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Visual AI And Its Application In The Fashion Industry

Visual AI technology uses computer vision and deep learning algorithms to create a system that creates a neural network that mimics the human brain and identifies various attributes in an image. AI analyzes thousands of images to better describe clothes.

The fashion industry is constantly adapting and changing the way it uses AI. Three typical embedded apps that increase conversions are AI product tagging, visual search, and AI styles. You can also get in touch with a professional company that uses artificial intelligence for clothing product photography.

Manual coding products are expensive and slow, with a high propensity for human error. Given the speed with which new fashion products are being launched and consumer demand, it is simply impossible to continue on this path. Visual AI technology can extract attributes from images including color, category, style, model, shape, length, and size.

This capability not only allows e-commerce fashion stores to measure and save money but also eliminates inappropriate search results and recommendations, as well as inaccurate cataloging that can lead to lost sales and customer frustration.

AI-powered fashion tags can increase conversions by:

1) Improve product discovery on and off-site by providing more accurate search results and improving SEO.

2) Increase average order size by improving your website's recommendation engine, resulting in larger cart sizes and fewer cart abandonments.

3) Enhanced personalization through significant attributes that can shape the buying journey based on the customer's personal preferences.

4) Improved inventory management due to AI tagging can identify popular trends and products in detail, providing insights that purchasing managers can use to make better decisions.