Amazon Products dataset to explore detailed product listings, pricing, reviews, and sales data. Popular use cases include competitive analysis, market trend forecasting, and e-commerce strategy optimization.

Use our Amazon Products dataset to explore detailed information on products across various categories, including pricing, reviews, ratings, and sales data. This dataset is ideal for e-commerce professionals, market analysts, and product managers looking to analyze market trends, optimize product listings, and refine competitive strategies.

Leverage this dataset to track pricing trends, assess customer feedback, and uncover popular product categories. Whether you're conducting competitive analysis, performing market research, or optimizing product strategies, the Amazon Products dataset provides key insights to stay ahead in the e-commerce landscape.

Dataset Features

• Title: The name or title of the product.
• seller_name: The name of the seller offering the product.
• Brand: The brand associated with the product.
• Description: A detailed description of the product, including key features.
• initial_price: The original price of the product before any discounts.
• final_price: The current price of the product after discounts.
• Currency: The currency in which the product is priced (e.g., GBP, USD).
• Availability: The stock status (e.g., in stock, out of stock).
• reviews_count: The total number of customer reviews.
• Categories: The specific category the product belongs to.
• asin: Amazon Standard Identification Number.
• buybox_seller: The seller currently winning the Amazon Buy Box.
• number_of_sellers: The number of sellers offering this product.
• root_bs_rank: The overall ranking of the product in the Amazon best-sellers list.
• answered_questions: The number of questions answered in the product Q&A section.
• domain: The website domain where the product is being sold.
• images_count: The number of images available for the product.
• URL: The link to the product page on Amazon.
• video_count: The number of videos available for the product.
• image_url: The URL of the primary image associated with the product.
• item_weight: The weight of the product.
• Rating: The average rating of the product based on customer reviews.
• product_dimensions: The dimensions of the product (e.g., length, width, height) and weight.
• seller_id: The unique identifier for the seller.
• date_first_available: The date when the product was first made available on Amazon.
• discount: Any discount applied to the product.
• model_number: The model number of the product.
• manufacturer: The company that manufactures the product.
• department: The department under which the product is categorized (e.g., Health & Household).
• plus_content: A flag indicating if the product has Amazon’s “Plus Content” (additional marketing content).
• upc: The Universal Product Code (UPC) associated with the product.
• video: URL(s) of any video content associated with the product.
• top_review: A summary or excerpt from the top customer review.
• variations: Different product variations (e.g., different sizes or flavors).
• delivery: Information on the delivery options (e.g., free delivery or Prime delivery).
• features: Key features or highlights of the product.
• format: The format of the product (e.g., powder, liquid).
• buybox_prices: Pricing details for the product, including the base and tiered prices.
• parent_asin: The ASIN of the parent product (if the product is part of a larger group of similar products).
• input_asin: The ASIN of the product as input for Amazon searches.
• ingredients: List of ingredients in the product (if applicable).
• origin_url: The source URL for product-related information or ingredients.
• bought_past_month: A flag indicating if the product was bought in the past month.
• is_available: Availability status of the product (True/False).
• root_bs_category: The broad product category (e.g., Health & Household).
• bs_category: The specific subcategory the product belongs to.
• bs_rank: The rank of the product in its specific subcategory.
• badge: Any badge or label the product has earned (e.g., Amazon's Choice).
• subcategory_rank: The rank of the product within its subcategory.
• amazon_choice: A flag indicating if the product has been selected as Amazon’s Choice.
• images: A list of URLs for additional product images.
• product_details: Detailed product specifications and features.
• prices_breakdown: A breakdown of the price, including any discounts or promotions.
• country_of_origin: The country where the product is made.
• from_the_brand: Information from the brand or manufact

Unlock the full potential of your data-driven projects with our comprehensive Grainger products dataset. This meticulously curated dataset includes detailed information on a wide range of products available on Grainger, one of the leading industrial supply companies.

This dataset is perfect for eCommerce platforms, market analysis, competitive analysis, product comparison, and more. Leverage the power of high-quality, structured data to enhance your business strategies and decision-making processes.

Versions:

Available latest version of the Grainger dataset with 1.2 Million records and last extracted on Jan 2025.

Reach out to contact@crawlfeeds.com

Use Cases:

• eCommerce Platforms: Integrate detailed product information to enhance your product listings.
• Market Analysis: Analyze product trends, pricing, and competition in the industrial supply market.
• Inventory Management: Utilize SKUs and unique identifiers for efficient inventory tracking.
• Data-Driven Projects: Incorporate rich product data into your data science and machine learning models.

Explore the vast collection of Grainger products and elevate your business insights with this high-quality dataset.

Check out Market Research Intellect's Data Diode Cybersecurity Products Market Report, valued at USD 1.5 billion in 2024, with a projected growth to USD 3.2 billion by 2033 at a CAGR of 9.5% (2026-2033).

Envestnet®| Yodlee®'s Retail Transaction Data (Aggregate/Row) Panels consist of de-identified, near-real time (T+1) USA credit/debit/ACH transaction level data – offering a wide view of the consumer activity ecosystem. The underlying data is sourced from end users leveraging the aggregation portion of the Envestnet®| Yodlee®'s financial technology platform.

Envestnet | Yodlee Consumer Panels (Aggregate/Row) include data relating to millions of transactions, including ticket size and merchant location. The dataset includes de-identified credit/debit card and bank transactions (such as a payroll deposit, account transfer, or mortgage payment). Our coverage offers insights into areas such as consumer, TMT, energy, REITs, internet, utilities, ecommerce, MBS, CMBS, equities, credit, commodities, FX, and corporate activity. We apply rigorous data science practices to deliver key KPIs daily that are focused, relevant, and ready to put into production.

We offer free trials. Our team is available to provide support for loading, validation, sample scripts, or other services you may need to generate insights from our data.

Investors, corporate researchers, and corporates can use our data to answer some key business questions such as: - How much are consumers spending with specific merchants/brands and how is that changing over time? - Is the share of consumer spend at a specific merchant increasing or decreasing? - How are consumers reacting to new products or services launched by merchants? - For loyal customers, how is the share of spend changing over time? - What is the company’s market share in a region for similar customers? - Is the company’s loyal user base increasing or decreasing? - Is the lifetime customer value increasing or decreasing?

Additional Use Cases: - Use spending data to analyze sales/revenue broadly (sector-wide) or granular (company-specific). Historically, our tracked consumer spend has correlated above 85% with company-reported data from thousands of firms. Users can sort and filter by many metrics and KPIs, such as sales and transaction growth rates and online or offline transactions, as well as view customer behavior within a geographic market at a state or city level. - Reveal cohort consumer behavior to decipher long-term behavioral consumer spending shifts. Measure market share, wallet share, loyalty, consumer lifetime value, retention, demographics, and more.) - Study the effects of inflation rates via such metrics as increased total spend, ticket size, and number of transactions. - Seek out alpha-generating signals or manage your business strategically with essential, aggregated transaction and spending data analytics.

Use Cases Categories (Our data provides an innumerable amount of use cases, and we look forward to working with new ones): 1. Market Research: Company Analysis, Company Valuation, Competitive Intelligence, Competitor Analysis, Competitor Analytics, Competitor Insights, Customer Data Enrichment, Customer Data Insights, Customer Data Intelligence, Demand Forecasting, Ecommerce Intelligence, Employee Pay Strategy, Employment Analytics, Job Income Analysis, Job Market Pricing, Marketing, Marketing Data Enrichment, Marketing Intelligence, Marketing Strategy, Payment History Analytics, Price Analysis, Pricing Analytics, Retail, Retail Analytics, Retail Intelligence, Retail POS Data Analysis, and Salary Benchmarking

1. Investment Research: Financial Services, Hedge Funds, Investing, Mergers & Acquisitions (M&A), Stock Picking, Venture Capital (VC)

2. Consumer Analysis: Consumer Data Enrichment, Consumer Intelligence

3. Market Data: AnalyticsB2C Data Enrichment, Bank Data Enrichment, Behavioral Analytics, Benchmarking, Customer Insights, Customer Intelligence, Data Enhancement, Data Enrichment, Data Intelligence, Data Modeling, Ecommerce Analysis, Ecommerce Data Enrichment, Economic Analysis, Financial Data Enrichment, Financial Intelligence, Local Economic Forecasting, Location-based Analytics, Market Analysis, Market Analytics, Market Intelligence, Market Potential Analysis, Market Research, Market Share Analysis, Sales, Sales Data Enrichment, Sales Enablement, Sales Insights, Sales Intelligence, Spending Analytics, Stock Market Predictions, and Trend Analysis

Data Quality Tools Market size was valued at USD 2.71 Billion in 2024 and is projected to reach USD 4.15 Billion by 2031, growing at a CAGR of 5.46% from 2024 to 2031.

Global Data Quality Tools Market Drivers

Growing Data Volume and Complexity: Sturdy data quality technologies are necessary to guarantee accurate, consistent, and trustworthy information because of the exponential increase in the volume and complexity of data supplied by companies. Growing Knowledge of Data Governance: Businesses are realizing how critical it is to uphold strict standards for data integrity and data governance. Tools for improving data quality are essential for advancing data governance programs. Needs for Regulatory Compliance: Adoption of data quality technologies is prompted by strict regulatory requirements, like GDPR, HIPAA, and other data protection rules, which aim to ensure compliance and reduce the risk of negative legal and financial outcomes. Growing Emphasis on Analytics and Business Intelligence (BI): The requirement for accurate and trustworthy data is highlighted by the increasing reliance on corporate intelligence and analytics for well-informed decision-making. Tools for improving data quality contribute to increased data accuracy for analytics and reporting. Initiatives for Data Integration and Migration: Companies engaged in data integration or migration initiatives understand how critical it is to preserve data quality throughout these procedures. The use of data quality technologies is essential for guaranteeing seamless transitions and avoiding inconsistent data. Real-time data quality management is in demand: Organizations looking to make prompt decisions based on precise and current information are driving an increased need for real-time data quality management systems. The emergence of cloud computing and big data: Strong data quality tools are required to manage many data sources, formats, and environments while upholding high data quality standards as big data and cloud computing solutions become more widely used. Pay attention to customer satisfaction and experience: Businesses are aware of how data quality affects customer happiness and experience. Establishing and maintaining consistent and accurate customer data is essential to fostering trust and providing individualized services. Preventing Fraud and Data-Related Errors: By detecting and fixing mistakes in real time, data quality technologies assist firms in preventing errors, discrepancies, and fraudulent activities while lowering the risk of monetary losses and reputational harm. Linking Master Data Management (MDM) Programs: Integrating with MDM solutions improves master data management overall and guarantees high-quality, accurate, and consistent maintenance of vital corporate information. Offerings for Data Quality as a Service (DQaaS): Data quality tools are now more widely available and scalable for companies of all sizes thanks to the development of Data Quality as a Service (DQaaS), which offers cloud-based solutions to firms.

This dataset contains the replication files for the RAPS paper titled “Product market competition, labor mobility, and the cross-section of stock returns” by Shamim Ahmed, Ziwen Bu, and Xiaoxia Ye.

Gain in-depth insights into Data Diode Security Products Market Report from Market Research Intellect, valued at USD 1.5 billion in 2024, and projected to grow to USD 3.2 billion by 2033 with a CAGR of 9.8% from 2026 to 2033.

Global Meter Data Management Product comes with the extensive industry analysis of development components, patterns, flows and sizes. The report also calculates present and past market values to forecast potential market management through the forecast period between 2024 - 2032. The report may be the best of what is a geographic area which expands the competitive landscape and industry perspective of the market.

Cloud Product Data Management (PDM) Software Market Outlook

The global Cloud Product Data Management (PDM) Software market size was valued at approximately USD 1.2 billion in 2023 and is anticipated to reach USD 3.5 billion by 2032, growing at a Compound Annual Growth Rate (CAGR) of 12.6% during the forecast period. This impressive growth can be attributed to the increasing adoption of cloud-based solutions, enhanced collaboration tools, and the rising demand for streamlined product lifecycle management processes.

One of the primary growth factors driving the Cloud PDM Software market is the growing need for real-time data accessibility and collaboration. Traditional PDM systems often face limitations in data accessibility and real-time collaboration, which can be a significant bottleneck for businesses aiming for faster time-to-market and efficient product development cycles. Cloud-based PDM solutions address these issues by providing seamless access to data from any location, allowing for improved team collaboration and decision-making processes. This is particularly valuable in industries where product complexity and the need for rapid innovation are paramount.

Another critical factor contributing to the market's growth is the increasing emphasis on reducing operational costs and enhancing flexibility. Cloud PDM solutions eliminate the need for substantial upfront investments in hardware and software infrastructure, offering a cost-effective alternative for organizations of all sizes. Additionally, the subscription-based pricing models associated with cloud solutions provide better financial flexibility, allowing companies to scale their usage based on current needs and budget constraints. This financial predictability is attractive, particularly for small and medium enterprises (SMEs), which often operate under stringent budget constraints.

The integration of advanced technologies, such as Artificial Intelligence (AI) and Machine Learning (ML), into cloud PDM software is another significant driver of market growth. These technologies enable more intelligent data management and provide predictive insights that can enhance product development processes. For instance, AI-driven analytics can identify potential design flaws or areas for improvement, thus reducing the risk of costly errors and enhancing product quality. The incorporation of such advanced features makes cloud-based PDM solutions an attractive proposition for forward-thinking organizations looking to leverage technology for competitive advantage.

Regionally, North America dominates the Cloud PDM Software market, owing to the high concentration of tech-savvy enterprises and the early adoption of cloud technologies. The presence of major market players and robust IT infrastructure further contribute to this dominance. However, the Asia Pacific region is expected to exhibit the highest growth rate during the forecast period. The rapid industrialization, increasing digital transformation initiatives, and growing awareness of the benefits of cloud-based solutions in emerging economies like China and India are significant contributing factors to this growth.

Component Analysis

The Cloud PDM Software market can be segmented by component into software and services. The software segment is expected to hold the largest market share due to the core functionality it provides in managing product data efficiently. Cloud PDM software typically includes various modules for managing product lifecycle data, which encompass everything from design and engineering to manufacturing and service. These software solutions are equipped with features like version control, BOM (Bill of Materials) management, and change management, which are essential for maintaining the consistency and accuracy of product data throughout its lifecycle.

The services segment, although smaller than the software segment, is anticipated to grow at a significant pace. Services include system integration, implementation, consulting, and support services that help organizations transition smoothly to cloud-based PDM solutions. As companies increasingly adopt these solutions, the demand for expert consultation and implementation services to ensure seamless integration with existing systems and processes will rise. Organizations often seek professional services to customize the cloud PDM software to their specific needs, train their staff, and provide ongoing support to resolve any issues that may arise post-deployment.

Furthermore, the rise of the "as-a-service" model is transforming the landscape

The Disk Based Data Fabric is projected to be valued at $1.2 billion in 2024, driven by factors such as increasing consumer awareness and the rising prevalence of industry-specific trends. The market is expected to grow at a CAGR of 10%, reaching approximately $3.1 billion by 2034.

Product Data Management (PDM) Software Market Outlook

The global Product Data Management (PDM) Software market is poised to witness significant growth with an estimated market size of USD 2.5 billion in 2023 projected to reach USD 5.3 billion by 2032, growing at a robust compound annual growth rate (CAGR) of 8.7% during the forecast period. The rapid digital transformation across industries is a key growth factor that is propelling the demand for PDM software. The increased need for efficient data management and enhanced collaboration in manufacturing and design processes is driving the adoption of PDM solutions globally. This market growth is further fueled by the rising adoption of cloud-based solutions and the integration of advanced technologies like AI and IoT in PDM systems.

One of the primary growth factors driving the PDM software market is the increasing complexity of product designs and the need to manage vast amounts of data associated with product development. As products become more complex, companies require advanced solutions to manage, share, and control product-related data efficiently. PDM software helps organizations streamline processes, reduce time-to-market, and enhance cross-functional collaboration, all of which are critical in maintaining a competitive edge. Moreover, the integration of PDM software with other enterprise solutions like ERP and PLM systems further enhances its value proposition, making it an indispensable tool for companies aiming to optimize their product lifecycle management.

The rising focus on digitalization and the need for real-time data access are also contributing significantly to the growth of the PDM software market. With the increasing adoption of Industry 4.0 initiatives, companies are leveraging digital tools to transform their operations. PDM software plays a crucial role in this transformation by providing a centralized platform for managing product data and facilitating seamless communication among dispersed teams. The ability to access and manage data remotely is particularly beneficial in the current global scenario where remote working has become prevalent. This trend is expected to continue driving the demand for PDM software solutions in the foreseeable future.

Another key factor contributing to the market growth is the growing emphasis on regulatory compliance and quality assurance in product development processes. Industries such as healthcare, aerospace, and defense are subject to stringent regulatory requirements, necessitating robust data management solutions like PDM software. These solutions help organizations maintain comprehensive records, ensure traceability, and facilitate compliance with industry standards, thereby mitigating risks and enhancing product quality. As regulatory landscapes become increasingly complex, the reliance on PDM software for compliance and quality management is expected to grow, further bolstering market expansion.

The regional outlook for the PDM software market indicates considerable growth prospects across various geographies. North America is currently the largest market for PDM software, driven by the presence of numerous manufacturing and technology firms that are early adopters of advanced data management solutions. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, fueled by rapid industrialization, increasing manufacturing activities, and rising investments in digital technologies. Meanwhile, Europe continues to be a significant market for PDM software, supported by strong automotive and aerospace sectors. Latin America and the Middle East & Africa regions are also expected to show steady growth, as companies in these regions increasingly recognize the value of digital transformation and data management solutions.

Deployment Type Analysis

Deployment type is a critical segment in the PDM software market, classified into on-premises and cloud-based solutions. On-premises deployment involves installing the software on the company's local servers, offering full control over data and security. This type of deployment is preferred by large enterprises with substantial IT infrastructure and stringent data security requirements. These organizations value the control on-premises solutions provide, allowing them to customize and integrate the software with their existing systems seamlessly. However, the initial investment and ongoing maintenance costs associated with on-premises deployment can be a barrier for some companies.

On the other hand, cloud-based PDM solutions have gained significant traction in recent y

This statistic shows the size of the global big data analytics services market related to healthcare in 2016 and a forecast for 2025, by application. It is predicted that by 2025 the market for health-related financial analytics services using big data will increase to over 13 billion U.S. dollars.

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Product Market size is rising upward in the past few years And it is estimated that the market will grow significantly in the forecasted period

Global Enterprise Information Management Market market valued at US$ 60.87 Billion in 2023, projected to grow 14.2% CAGR to US$ 201.09 Billion by 2032.

Gross domestic product (GDP) at market prices - annual data

Discover the latest insights from Market Research Intellect's Meter Data Management Product Market Report, valued at USD 1.2 billion in 2024, with significant growth projected to USD 2.5 billion by 2033 at a CAGR of 9.5% (2026-2033).

Product Market size is rising upward in the past few years And it is estimated that the market will grow significantly in the forecasted period

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Master Data Management Product Data Syndication (PDS) Market size was valued at USD 1.8 Billion in 2023 and is projected to reach USD 5.55 Billion by 2030, growing at a CAGR of 16.3 % during the forecast period 2024-2030.

Global Master Data Management Product Data Syndication (PDS) Market Drivers

The market drivers for the Master Data Management Product Data Syndication (PDS) Market can be influenced by various factors. These may include:

Proliferation of E-commerce: The volume and complexity of product data have increased exponentially as a result of the quick development of online marketplaces and e-commerce platforms. Businesses may effectively manage and disseminate correct, current product information across numerous channels with the use of master data management (MDM) systems that have product data syndication capabilities. This enhances web visibility, customer satisfaction, and sales conversion rates. Demand for Omnichannel Retailing: Retailers must guarantee consistency and accuracy in product information across all touchpoints as consumers expect a seamless shopping experience across multiple channels, including websites, mobile apps, social media platforms, and brick-and-mortar stores. Retailers may improve brand reputation and customer happiness by using MDM PDS solutions to synchronize product data in real-time and give consistent product information across numerous channels. Regulatory Compliance and Data Governance: For companies operating in highly regulated industries including healthcare, pharmaceuticals, food and beverage, and consumer goods, compliance with regulatory regulations, industry standards, and data governance rules is essential. MDM PDS solutions facilitate traceability, labelling, and reporting requirements while guaranteeing the accuracy, consistency, and completeness of product data. This helps enterprises stay compliant. Globalization and Expansion Initiatives: Businesses have difficulties with localization, language translation, and cultural adaption of product information as they enter new markets and regions. Organizations can support international expansion ambitions and market penetration goals by using MDM PDS solutions to manage multilingual product catalogues, adapt product descriptions and specifications, and adhere to regional rules and labelling requirements. Demand for Real-time Data Synchronization: Businesses must react swiftly to shifts in the market, client preferences, and competitive dynamics in the fast-paced business world of today. With real-time data synchronization capabilities provided by MDM PDS solutions, businesses can improve their agility and responsiveness by launching new goods more quickly, updating product information dynamically, and taking advantage of developing market opportunities. Pay Attention to Data Quality and Accuracy: Having accurate and trustworthy product data is crucial for increasing sales, decreasing returns, and building client loyalty. By removing duplicate entries, resolving discrepancies, standardizing and enhancing product information, and maintaining a single source of truth for product data throughout the company, MDM PDS solutions assist businesses in improving the quality of their data.