Big data technology is changing the face of fashion and the way the industry operates in a big way. Big data is all about turning huge quantities of data into insightful and actionable business information. When you cluster data, patterns emerge, ideas are born, and you make better strategic decisions. In an industry where the success of next season’s collection hinges on picking the right patterns, colors, fabrics, shapes, and sizes, big data is a big deal.
I’ve seen this specific effect of big data personally as some of the clients of my data science consultancy are in the fashion industry. The industry is hyper-competitive and forward thinking clothing designers, lines and showrooms are always searching for ways to gain advantage. One big advantage is in smart placement of advertising dollars. Using machine learning techniques, I’ve managed the process of associating fashion brands with high-profile non-fashion brands, such as musicians, actors, athletes, etc., for cross-advertising purposes. As it turns out, it is useful to know that Coach handbags are popular with Katy Perry fans.
One explanation for why fashion is at the forefront of this area of technology is because of the importance of unstructured social media data sets to the application of data science techniques. Fashion has been in social media from the beginning, so there is a definite comfort level there. It is more a matter of warehousing and analyzing the social media data in a productive way. Machine learning comes to the rescue here.
There are more than a billion people on social networks, and most of them wear clothes. Coupled with the fact that fashion is social by nature, it’s no surprise that millions of Tweets, Likes, comments, shares, pins, favorites, and Instagrams about what’s hot and what’s not appear online every day.
A growing number of recognizable designers, brands, and retailers are tapping into leading social networks to get a glimpse of the consumer mindset. They want to collect customer opinions, ideas, and feedback on products and trends from the start of the design process all the way to the Facebook photo you post wearing a “hot new dress.” All this new customer interaction adds up to a growing base of data for an industry going through a cultural change centered around technology.
Daniel – Managing Editor, insideBIGDATA