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TwitterApache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
The dataset released is anonymized and not representative of the production characteristics.
The Multilingual Shopping Session Dataset is a collection of anonymized customer sessions containing products from six different locales: English, German, Japanese, French, Italian, and Spanish. It consists of two main components: user sessions and product attributes. User sessions are a list of products that a user has engaged with in chronological order, while product attributes include various details like product title, price in local currency, brand, colour, and description.
The dataset has been divided into three splits: train, phase-1 test, and phase-2 test. For Task 1 and Task 2, the proportions for each language are roughly 10:1:1. For Task 3, the number of samples in the phase-1 test and phase-2 test is fixed at 10,000. All three tasks share the same train set, while their test sets have been constructed according to their specific objectives. Task 1 uses English, German, and Japanese data, while Task 2 uses French, Italian, and Spanish data. Participants in Task 2 are encouraged to use transfer learning to improve their system's performance on the test set. For Task 3, the test set includes products that do not appear in the training set, and participants are asked to generate the title of the next product based on the user session.
Table 1 summarizes the dataset statistics, including the number of sessions, interactions, products, and average session length. The dataset will be made publicly available as part of the KDD Cup competition. Each product will be identified by a unique Amazon Standard Identification Number (ASIN), making extracting more information from the web easy. Participants are free to use external sources of information to train their systems, such as public datasets and pre-trained language models, but must declare them when describing their systems beyond the provided dataset.
| Language (Locale) | # Sessions | # Products (ASINs) |
|---|---|---|
| German (DE) | 1111416 | 513811 |
| Japanese (JP) | 979119 | 389888 |
| English (UK) | 1182181 | 494409 |
| Spanish (ES) | 89047 | 41341 |
| French (FR) | 117561 | 43033 |
| Italian (IT) | 126925 | 48788 |
Table 1: Dataset statistics
In addition, we list the column names and their meanings for product attribute data: - locale: the locale code of the product (e.g., DE) - id: a unique for the product. Also known as Amazon Standard Item Number (ASIN) (e.g., B07WSY3MG8) - title: title of the item (e.g., âJapanese Aesthetic Sakura Flowers Vaporwave Soft Grunge Gift T-Shirtâ) - price: price of the item in local currency (e.g., 24.99) - brand: item brand name (e.g., âJapanese Aesthetic Flowers & Vaporwave Clothingâ) - color: color of the item (e.g., âBlackâ) - size: size of the item (e.g., âxxlâ) - model: model of the item (e.g., âiphone 13â) - material: material of the item (e.g., âcottonâ) - author: author of the item (e.g., âJ. K. Rowlingâ) - desc: description about a itemâs key features and benefits called out via bullet points (e.g., âSolid colors: 100% Cotton; Heather Grey: 90% Cotton, 10% Polyester; All Other Heathers âŚâ)
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Print On Demand Market Size 2025-2029
The print on demand market size is forecast to increase by USD 25.36 billion, at a CAGR of 25.6% between 2024 and 2029.
The market is experiencing significant growth, driven by the increasing popularity of customized merchandise as a branding tool. Businesses are leveraging print on demand services to create unique, personalized products, particularly in the apparel sector, where custom T-shirts are leading the charge. This trend is further fueled by the seamless integration of print on demand services with e-commerce platforms, enabling businesses to reach a wider customer base and streamline their operations. However, the market is not without challenges. The dynamic pricing of raw materials poses a significant obstacle for businesses, as fluctuations in the cost of essential inputs can significantly impact profitability.
Moreover, ensuring consistent quality across various orders and maintaining a steady supply chain are ongoing challenges that require careful attention and strategic planning. To capitalize on the opportunities presented by this market and navigate these challenges effectively, companies must stay agile, invest in advanced technology, and build strong relationships with their suppliers.
What will be the Size of the Print On Demand 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.
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The market continues to evolve, driven by shifting consumer preferences and advancements in technology. This dynamic industry caters to various sectors, including home decor, personalized products, and custom apparel. The ongoing unfolding of market activities is characterized by continuous improvements in printing quality and customer service. Production costs and lead times are subject to change as new technologies emerge, such as digital and sublimation printing. Customer lifetime value and environmental impact are increasingly important considerations for businesses in this market. Ethical sourcing and sustainable practices are gaining traction, as are marketing and advertising strategies that leverage email marketing and social media.
Heat transfer printing and phone case production remain popular applications, with a focus on color accuracy and customer satisfaction. On-demand printing enables businesses to offer a wide range of products, from canvas prints to white-label items, without holding inventory. E-commerce integration and order management systems streamline operations, while graphic design services and product photography help businesses create compelling offerings. Fulfillment services and inventory management systems ensure timely delivery, enhancing customer experience. Pricing strategies continue to evolve, with businesses leveraging pay-per-click (PPC) advertising and returns and exchanges policies to optimize revenue. Print resolution and file formats are crucial factors in maintaining high-quality output, while color profiles and shipping and logistics are essential components of a successful business model.
The print-on-demand landscape is constantly evolving, with new trends and applications emerging as consumer demands and technological advancements shape the industry.
How is this Print On Demand Industry segmented?
The print on demand 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.PlatformSoftwareServiceProductApparelHome decorDrinkwareOthersChannelD2CMarketplaceGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKMiddle East and AfricaEgyptKSAOmanUAEAPACChinaIndiaJapanSouth AmericaArgentinaBrazilRest of World (ROW)
By Platform Insights
The software segment is estimated to witness significant growth during the forecast period.
Print on demand software, including platforms like Printful, Spocket, and Gooten, offers businesses access to essential printing tools via a cloud network or on-premises setup. The globalization trend and expanding reach of IT, BFSI, and retail sectors necessitate a centralized system for managing print operations. The cloud facilitates access to extensive data sets, thereby reducing capital expenditure (CAPEX) for businesses. Print quality and customer service are crucial factors driving the adoption of print on demand solutions. Production costs and lead times are significantly reduced through digital printing technologies, such as sublimation and direct-to-garment printing. Canvas prints, home decor, and personalized products are popular offerings in this market.
E-commerce integration, white-label products, and order management systems enable seamless selling of print products online. Ethical sourcing and environmental impact are growing conc
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Facebook
TwitterApache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
The dataset released is anonymized and not representative of the production characteristics.
The Multilingual Shopping Session Dataset is a collection of anonymized customer sessions containing products from six different locales: English, German, Japanese, French, Italian, and Spanish. It consists of two main components: user sessions and product attributes. User sessions are a list of products that a user has engaged with in chronological order, while product attributes include various details like product title, price in local currency, brand, colour, and description.
The dataset has been divided into three splits: train, phase-1 test, and phase-2 test. For Task 1 and Task 2, the proportions for each language are roughly 10:1:1. For Task 3, the number of samples in the phase-1 test and phase-2 test is fixed at 10,000. All three tasks share the same train set, while their test sets have been constructed according to their specific objectives. Task 1 uses English, German, and Japanese data, while Task 2 uses French, Italian, and Spanish data. Participants in Task 2 are encouraged to use transfer learning to improve their system's performance on the test set. For Task 3, the test set includes products that do not appear in the training set, and participants are asked to generate the title of the next product based on the user session.
Table 1 summarizes the dataset statistics, including the number of sessions, interactions, products, and average session length. The dataset will be made publicly available as part of the KDD Cup competition. Each product will be identified by a unique Amazon Standard Identification Number (ASIN), making extracting more information from the web easy. Participants are free to use external sources of information to train their systems, such as public datasets and pre-trained language models, but must declare them when describing their systems beyond the provided dataset.
| Language (Locale) | # Sessions | # Products (ASINs) |
|---|---|---|
| German (DE) | 1111416 | 513811 |
| Japanese (JP) | 979119 | 389888 |
| English (UK) | 1182181 | 494409 |
| Spanish (ES) | 89047 | 41341 |
| French (FR) | 117561 | 43033 |
| Italian (IT) | 126925 | 48788 |
Table 1: Dataset statistics
In addition, we list the column names and their meanings for product attribute data: - locale: the locale code of the product (e.g., DE) - id: a unique for the product. Also known as Amazon Standard Item Number (ASIN) (e.g., B07WSY3MG8) - title: title of the item (e.g., âJapanese Aesthetic Sakura Flowers Vaporwave Soft Grunge Gift T-Shirtâ) - price: price of the item in local currency (e.g., 24.99) - brand: item brand name (e.g., âJapanese Aesthetic Flowers & Vaporwave Clothingâ) - color: color of the item (e.g., âBlackâ) - size: size of the item (e.g., âxxlâ) - model: model of the item (e.g., âiphone 13â) - material: material of the item (e.g., âcottonâ) - author: author of the item (e.g., âJ. K. Rowlingâ) - desc: description about a itemâs key features and benefits called out via bullet points (e.g., âSolid colors: 100% Cotton; Heather Grey: 90% Cotton, 10% Polyester; All Other Heathers âŚâ)