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how brands are changing consumer experience

April 28, 2022
Leigh B. Maynard
Read Time : 5 Minutes

With fashion and technology interlocking in an unstoppable manner, purely digital closets don’t seem like a far-off reality, says our guest author.

Fashion is the manifestation of one’s personality. Each one of us is so unique and distinct that technology, one would imagine, can never permeate this world. Yet, when it came to forecasting the future of fashion, thirty-two per cent (see below) said digital is the growth driver that they would veer towards.

Technology in fashion is gearing up to provide solutions in sourcing, demand forecasting, supply chain and marketing. Artificial intelligence (AI) innovations of today don’t just accumulate data, but also accelerate the creative process and help in every aspect of manufacturing and distribution – starting from capacity planning to automated production and delivery.

The COVID pandemic has led technology to step in and give momentum to the industry, which was on the verge of an existential crisis.

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A fashion show without its sartorial theatrics and elaborate productions was an unborn idea, until now. Enter the likes of US-based Bigthinx. It offers AI for fashion and retail.

Italian fashion giant Prada’s Spring/Summer 2021 Womenswear Show was one of the most hotly anticipated on the Milan Fashion Week schedule. And though there was no physical show, the brand delivered one of the best virtual runway presentations to date.

Virtual trials during online shopping & mass customisation

One major pain point for consumers, while shopping online, is to buy clothes without having an idea of how these pieces, which look aspirational on models, will appear on normal mortals, consequently resulting in higher return/exchange rates.

Today, AI can help bring the offline experience to the online world by helping resolve the two biggest pain points in online fashion – size and look. Italian fashion giant Gucci, for instance, uses augmented reality (AR) to allow customers to try on sneakers via its app or Snapchat. By pointing their smartphone device at their feet, customers can see how a shoe would look from various angles.

Mobile body scanning gives information beyond just body measurements. Body shape data can be broadly interpreted to allow clothing brands to deliver mass customisation, intermediate sizes and optimise production, according to their audience.

AI styling – virtual shopping assistant

We now live in a world where one can use an artificially intelligent stylist. One who can milk image recognition technology to squeeze out product and style information from pictures, feed that to its AI engine, and produce contextual and personalised results for fashion shopping.

With an understanding of natural language, images, voice and the context of the fashion query, the virtual assistant even knows the difference between ‘dress shirts’ and ‘shirt dresses’. The virtual assistant is user friendly and as efficient as a fashion sales assistant.

AI can also help map, and analyses, browsing patterns to come up with recommendation, preference of colour pattern necklines, sleeve length, styles, etc. All mapped to perfection. Some companies even claim to have styling solutions based on body measurements/variation and skin tone, which would be available at the tap of a button.

To begin with, while there is no Holy Grail algorithm capable of forecasting demand in all phases of the life cycle (pre-in-post season), there are definitely ways to produce closer results. Bengaluru-based Stylumia is one such company which collects and analyses publicly available global data to rank product trends, providing fashion designers, retail buyers and merchandisers with a much deeper understanding of real-time consumer demand signals. Pre-season planning, as well as unexpected in-season events, like the pandemic.

AI fashion – no designers

But can there be fashion without designers? Today, the AI race is on to offer computer generated apparel solutions, ranging from jeans and shirts to shoes, which help to reduce time to design and go to market. Armed with knowledge from fashion portals, social media and others, machine learning is able to reduce the time to (go to) market from 180 to 45 days.

Undeniably, fashion labels are facing stronger than ever competition from their avant-garde counterparts. But with fashion and technology interlocking in an unstoppable manner, purely digital closets don’t seem like a far-off reality. Fashion has been at the forefront of the digital revolution and, with technology now making inroads into the complete life cycle, the future is truly here!

(The author is senior vice president marketing at DaMENSCH.)

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