Big Data in Fashion

Some time ago, I was managing a company that provided on-site IT solutions and had a number of clients from the fashion and talent management industry; who dealt with everything from design, marketing/sales and distribution of product lines globally. Fashion is an exciting, but volatile and dynamic industry. From misinterpreting the popularity and potential of a trend, to miscalculated inventory/logistics, such challenges have compelled the industry to think of efficiency. Back then (we’re talking almost 10 years ago), the extent of their IT requirements came in the form of networking, email and site hosting – much like many other companies of the same size – however, fast forward a decade and now we’re seeing a huge trend in this industry as well, as it pertains to Big Data and Business Intelligence.

Though the fashion industry is one of the slower adopters of big data, the industry is moving forward. Over the past couple of years the industry has invested in Business Intelligence systems, in-store data capture systems and point-of-sales data capture. Unfortunately, the pace at which the industry is switching to more savvy BI tools is adversely affecting the decision making process.

The fashion industry has always been driven by gut feeling and instinctive development of design, colors, styles, patterns etc. The absence of evidence demands more tangible factors that give reasons for the success or failure of a particular style. Despite the huge role creativity plays in designing a fashion line, profit and business success needs metrics that provide empirical analysis. And this goes beyond focus group sessions for choosing the next season’s line.

Lets discuss Big Data’s potential and where it can play a big role in creating an impact in the fashion industry.
Fashion itself is infamous for being changeable, and is driven more by fads and styles than by statistical data. Big Data can help fashion companies look in depth at each trend ahead of competition. Fashion companies are now able to gather larger amounts of customer insights, with a greater depth and clarity of detail and derive inputs by analyzing much more than historical sales data and focus groups. And these insights can help creative design as well as supply chain and pricing decisions. There are fashion websites today that go beyond sales trends or focus groups. These websites collect and share data not just on what people are buying, but also what they’re wearing. Behavioral data allows fashion companies to correlate purchases with consumer trends.

Lets talk Social: For fashion businesses, in particular, social media has immense marketing potential. By tapping into vast online conversations, savvy companies can get access to how customers put together brands online. Keeping in mind that a Facebook “Like”, or word of mouth shared via social media, is more powerful than any survey or focus group. Big data tools can help you extract vast amounts of data and analyze all conversations about trends, successful designs, preferences and fashion “failures”.

Gallant Analytics gives industry leaders the option to pull significant and valuable information out of all the raw data that is found in all aspects of sales and marketing within an ecosystem. Until now, consumer demand for fashion has been driven by fashion experts and legacy analytics models which are much less sophisticated. Big data is changing the way real-time market consumer preferences are gathered and analyzed. It gives the fashion industry access to individual preferences with far greater detail. I’m interested to see how the industry adopts these new insights and tools and what we will find out about the social trends then.