The recent drive towards sustainability and efficiency in the fashion industry is intricately tied to the increasing use of Artificial intelligence. Because AI makes things faster, easier and saves many resources and energy, it is unequivocally accepted as the one solution for different industry problems. AI technology is being called upon to assist the studio in inventory, product tagging, and data analysis for demand prediction. All of these features can immensely benefit the industry in being more successful and taking decisive steps towards saving the environment and the less privileged sections of society.
Benefits of AI
AI brings so many benefits that one cannot recognize its merits:
- It saves time by reducing the number of steps required by traditional processes to get a product to go live. The warehouse to the studio takes no more than 60 minutes, while the conventional process ends up taking more than 10 days.
- Inventory is ideally done with the help of AI. Making calculations using customer data, the demands are perfectly predicted, which is why overproduction and stocking can be avoided.
- 3D product modelling and using AI-generated model poses can bring the best visuals to the customers so that they are happy with what they see and can be satisfied with the results of their research. Good product imagery can attract customers and keep them loyal if they find themselves represented well on the company’s catalogue.
(Product Marketing Manager)
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How is AI useful for product information and product image?
AI is beneficial in analyzing products and tagging them to provide ample information about the product and aid the searches that potential and actual customers are running in real-time. To break it up into a few parts, AI has specific uses for the fashion industry, especially retail. This article will look at some of these particular uses:
- Product attribute tagging:
Some AI applications have built-in fashion taggers that automatically assign labels to the different attributes of fashion products in great detail. Machines can learn these fashion attributes by processing both image and the text-based information present alongside it. This eliminates manual tagging and makes the whole process of catalogue management efficient.
2. Visual searching:
Customers love the system of one-click visual discovery. Searches like this help users get recommendations as well. They can upload an image of a picture of what they are looking for, and the technology immediately yields results by using algorithms that understand image context. It is beneficial because people often find it difficult to recall the exact keywords that match the product they are looking for. Thus simply uploading a picture for the same, if not better, results is much easier. It also helps make the fashion industry more accessible to people who have problems using the text typing search features.
a. Similar product recommendation: recommending products that are similar to the product they came for maximizes the chances of conversions. Some visual AI technologies can analyze fashion items in uploaded images and recommend identical-looking products from your catalogue. Even if there is an out-of-stock item, this function suggests similar alternative items already present in the shop. This will improve product visibility, increase the relevance of different products in your shop, and prevent customers from bouncing off the site.
b. Ensemble recommendations and trend analysis: AI can analyze credible fashion websites and blogs with the help of machine learning-based algorithms to arrive at trendy combinations of products used by influencers, models, fashion bloggers and help retailers create recommendations based on this knowledge. It almost compiles a piece of personal advice based shopping list for the customers.
The contribution of AI technology to the product image aspect of the fashion industry has been irreplaceable if a little underrated. It shouldn’t be an understatement to say that it will soon be used as an invaluable part of the industry itself.