This automatic filling machines Factory saves time and money that was earlier wasted in experimentation. With access to more data and insights, the fashion designers can now take help from the AI platforms to design accordingly. Using this info, it is possible to accurately map a person’s digital persona to their potential interests. The typical variables include colours, patterns, designs and geographic tastes in materials. A machine is a much more faithful friend with another machine – than a human. The resulting insights very often are counter-intuitive, and hence help in more accurate design decisions. Ambud Sharma, Founder of Escaro Royale Luxury (Escaro. Companies around the world have invested millions in writing software that would eventually be able to quantify the complexities of abstracts, such as fashion.
A lot of trends that may be seen as useless, may well be defined as valuable when the AI systems and machine learning engines do the data crunching.AI in Inventory ManagementMost fashion brands of today understand the importance of a well-orchestrated supply chain and inventory management.AI in Consumer Interaction and Engagement:AI-based chat-bots are being used now to seamlessly interact with consumers. The AI platforms can be taught about the regional colour, design and material preferences of consumers – and then emerging patterns of information can be used to make intelligent supply chain decisions. Further, smoke and fire detectors have been installed at every 50m of the distance,” he said.This is where AI-based inventory management systems come to rescue.AI in Fashion Forecasting With the exponential increase in data and events pertaining to fashion each season, it is humanly impossible to collate and correlate all data to understand the future trends.
There is nothing more frustrating than having inventory that doesn’t sell and not having inventory that sells well. These chat-bots learn skills over time by interacting with a various set of customers and they are able to handle most questions and concerns on their own – not to mention that they don’t change shifts or get tired like their human counterparts – thus leading to higher consumer satisfaction. For sized products, like shoes and apparels, these intelligent platforms provide market-wise recommendation in sizing to ensure that the correct set of sizes are available in applicable markets. More importantly, they help in providing recommendations on inventory optimization across markets – thus ensuring that the right product is available in the right market. These systems understand the velocity of sales, many times global sales, and provide insights into what is selling and how fast. This feedback, if correlated correctly, can be used as a guiding tool for future merchandising and retail dominance. AI systems are now being utilised to correlate worldwide data to forecast trends on what merchandise needs to be produced and in what quantity.
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