Bestseller Book Pricing Analysis Dataset

Columns

• amtsave: The monetary amount saved by the customer due to discounts.
• brand: The published brand or imprint associated with the book.
• breadcrumbs: Navigational path or category hierarchy of the product on the site.
• country: The country associated with the product listing (India).
• desc: A short description of the book.
• discount: The percentage discount applied to the list price.
• domain: The specific Paytm catalogue domain used for the listing (e.g., https://catalog.paytm.com).
• gallery: URL links to supplementary images, though often null.
• image: The primary URL link to the product's image.
• insertedon: The date the data record was crawled or inserted.
• list_price: The original manufacturer's suggested retail price (maximum value observed is 12,801).
• model: The specific model number or identification for the product, often containing embedded JSON details.
• name: The title and sometimes author/edition of the book.
• other_sellers: Information regarding alternative vendors for the product.
• payment_methods_supported: A list of accepted payment types (e.g., Credit Card, Debit Card, EMI).
• productcode: A unique identification number used by Paytm for the product.
• selling_price: The final price at which the book is sold (maximum value observed is 12,801).
• specifications: Detailed attributes of the book, often in JSON format (e.g., binding, language, publication year).
• type: Product type classification.
• uniq_id: A unique identifier for the specific record.
• url: The direct URL link to the product page.
• weight: The physical weight of the product.

Distribution

Usage

• Pricing and Discount Analysis: Researching competitive pricing strategies and the effectiveness of discount percentages in the Indian e-commerce book sector.
• Market Trend Identification: Analysing product specifications, popular authors, and publication years to determine current best-selling trends.
• E-commerce Modelling: Creating models focused on pricing elasticity or building initial recommendation engines.

Coverage

• Geographic Scope: India.
• Time Range: The records were captured on a specific date, 18 May 2016.
• Data Source: Web-crawled data, with an expected annual update frequency.

License

Who Can Use It

• E-commerce Strategists: To benchmark list price versus selling price and understand margin potential.
• Data Analysts: For exploring complex product attributes embedded in JSON fields and calculating sales metrics.
• Retail Businesses: Seeking insights into the competitive landscape of online book sales in India.

Dataset Name Suggestions

• Paytm India Bestselling Books Catalogue
• Indian E-commerce Book Pricing Data (2016)
• Paytm Product Specification and Sales Records
• Bestseller Book Pricing Analysis Dataset

Attributes