Global Insights on Fashion Trends by Style, Category & Color

The GenZ fashion trend dataset is a curated collection of fashion data aimed at understanding the preferences and behaviors of GenZ consumers. This sample dataset contains information and insights that can be used to analyze trends, product and style popularity enabling you to drive strategic decision making in the fashion, e-commerce and retail industry. Perfect for training and benchmarking multimodal AI models for fashion understanding, visual search, image-based recommendation, and automated tagging.

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Key attributes of this sample dataset:

- Brand: The brand of the product (e.g. "Zara", "Nike").
- Product Name: The name or description of the product (e.g. "Oversized hoodie").
- ID: Unique identifier for each record in the dataset.
- Color: The primary color or color combination of the product (e.g. "Black", "Pastel Blue").
- Save count: A metric indicating the number of items a product has been saved or favorited by a consumer, reflecting its popularity.
- Image: An image path or URL to the product image, which can be used for visual analysis or training computer vision models.
- Date: The time when the item was published.