Fashion CMO: See what happens when Fashion meets Big Data

    As a fashion CMO, you may have noticed the huge impact Big Data has made to the business world. We can’t help wondering, what will Big Data change the Fashion world that we deeply love so much? What will happen when Fashion meets Big Data? As an Integrated Marketing Communications student at Medill School of Northwestern University, and a keen fashion follower, I have identified two articles that define the importance of big data in fashion industry.

    The first article “Big data may be fashion industry’s next must-have accessory” states that big data may become the next new thing to hit the fashion industry’s runways. Researchers were able to identify a network of influence among major designers and track how those style trends moved through the industry by analyzing relevant words and phrases from fashion reviews. While professionals in many industries are welcoming data analytics, this type of analysis may meet some skepticism from fashion designers, who view their work as a form of art and more difficult to quantify. Fashion styles may also be predicted by analyzing real-time data from social media sites, such as Twitter, Pinterest and Instagram, which is pretty cool.

                                
                                                          Source: Cable Fashion Show

    Similarly, this article below "What does data and analytics mean for the fashion industry" states that by using tools such as Google Analytics, the fashion industry should be able to accurately forecast what consumers want to buy and not what designers want them to buy, hence they will be able to end up growth-hacking their business. Social shopping sites, such as Krush, have worked wonders in connecting the predictive power of analytics and e-commerce in the fashion industry. If we can get the right information about the right fashion to the right people at the right time, businesses will be able to make the right business decisions to forecast the next fashion trends, which is the rise of “Fashion Analytics”.

    From my studies from these two articles and my data analytics background in the Medill IMC program, I think there are several steps can be followed to think about improving “Fashion Analytics”, since it’s becoming the heart of almost all the fashion industry developments:

• Develop Better Analytics - Better data analytics can directly help improve profitability. Better data analytics can help optimize every aspect of the fashion business, including the supply chain, customer segmentation, spotting hot items, monitoring profitability. 
• Create Social Communities - Social fashion communities have become extremely important, you shouldn’t ignore. It has become a real-time source of data analytics for consumers and brands alike, and social network analytics can reveal who are the key fashion influencers.
• Utilize Analytical Customization - Customization and iteration become doable. It is now possible to create more “data analytics” fashion. Companies can move to a more iterative, analytics-based customized approach, where clothes are made in smaller batches based on the particular desires of an individual or community.

    In all, big data is starting to influence fashion industry in every way, and more is yet to come. Through social media, which is bigger than you think, the industry is opening its door to millions of fashion chasers who are eager to share their opinions. The brands can then extract the most wisdom from the tremendous data resources and change them into actionable strategies.


The author, Yun Xu "Betty" is an integrated marketing communication graduate student at Northwestern University. She is particularly interested in turning data into actionable insight and marketing strategy in the fashion industry, therefore to improving ROI. You may contact the author via twitter: @xuyunbetty and LinkedIn: @Betty Yun Xu