E-commerce Product Dataset

Project Overview:

Objective

To establish a vast and varied dataset of e-commerce products, aiming to facilitate advancements in AI-driven e-commerce platforms, product recommendation systems, and inventory management solutions.

Scope

Compile images and metadata of a diverse range of e-commerce products across multiple categories and brands. Each product entry will have corresponding details like title, price, category, and customer reviews.

E-commerce Product Dataset
E-commerce Product Dataset
E-commerce Product Dataset
E-commerce Product Dataset

Sources

  • Collaboration with e-commerce platforms to access their product catalogs and images.
  • Data scraping from popular e-commerce websites, ensuring adherence to terms of use and data privacy regulations.
  • Partnering with small to medium e-commerce retailers for exclusive access to niche products.
E-commerce Product Dataset
E-commerce Product Dataset

Data Collection Metrics

  • Total Products: 1,000,000
  • Electronics: 200,000
  • Fashion & Apparel: 250,000
  • Home & Living: 150,000
  • Books & Stationery: 100,000
  • Others (Toys, Groceries, etc.): 300,000

Annotation Process

Stages

  1. Metadata Compilation: Product details such as title, description, brand, and price are compiled.
  2. Image Annotation: Relevant tags are assigned to product images to classify and describe them better.
  3. Review & Validation: Industry experts review the collated data for accuracy and coherence.

Annotation Metrics

  • Total Annotated Images: 1,200,000 (Some products have multiple images)
  • Average Annotation Time per Product: 5 minutes
E-commerce Product Dataset
E-commerce Product Dataset
E-commerce Product Dataset
E-commerce Product Dataset

Quality Assurance

Stages

Automated Data Consistency Checks: Ensure product details don’t have discrepancies (e.g., an electronics item listed under the fashion category).
Image Verification: Use AI models to cross-verify that product images match their described categories and tags.
Expert Review: Products with high customer views or purchases are manually reviewed to ensure data accuracy.

QA Metrics

  • Products Checked for Data Consistency: 600,000 (60% of total products)
  • Images Verified using AI Models: 720,000 (60% of total images)
  • Products Manually Reviewed: 50,000 (5% of total products)

Conclusion

The E-commerce Product Dataset is a pivotal resource for businesses aiming to integrate AI into their e-commerce platforms. By offering a comprehensive view of diverse products and their attributes, this dataset ensures better product recommendation, enhanced search functionalities, and improved customer experience on e-commerce platforms.

quality dataset

Quality Data Creation

Guaranteed TAT​

Guaranteed TAT

ISO 9001:2015, ISO/IEC 27001:2013 Certified​

ISO 9001:2015, ISO/IEC 27001:2013 Certified

HIPAA Compliance​

HIPAA Compliance

GDPR Compliance​

GDPR Compliance

Compliance and Security​

Compliance and Security

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