This is the seventh and final part of the multi-part blog series on AI/ML within the Fashion Retail Space. The seventh and final part will help you understand how web-based retailers can leverage AI/ML to facilitate customer delight. We will also be looping back and looking at how AI/ML are revamping the fashion space, from a bird’s eye-view perspective.

Retail returns are an expensive affair. Whether it be shipping fees, discarded packaging, inventory shortage, or damaged merch, returns impact businesses.

Today’s culture is shaped around the concept of convenience. Life is geared towards being lived on the go, and as it is, retail brands are accomplices in generating economic and environmental waste. There have been certain commentators who’ve gone so far as putting down the free return policy. In the present scenario of web commerce, it would be difficult to envision a planet where web retailers came to a joint decision to roll back their return policy. It must be done across the board; several sellers could be disenfranchising themselves and playing second fiddle to outlets that continued to accommodate clients with two-day shipping.

⁂ Hobby purchases and niche taste apart, several shoppers are needing of friendly return policies.

⁂ It is difficult to commit to purchasing without seeing the product.

⁂ This is one of the major advantages that brick-and-mortar retail holds over web-based retail.

⁂ AR/VR tech is experiencing growth but is yet to become mainstream. This could even up the playing field.

⁂ Even when it does, the physical touch and feel is an aspect that AR/VR will have problems with.

Customers are resistant to making commitments they are concerned about the product and fitment. However, on an increasing basis, web-based retailers are resorting to AI/ML to facilitate clients not just to find out about new products that might pique their interest, also to detect SKUs and particular sizes they’ll be very happy with storing in their closet.

Let’s hold on to this thought for a while.

AI in Fashion – what’s up with it?

AI is being deployed in various ways within the fashion space. The use case that first comes to mind is smart digital assistants.

⁂ These helpers suggest clothing articles to clients based on their physical attributes.

⁂ Clients are then provided precise sizing based on the information they have put into the system.

⁂The sizing precision is fine-tuned from feedback from other clients.

⁂ 40% of web purchases are eventually returned.

⁂ The utilization of AI in client advisory is critical as it facilitates customer delight and a reduced number of returns.

AI can additionally be leveraged for practical purposes, in addition to ones concerned with productivity. By logging sales figures, returns, and web-based purchases, retailers can maintain an understanding of inventory and determine which shops are requiring which products. Based on a survey by Capgemini, AI could assist retailers in saving $340 billion every year – this is possible by the current year.

This forecasted number is massive and one can understand why several retailers, especially web-based retailers, are looking to integrate innovative technologies like AI into their operations.

Retail Returns Revisited

The next significant development in the domain of Recommendation Engines

But it is to be noted that the concentration for almost all customization tools has been improving average cart sizes and client lifetime value. This is a sort of tunnel vision that gives priority to the revenue aspect but is neglectful of preserving the top line.

Utilizing the same tech but going one step beyond to undertake analysis of return-based data points, traders can allocate more weighted value on product upselling and cross-selling they know shoppers are more probable to buy and retain. Consequentially, fashion brands will probably see increased client delight and appropriate and relevant enhancements to their profits. While this might not be a unique idea, it has value in resurfacing as the retail return issue is only predicted to expand with time.

AI/ML – The intersection of Fashion and Sustainability

The international fashion industry has for long, been one of the most egregious offenders with regards to pollution. It contributes towards:

The pressing issue to be observed here is to hold the belief that this domain can go on mass-manufacturing clothing to maintain the pace with this fast fashion epidemic. But AI can be leveraged at several phases of production to counter this dilemma, consequentially creating a reduction in inventory levels. AI provides a sustainable solution to the fashion industry, minimizing cumulative inventory levels by 20-50% in addition to enhancing working conditions within the fashion space.

An array of emergent tech is utilized to minimize errors in trend forecasting and predict trends more precisely which would minimize the amount of clothing produced and then subsequently not used.

Half a decade ago, in 2017, an Amazon team in SF developed an unnamed AI “fashion designer”. They produced an algorithm that undertakes an analysis of imagery and replicates the style, making fresh items in styles that resemble the analyzed imagery. We’ve not yet attained haute couture levels, but these fresh and emergent technologies predict upcoming potentialities.

A business that considers sustainability to be one of the forerunning considerations of its business framework and has held this belief for years is Toms. Initiated in May 2006 by Blake Mycoskie, their mission is:

‘TOMS’ intends to assist in enhancing lives through business, as a core value, and this is integrated into all the things that they do. They believe in collaborating with others who also have these values and carry out their business in an ethical and compliant fashion.

With every pair of Toms purchased, a pair is automatically donated to underprivileged locations around the world. As of today, Toms has given out more than 96.5 million pairs of shoes. These shoes are eco-friendly and sustainable as they are made from materials such as organic cotton, natural hemp, and recycled polyester. These fabrics are utilized on the upper, liner, and/or the sole of the shoe. They just don’t donate shoes but they also make donations of 33.3% of their net profit.

⁂ For every $3 that is earned by Toms,

⁂ $1 is donated to underprivileged societies.

⁂ Toms is dedicated to the upliftment of underprivileged societies the world over.

⁂ In 2011, they began donating prescription eyewear to ones in need

⁂ In 2014, they started providing 140l of water for each person, fulfilling their needs for a week.

⁂ In 2015, they imparted training for skilled midwives and put out safe birth kits.

⁂ They are on record as providing safe births for >25k mothers.

Toms is a beacon of sustainability and ethics in business.

Improving involvement in Fit Technology

Yet another vendor, True Fit, attempts to go one step beyond to power customized product suggestions based on an array of factors, which includes fit. In collaboration with Google Cloud, True Fit provides fashion retailers the “Fashion Genome” which is a major linked dataset for the fashion retail space. This paradigm shift, this evolution towards data-driven customization speaks to how fitment tech is becoming a plus point for both retail outlets and customers.

Accommodating return policies are so commonplace as they minimize friction in the purchase procedure. However, fashion retailers should take into consideration integrating AI and ML utilities to assist in increasing client delight when it comes to identifying an ideal fit as even the procedure of repackaging a return order is an unwanted outcome for your shoppers, and your profits.

Designer’s Active ML Deployments

⁂ H&M is a forerunner in this category. It is a Swedish Company.

⁂ Created by Erling Persson in 1947, H&M mass manufactures clothing globally.

⁂ Artificial Intelligence and Advanced Analytics are actively deployed to enhance their business

⁂ H&M is enhancing the way trends are identified and plan logistics

⁂ In addition, they use it to reduce the number of discounted sales, and unsold stock by using AI tech

⁂ It is used to analyze supply/demand and assign adequate goods to every outlet

⁂ This, in turn, reduces the number of wasted clothing.

⁂ At H&M, they are bringing together analytics and AI with human intelligence to use what is referred to as “Amplified Intelligence”.

Conclusion

AI confers several advantages on the fashion space, which includes the utilization of web-based fashion assistants to enhance the client experience, trend forecasting, and creating more sustainable solutions. In a customer-driven age, we must get the correct messaging across to them and encourage them to take part in this discourse as we evolve onwards towards a digital-universal age.