Big data meets fashion, makes companies trendsetters

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Big Data is all about turning extremely large quantities of data into useful information. When companies aggregate data and analyse them effectively, patterns emerge, ideas are born, and fashion companies become trend setters.
The retail sector in India is emerging as one of the largest sectors in the economy and is currently valued at $ 600 billion. Of this, about 90 per cent is unorganised retail and only 10 per cent is organised. However, the balance seems to be increasingly tilting towards the organised space. In fact, a recent study by Google stated that by 2020, India is expected to generate $100 billion online retail revenue out of which $35 billion will be through fashion e-commerce. Liberalisation of the FDI policy in retail sector will also provide further impetus to the entry of large international retailers, especially in the category of fashion and apparel.
The fashion industry in India is rapidly evolving with a constant blur of new and enviable trends, patterns, designs and colours. Today, with millennials being the primary target market, these trends emerge and subside with mind boggling speed and preferences patterns change in the blink of an eye. Keeping up with these trends and being able to predict customer demand is the key prerequisite for fashion companies to thrive today. For years, fashion companies have had previous data and intuition at its disposal to predict customer demands, which is now however, becoming irrelevant considering the fast-changing fashion trends and the tough competition in the market. More so, with more and more people getting brand conscious, it is becoming tougher for fashion companies to predict fashion trends on a real time basis. This is where Big Data steps in to save the day.
In true fashion industry style, bloggers and media alike have coined a different term for big data meeting fashion – ‘trend forecasting’ is the term Wall Street Journal contributor Kathy Gordon used to describe this information analysis. Big Data is all about turning extremely large quantities of data into useful information. When companies aggregate data and analyse them effectively, patterns emerge, ideas are born, and fashion companies become trend setters. In an industry where the success of next season’s collection hinges on picking the right patterns, colours, fabrics, shapes and sizes, Big Data is a big deal. Fashion companies and retailers can leverage Big Data analytics to quickly understand which trends are gaining momentum and which ones are losing ground at any point in the product’s lifecycle. With that insight, they can make smart adjustments to designs, production and marketing before launching a new collection, reducing the risk that the line won’t sell. Additionally, companies also optimise their supply chains as they can now decide what to produce more and should be stocked in inventory and what can be kept for made-to-order or what is needed immediately.
Fashion companies today, understand that the more data they collect and analyse on the basis of their interactions and engagements with customers, more will the individual preferences become easier to predict, in a more comprehensive and detailed way than ever before. This will, in turn, provide valuable insights for the fashion industry, from what products might perform best, in general, down to what will likely sell well in which store locations, what products are successful when placed next to each other and how to optimise retail experiences. Big data is extremely useful in a marketing capacity, using information like customer demographics and spending habits, in terms of how much they spend, on what and where. Data analytics helps the companies understand what their customers are looking for, on the basis of their search history, previous purchases and buying patterns and analyses trends arising from it. This is what helps companies stay ahead of competition – the ability to analyse and make actionable information and trends from the data collected.
As difficult it is to believe, Big Data is gradually becoming an integral appendage of one of the most intuition-based and unpredictable industry. In a universe where outfits and trends become dated with the launch or release of the next big thing, even top fashion companies like Prada, Gucci, Burberry, Chanel, Ralph Lauren and the rest of the bandwagon are relying heavily on Big Data Analytics and related technologies. In fact, designers and fashion companies often share photographs of their exclusive collections on Social Media (Facebook, Twitter, Instagram, Pinterest), which help them understand the trends and people’s response much before the curtain-raiser.
Sentiment analysis through collection of the responses (likes, shares, comments, re-tweets) helps the industry analyse every aspect of consumers’ demand — from the most loved colour to the most acceptable fi t.
With venture capitalists backing e-commerce platforms, the importance of the companies being profitable is heightened even further. Revenue generation and in turn increasing profitability is the key focus of e-commerce companies and this is where big data analytics steps in to save the day. Understanding customer preference, predicting customer demand and targeting customers through their chosen medium is possible through the undeniable contribution of big data analytics. Fashion companies, in order to stay ahead of the curve, are increasingly looking at not only adopting data analytics and related technologies but also implementing across departments to generate results for real time predictions and results.
With the liberalisation of the FDI policies, increasing demand for e-commerce and the dizzying pace of changing trends in the market place, fashion companies need to up their game to stay ahead in the race. Without a doubt, Big Data is starting to make a big impact on fashion, and more is yet to come. While the adoption is taking place slowly but gradually, it is the real time implementation and the customer experience which is the true differentiator. The brands and companies who can extract most wisdom from customer data and react to it most effectively, will ultimately emerge as the winner.
suniljose-mdteradataABOUT THE AUTHOR: Sunil Jose is MD, Teradata India. He joined Teradata in June 2014, bringing with him more than 25 years of technology industry leadership experience that encompasses enterprise software & hardware knowledge, general management, strategy development and executive management experience. Jose is also a member of the advisory board of At Teradata, he is responsible for providing leadership and overall strategic direction to the company’s India business overseeing fi eld operations including sales, customer management, marketing, consulting, professional services and support. Before joining Teradata, he was Vice President at Oracle managing its applications & cloud business operations. He started his career with HCL in 1990 and moved on to work in various geographies which included the Middle East.
The views and ideas expressed in this article are his own

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