Artificial Intelligence is redefining Indian fashion industry

Fashion traditionally has been seen as an expression of artistic sensibilities to enhance one’s personality. There have been several attempts in the past to quantify something as abstract as fashion – but most attempts have failed due to varying opinions on the very definition of fashion – until the turn of this century. Companies around the world have invested millions in writing software that would eventually be able to quantify the complexities of abstracts, such as fashion. Ambud Sharma, Founder of Escaro Royale Luxury (Escaro.in) feels that artificial intelligence is now helping with not only the merchandising decisions but also in fine-tuning the supply chain and creating customised and personalised fashion trends.

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. AI systems are now being utilised to correlate worldwide data to forecast trends on what merchandise needs to be produced and in what quantity. The typical variables include colours, patterns, designs and geographic tastes in materials. With access to more data and insights, the fashion designers can now take help from the AI platforms to design accordingly. This saves time and money that was earlier wasted in experimentation. The designers can now be more confident in the sales potential of their merchandise. 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. The resulting insights very often are counter-intuitive, and hence help in more accurate design decisions.

AI in Consumer Insights

It is important to know your customer, and even more important to know your consumers’ buying and spending behaviour. There are thousands of digital footprints that we leave behind each day when we engage over the Internet – be it reading an article, reviewing a product or signing up for an event. These footprints are a goldmine for the fashion industry – since it helps in identifying what we call a digital persona of a person in the AI world. Using this info, it is possible to accurately map a person’s digital persona to their potential interests. This is especially amplified when an AI system knows what a person bought and when – thus projecting and reinforcing a potential consumer’s interest in a fashion product through targeted advertising. For instance, if someone reads about Harley Davidson bikes, they can then be targeted to see ads related to high fashion leather biker shoes. The power of consumer insights allows for gauging the market size as well – thus helping brands in ascertaining the quantities to be produced. It is well said — A machine is a much more faithful friend with another machine – than a human.

AI in Retail Intelligence

Retail is complex but can be handled seamlessly using AI. A consumer’s retail interaction, be it in a showroom or on a website is extremely important and hear-worthy. The feedback received in real-time from the consumers can be extrapolated to ascertain whether the consumer demand is being sufficed or not – and if the consumer is looking for something that isn’t available. Also, the real-time digital feedback mechanisms can quantify the customer satisfaction – thus assisting in customer retention. This feedback, if correlated correctly, can be used as a guiding tool for future merchandising and retail dominance. Though this can be done manually, it can be done faster, better, cheaper and more accurately by using the processing capability of an AI platform.

AI in Consumer Interaction and Engagement:

AI-based chat-bots are being used now to seamlessly interact with consumers. 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. Additionally, the information collected through chat-bots is regularly analyzed and correlated by AI central commands for deeper insights about consumer base. Customised and automated messaging systems can keep the consumers abreast with the latest offerings of a fashion brand; thus keeping the customers engaged through the information that is unique & customized to his/her taste.

AI in Inventory Management

Most fashion brands of today understand the importance of a well-orchestrated supply chain and inventory management. There is nothing more frustrating than having inventory that doesn’t sell and not having inventory that sells well. This is where AI-based inventory management systems come to rescue. These systems understand the velocity of sales, many times global sales, and provide insights into what is selling and how fast. More importantly, they help in providing recommendations on inventory optimization across markets – thus ensuring that the right product is available in the right market. 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. 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.

In all, something as abstract as fashion can be more-or-less quantified using artificial intelligence to the point that it may very well one day be able to make automated design and product decisions for current and future trends. For fashion brands, the potential of AI taking over these day to day decisions is very high and will only increase with time. As digital transactions and interactions increase, and more and more data is produced, the fashion brands can only look up to powerful AI platforms with humongous data-crunching capacities to assist them to navigate complex digital waters.

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