TheNFAPost Podcast
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Using Azure Machine Learning, Myntra is enabling international and domestic fashion brands to cater better to consumer demands in the current COVID situation and beyond.

Chennai, NFAPost: As the threat of COVID-19 started emerging in the country, the biggest worry on Amar Nagaram’s mind was the safety of his employees, delivery partners, and customers. As the CEO of Myntra, India’s leading online fashion retailer, Nagaram and his management team not only had to think about business continuity but more importantly the role that the organisation could play in a world so profoundly changed by the pandemic.

Like almost every business, Myntra also had to move all its employees to work from home overnight just days before one of its biggest annual sale events.

“From a vibrant office to working from home, I was pleasantly surprised how quickly we adapted to working from home. Thanks to being on Azure, we were able to deliver one of our most successful End of Reason Sale remotely,” Myntra CEO Amar Nagaram said.

Taking stock

For Myntra, which has a strong delivery network across 27,000 PIN codes in India, one of the first order of business was to secure essential personal protective equipment like face masks, which were in acute short supply and difficult to procure.

“We realised that face masks were the need of the hour. Together, with our partners, we decided to serve our customers in the most meaningful way right at their doorsteps,” said Nagaram.

Myntra partnered with Wildcraft, India’s fastest-growing outdoor gear, clothing, and footwear brand, to manufacture and sell face masks on its platform. Within days, other brands too launched their masks and a new category for masks emerged on Myntra.

“One of the things I’ve realised in the past three months, after how we regrouped, recouped, and reimagined our business, is that the pandemic showcased the significant role we can play in an unfortunate situation like this,” he added.

Selling what customers want

Face masks were just the beginning. With physical brick and mortar stores shut due to lockdowns and consumers staying away from shopping centres, major fashion brands had to reimagine their go-to-market strategy overnight. Myntra found itself uniquely placed to help them.

Right before the pandemic, Myntra had migrated its entire data platform including supply chain management, inventory, and website capabilities to Microsoft Azure. Apart from providing Myntra the elasticity to cater to demand spikes, Azure’s built-in Machine Learning tools expedited the development of advanced analytics capabilities to understand their consumers better.

“The amount of data from which we learn today is six to seven times more than the pre-COVID world. Microsoft Azure has enabled us to scale-up overnight and Azure Machine Learning gave us the right kind of levers to expedite our learnings,” Nagaram said.

As a result, right from the early days of the lockdown, Myntra was able to provide actionable insights to partner brands about what consumers were looking for and helped them prioritize their offerings accordingly.

Some of the immediate insights from what consumers were searching, viewing, and buying, highlighted how a larger set of customers was now staying at home, balancing between work and household chores, and needed clothes that were functional yet comfortable.

As a result, Myntra was one of the first out of the block to identify these changing needs and introduced ‘Work from Home Edit’ on its app that focussed on categories like comfort wear, loungewear, athleisure, home wear, and ethnic wear.

“The use of technology to generate actionable insights is a big reason for the success of our recent End of Reason Sale. We’re now selling what consumers want and not what we want to sell. The credit also goes to the brands that responded to these insights in a matter of days and not weeks,” said Myntra CEO.

Apart from gleaning insights from what consumers are searching and buying, Myntra is also understanding the aspirations of its consumers, thanks to Myntra Studio. A personalised content destination, it features fashion style guides from influencers and brands that users can shop directly from Myntra.

During the early days of the lockdown, insights from customer behaviour on Myntra Studio suggested a spike in interaction with certain categories like DIY makeup, among others. These insights enabled Myntra’s partner brands to move their inventory from their physical stores, which were shut due to the lockdown, to Myntra.

“We saw that COVID blurred the lines between online and offline retail. The economy is going to be more digital for sure, but retail isn’t going to be online only. It will be a mix of online and offline,” he said, adding that they have witnessed offline retail embracing technology at a large scale in the last three months.

Some of the brands that used Myntra’s omni-channel technology during the End of Reason were able to sell inventories out of their stores that they could not sell due to the lockdown.

Making data fashionable

“I’ve always believed the fashion industry could use technology to disrupt some of the orthodox practices that have been going on for a very long time and make them more eco-friendly and business friendly,” he said.

“The industry has always relied on the concept of seasons—Spring-Summer and Autumn-Winter. The trends are decided a year in advance, and they go into production. It is the bets that the industry makes—this design will work, and that pattern will work— that leads to the unsold inventory problem which the industry faces,” he added.

Myntra is disrupting the age-old practices of the fashion industry with data and machine learning. It is now able to provide brands with consumer insights that take into account not only the consumer’s profile but also variables like their location, the weather patterns, and what other consumers with similar parameters are buying.

The Holy Grail, however, is to be able to provide a personalised fashion shopping experience to consumers. Myntra already has implemented one of the most comprehensive sizes and fit recommendations when customers are buying on its platform, which has brought down returns significantly. The next phase is to be able to provide highly customised experiences to its users.

“We’re trying to learn about our consumers at an individual level. So when you open our app, we should be able to show things based on your style preferences,” Nagaram said. “Having the right Cloud and AI partner is key to enable this. We’re happy to have Microsoft on our side as a partner to make it happen,” he added.

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