How can Fashion buyers leverage AI and Analytics?

Written by Maavrus

October 20, 2022


Video Transcript

Hi. Good morning. Traditionally, fashion buyers base their buying decisions on a combination of past performance data, inputs gathered from fashion conferences, fashion magazines, and supplier visits, and also their own gut instinct and experience. So obviously they do run the risk of wrong predictions.

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However, they can base their buying decisions on smart analytics and AI. They can reduce the risk of such wrong predictions and significantly enhance their gym noise.

What are the uses cases of AI in the Fashion Industry?

So, AI has got a few use cases already in the fashion industry.

One of the first ones is automated product tagging. So buyers can use visual AI and analytics tools to scan their products or samples and create product metadata on the fly like the color pattern, print, sleeve length colors, et cetera. AI can then help them analyze the performance not only at a product level but at each of the attribute levels or at a combination of various attributes.

Another area where Artificial Intelligence is being used significantly is in terms of reading and interpreting data from social media, from other eCommerce platforms, and from the runway to help buyers spot future fashion trends. Buyers could then overlay such insights gathered using AI on their own past product performance and consumer behavior to help build an optimum assortment mix that will connect well with their own consumer base.

They can also get insights, in real-time in terms of performance using AI and machine learning which will help them identify shifting trends in terms of consumer choices and enable them to be proactive in the way they engage with their customers. So, in summary, AI and analytics are enabling fashion buyers with creating product metadata, automated and on the fly.

Helping them analyze and predict performance at the attribute or a combination of attribute levels helps them to be relevant to their customers by looking at global fashion data and spotting trends, and enables them to be proactive to change managing customer needs and stock performance. Hope you found this insightful. Thank you.

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