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Combating challenges in fast fashion using AI: Myntra’s way

by Apparel Resources

10-January-2019  |  10 mins read

Smart Retail
Image Source: www.forbes.com

The fashion cycle now moves faster than ever before considering the fact that the consumers’ demand is quite diversified and the recent trends suggest that the industry has therefore shifted to the concept of fast fashion. Wikipedia defines fast fashion as a term used by the fashion retailers to express that designs move from catwalk quickly to capture the current fashion trend. Today customers want clothes that are trendy as well as affordable at the same time, a rare and difficult combination. The AI technology should be thanked for saving the life of retailers by helping them deal with the challenges that occur while working on this combination. Team Apparel Resources, in this article, discusses how the use of artificial intelligence (AI) has helped the retailers not only in facing the challenges but also in achieving greater profits.

Machine-generated designs at Myntra!!

Analysing a situation and making decisions depending upon the need of the current scenario, irrespective of the industry, is always the appropriate strategy. Many of the fast-fashion retailers, nowadays, do not achieve the planned sales target as they fail to analyse the decision they make based on their sales strategies. This leads to a situation where their competitors find it easier to overtake them in sales and consumer reach, which is one of the biggest challenges in today’s fashion retail, both in e-commerce and offline.

To deal with such challenges, fashion retailers should start measuring what matters to them as it is the only way for companies to survive in the near future. However, the question that arises is ‘how’. Myntra, an Indian e-commerce platform, has set an example by using AI to launch two fast-fashion brands: ‘Moda Rapido’ and ‘Here and Now’, whose designs are completely computer-generated. Notably, these two brands contributed 12.5 per cent in total sales acquired by Myntra’s private labels in 2016, a year after they were launched in 2015.

How is the fashion retailer using the technology…

The majority of Myntra’s business comes from its online platform (both e-commerce and m-commerce) and notably its app already has elements of AI incorporated into it, using which it provides automated suggestions on complementary looks and accessories to go for along with a particular, selected product. The company’s Rapid Technology project was aimed at delivering fast-fashion products to its customers. This platform worked by analysing the sales data of Myntra and Flipkart and also the fashion trends collected by trawling Instagram, Pinterest, fashion magazines and similar sources. Based on the analysis, the technology suggested the list of attributes like type of collars, sleeves, cuts, colours and other features that are currently popular with the customers. However, the technology was slow to keep pace with the standards of the tech world as the suggestions were in the form of text and, therefore, required an extra amount of time to create a design out of the given suggestions.

The need to respond much faster to the market raised the demand to come up with a technology that will give results in the form of images of the total design. This will eliminate the extra time spent on identifying the trends of the attributes that were given in the form of text and then converting them to designs.

For this, Myntra started applying the new innovative technology on its basic T-shirt range due to the product’s simplicity. It was found that the new developed systems were capable of producing the whole image of the garment based on the favourable attributes discovered. This not only reduced the time involved in bringing a specific style to the market but also enhanced the chances of success of the same technology to be implemented in other categories too.

This implementation not only created machine-generated high trend garments but also helped the brand to massively shrink the manufacturing process from 180 days to 35 days. The software helped the company to get the quickest of the supply chain. The amount of time that was earlier spent by designers to analyse the latest trends, colours and other such attributes to create designs, are now all being done by the machines within no time. The process that took weeks has now been reduced to few hours and therefore it has made the production cycle short.

Measuring what is being sold the most and what people are liking the most helps the brands know what will be sold more and what kind of products the customers will be willing to buy from them. This will help them in manufacturing the right product which will further help them in availing a number of benefits starting from increase in sales, lower return rate to lower leftover stock that has not been sold and will ultimately have to be disposed or sold at a much lower price, resulting in a loss to the brand or retailer.

The new technological developments, therefore, have solutions to make our processes much more simplified. The solution providers in this field, such as Style Lumia, Hybrid and Rapid technology, are changing the way people have being dealing with fast fashion. Technologies like these have been a helping hand for the retailers to come out more responsive to the situations by improving upon the lead time and reducing the fashion cycle making clothes available to the customer in a much lesser time.

The advantage of this technology is that it works by analysing the sales data from different e-commerce websites as well as the latest fashion trends collected by trawling Instagram, Pinterest, fashion magazine and similar sources. The software then comes up with a list of attributes or an image showing the latest trends in fashion. The software also creates designs by analysing the best of the attributes like sleeves, collars and other features that are currently popular with customers.

The technology is revolutionising the way we deal with challenges

This revolutionary technology is transforming the apparel industry in a big way by helping to eliminate the limitations that the manual designers previously had such as the time consumed in analysing trends and creating designs out of the identified trend. Previously, this whole procedure took few weeks. However, with the introduction of such technology, the procedure has become much simpler, making it possible for the retailers to bring in new styles far more quickly to the market.

There are many brands and solution providers using this technology such as StitchFix, an American online retailer, which has a tech platform called Hybrid Design similar to this technology that automates fashion designs using AI. The online retailer has combined the expertise of personal stylists with the insight and efficiency of AI to analyse data on style trends, body measurements, customer feedback and preferences to arm the human stylists with a culled-down version of possible recommendations. This helps the company provide its customers personalised style recommendations that fit their lifestyle and budgets.

StyleLumia is another similar solution provider that helps the retailers by analysing and delivering structured solutions from the unstructured data sources with the use of advance AI and computer vision. The software uses images, user behaviour data, textual descriptions on social media and similar sites as its source data. The result helps the retailers and brands to make laser-edge informed decision for current course correction and future decision.