C e-commerce market. The demand for the latest gadgets and electronic devices has driven consumers to shop from international online stores where these products are often available at competitive prices. The segment has benefited from the continuous innovation in electronics, with consumers eager to purchase the newest smartphones, laptops, and smart home devices. The availability of detailed product descriptions, customer reviews, and warranty options online has also enhanced consumer confidence in purchasing electronics from international platforms.

The personal care and beauty segment is experiencing rapid growth due to the rising popularity of international beauty brands and skincare products. Consumers are increasingly seeking high-quality and innovative beauty products that may not be available in their local markets. The influence of beauty bloggers and social media influencers has also played a significant role in promoting international beauty brands. Additionally, the convenience of online tutorials and reviews has made it easier for consumers to choose the right products, encouraging them to shop from international e-commerce platforms.

Food and beverage is another growing segment in the cross-border B2C e-commerce market. The demand for specialty

Consumer Electronics E-commerce Market Outlook

According to our latest research, the global Consumer Electronics E-commerce market size reached USD 641.2 billion in 2024, driven by the rapid adoption of digital channels and rising internet penetration worldwide. The market is expected to expand at a robust CAGR of 13.1% from 2025 to 2033, reaching an estimated USD 1,751.8 billion by 2033. This remarkable growth is primarily attributed to evolving consumer purchasing patterns, the proliferation of smartphones, and the increasing convenience offered by online retail platforms.

One of the most significant growth factors propelling the Consumer Electronics E-commerce market is the widespread adoption of smartphones and high-speed internet connectivity. As more consumers gain access to affordable mobile devices and broadband services, there is a notable shift in shopping behavior from traditional brick-and-mortar stores to online platforms. The availability of a vast array of electronic products, combined with the convenience of home delivery and easy returns, has made e-commerce the preferred channel for purchasing consumer electronics. Additionally, the rise of digital payment solutions and the integration of advanced technologies such as artificial intelligence and augmented reality for product visualization are enhancing the overall online shopping experience, further fueling market growth.

Another critical driver of market expansion is the growing influence of e-commerce giants and specialized consumer electronics retailers. Companies like Amazon, Alibaba, Flipkart, and Best Buy have revolutionized the way electronic products are marketed and sold, leveraging data analytics and personalized marketing to target specific consumer segments. These platforms offer competitive pricing, exclusive deals, and a wide selection of products, attracting price-sensitive and tech-savvy consumers alike. Furthermore, the increasing frequency of online sales events such as Black Friday, Cyber Monday, and regional shopping festivals has significantly contributed to the surge in online sales volumes, encouraging both established brands and emerging players to invest heavily in their e-commerce capabilities.

The ongoing digital transformation across industries has also played a pivotal role in shaping the Consumer Electronics E-commerce market. Businesses are increasingly adopting e-commerce solutions to streamline their operations, expand their customer base, and enhance supply chain efficiency. This trend is particularly evident in the commercial segment, where organizations are procuring bulk electronics such as laptops, tablets, and audio devices for remote work and collaboration. The integration of omnichannel strategies, which combine online and offline touchpoints, is further blurring the lines between physical and digital retail, enabling retailers to offer a seamless and personalized shopping journey. As a result, the market is witnessing robust growth across both individual and commercial end-user segments.

Regionally, Asia Pacific continues to dominate the Consumer Electronics E-commerce market, accounting for the largest share in 2024. This dominance is underpinned by the region’s massive population, rapid urbanization, and the burgeoning middle class with rising disposable incomes. Countries such as China, India, and Southeast Asian nations are leading the charge, driven by aggressive investments in digital infrastructure and favorable government policies promoting e-commerce. North America and Europe also represent significant markets, characterized by high internet penetration rates and a mature e-commerce ecosystem. Meanwhile, Latin America and the Middle East & Africa are emerging as high-growth regions, supported by increasing digital literacy and expanding mobile internet coverage.

Product Type Analysis

The Consumer Electronics E-commerce market is highly segmented by product type, encompassing smartphones, laptops & tablets, audio devices, wearables, cameras, televisions

Analysis of ‘E-commerce Dataset ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/mervemenekse/ecommerce-dataset on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Introduction

Analyzing the purchases of our customers for 1 year. How are their customer's online buying habits?

Columns name and meanings:

Order_Date: The date the product was ordered.

Aging: The time from the day the product is ordered to the day it is delivered.

Customer_id: Unique id created for each customer.

Gender: Gender of customer.

Device_Type: The device the customer uses to actualize the transaction (Web/Mobile).

Customer_Login_Type: The type the customer logged in. Such as Member, Guest etc.

Product_Category: Product category

Product: Product

Sales: Total sales amount

Quantity: Unit amount of product

Discount: Percent discount rate

Profit: Profit

Shipping_cost: Shipping cost

Order_Priority: Order priority. Such as critical, high etc.

Payment_method: Payment method

Here is the some question that you can start with;

-What devices do my customers use to reach me? -Who is the customer base? -What product categories am I selling? -Which product categories do I sell to whom? (Gender Distribution by Category or Product?) -Which login type do my customers prefer when shopping? -How does the date and time affect my sales? (Total sales by month, the days of week or time arrival) -From which product do I earn the most profit per unit? -How is my delivery speed and order priority?(Delivery Time distribution of order priority by months)

--- Original source retains full ownership of the source dataset ---

In 2024, next to an add-to-cart rate of 9.3%, a cart abandonment rate of 72.8%, and a conversion rate of 2.5%, the eCommerce Benchmark KPIs in Japan also consist of an AOV of US$116.7, a discount rate of 10.3%, and a return rate of 7.4%.

A comprehensive dataset providing key insights into the eCommerce industry, including global retail online sales projections, number of eCommerce stores, digital buyer statistics, revenue growth in the United States, sector-wise revenue details with a focus on consumer electronics, average conversion rates, and mobile commerce sales forecasts.

OpenWeb Ninja's Product Data API provides Product Data, Product Reviews Data, Product Offers, sourced in real-time from Google Shopping - the largest product listings aggregate on the web, listing products from all publicly available e-commerce sites (Amazon, eBay, Walmart + many others).

The API covers more than 35 billion Product Data Listings, including Product Reviews and Product Offers across the web. The API provides over 40 product data points including prices, rating and reviews insights, product details and specs, typical price ranges, and more.

OpenWeb Ninja's Product Data common use cases: - Price Optimization & Price Comparison - Market Research & Competitive Analysis - Product Research & Trend Analysis - Customer Reviews Analysis

OpenWeb Ninja's Product Data Stats & Capabilities: - 35B+ Product Listings - 40+ data points per job listing - Global aggregate - Search by keyword or GTIN/EAN

3D Ecommerce Market Outlook

The global 3D ecommerce market size was valued at approximately USD 3.5 billion in 2023 and is projected to reach around USD 12.7 billion by 2032, growing at a Compound Annual Growth Rate (CAGR) of 15.3% from 2024 to 2032. The primary growth factor driving this market is the increasing consumer preference for immersive and interactive online shopping experiences, propelled by advancements in 3D imaging and augmented reality technologies.

One of the primary growth factors for the 3D ecommerce market is the rapid technological advancements in 3D modeling and augmented reality (AR). These technologies enable online shoppers to visualize products in a highly realistic manner, thereby enhancing the overall shopping experience. This capability not only helps in reducing product returns but also increases consumer confidence in making purchases, which in turn drives the market. Moreover, the continuous development in AR and virtual reality (VR) technologies is making it easier and more cost-effective for businesses to implement 3D ecommerce solutions, thereby fuelling market growth.

Another significant growth factor is the increasing adoption of e-commerce platforms across various sectors such as retail, automotive, and real estate. The retail sector, in particular, has been quick to adopt 3D ecommerce solutions to offer customers virtual try-ons and product visualizations. This has led to increased sales and customer satisfaction. Similarly, the real estate sector is increasingly using 3D virtual tours to showcase properties, thereby saving time and resources for both buyers and sellers. The automotive industry is also leveraging 3D technology to provide virtual showrooms and configurators, making the car-buying process more interactive and personalized.

The growing internet penetration and smartphone usage are also playing a crucial role in driving the 3D ecommerce market. As more consumers gain access to high-speed internet and advanced mobile devices, the demand for interactive and immersive online shopping experiences is rising. This trend is particularly noticeable among the younger generation, who are more inclined towards using technology in their daily lives. Additionally, the COVID-19 pandemic has accelerated the shift towards online shopping, further boosting the market for 3D ecommerce solutions.

The 3D Virtual Fitting Service is revolutionizing the way consumers shop for apparel online. This innovative service allows customers to try on clothes virtually, using their own body measurements to see how different styles and sizes will look on them. By providing a more personalized and accurate shopping experience, 3D Virtual Fitting Service helps reduce the uncertainty associated with online clothing purchases. This not only enhances customer satisfaction but also significantly reduces return rates, as customers are more likely to receive items that fit well. Retailers are increasingly adopting this technology to offer a more engaging and interactive shopping experience, which is crucial in today's competitive ecommerce landscape. The integration of 3D Virtual Fitting Service with existing ecommerce platforms is expected to drive further growth in the 3D ecommerce market, as it aligns with the growing consumer demand for convenience and personalization.

From a regional perspective, North America and Europe are currently leading the 3D ecommerce market due to the high adoption rate of advanced technologies and strong presence of key market players in these regions. However, Asia Pacific is expected to witness the highest growth rate during the forecast period. This growth can be attributed to the increasing internet penetration, growing middle-class population, and rising disposable incomes in countries like China and India. Latin America and the Middle East & Africa are also showing promising growth potential, driven by the expanding e-commerce sector and increasing investments in digital infrastructure.

Component Analysis

The 3D ecommerce market is segmented by components into software, hardware, and services. The software segment is currently the largest and is expected to continue its dominance over the forecast period. This segment includes various tools and platforms that enable the creation, management, and deployment of 3D content for ecommerce applications.

The global e-commerce returns management software market is experiencing robust growth, driven by the escalating volume of online returns and the increasing need for efficient and cost-effective return processes. The market size in 2025 is estimated at $2.5 billion, exhibiting a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This significant expansion is fueled by several key factors. Firstly, the rising adoption of e-commerce across diverse demographics necessitates sophisticated returns management solutions to mitigate losses and enhance customer satisfaction. Secondly, the increasing complexity of supply chains and the geographical dispersion of both customers and fulfillment centers necessitate automated, streamlined return processes. Furthermore, the growing demand for omnichannel returns experiences, where customers can return items through multiple channels (e.g., online, in-store), is boosting the adoption of advanced returns management software. Finally, the integration of artificial intelligence (AI) and machine learning (ML) into these systems is improving efficiency, accuracy, and predictive capabilities, further fueling market growth. The market segmentation reveals strong growth in cloud-based solutions due to their scalability, cost-effectiveness, and accessibility. The B2C segment dominates, reflecting the sheer volume of consumer returns. However, the B2B segment is also showing promising growth, particularly amongst larger businesses seeking enhanced supply chain visibility and control over returns. While the market faces challenges such as integration complexities and the initial investment costs associated with software implementation, the long-term benefits in terms of cost savings, improved customer loyalty, and enhanced operational efficiency are driving widespread adoption. The competitive landscape is characterized by a mix of established players and emerging startups, offering a diverse range of solutions tailored to specific business needs and industry verticals. The continued expansion of e-commerce, coupled with technological advancements, ensures a positive outlook for the returns management software market in the coming years.

Overview:

This dataset contains 1000 rows of synthetic online retail sales data, mimicking transactions from an e-commerce platform. It includes information about customer demographics, product details, purchase history, and (optional) reviews. This dataset is suitable for a variety of data analysis, data visualization and machine learning tasks, including but not limited to: customer segmentation, product recommendation, sales forecasting, market basket analysis, and exploring general e-commerce trends. The data was generated using the Python Faker library, ensuring realistic values and distributions, while maintaining no privacy concerns as it contains no real customer information.

Data Source:

This dataset is entirely synthetic. It was generated using the Python Faker library and does not represent any real individuals or transactions.

Data Content:

Potential Use Cases (Inspiration):

Customer Segmentation: Group customers based on demographics, purchasing behavior, and preferences.

Product Recommendation: Build a recommendation system to suggest products to customers based on their past purchases and browsing history.

Sales Forecasting: Predict future sales based on historical trends.

Market Basket Analysis: Identify products that are frequently purchased together.

Price Optimization: Analyze the relationship between price and demand.

Geographic Analysis: Explore sales patterns across different cities.

Time Series Analysis: Investigate sales trends over time.

Educational Purposes: Great for practicing data cleaning, EDA, feature engineering, and modeling.