Fashion Analytics?

Modeling for fashion just took on a whole new meaning


The world of fashion is a place of endless creativity, inspiration and lasting impact.

No wonder the industry has been omnipresent and evolving for centuries.

However, when it comes to paradigms of Analytics and Big Data which, as we all know, are becoming more ubiquitous as we speak. The marriage of fashion and advanced analytics engines is still fairly nascent, at early stages, especially compared to other industries which have been leveraging the benefits and insights provided by Analytics, for some time already.

The sheer breadth of variables in the realm of fashion is huge:

Internal data sources, external data sources, sentiment analysis of their brand on social media, gender differences, seasonal trends, price fluctuations, generational differences and preferences/attitudes, style preferences across continents and geographies, traditional versus provocative style.  The data set to be analyzed and to provide insights from is immense.

Another dimension to consider is key analytics capabilities which are: descriptive, predictive and potentially prescriptive.

E.g. how about digging into native cultures of the Americas, Asia and Africa and determine their impact of certain cultural components on, let us say, luxury bags, jewellery and clothing.

Can some of the insights be leveraged by entrepreneurial fashion designers when looking for inspiration and subsequently impact on their respective style, age, gender, geography target audience?

There are some very interesting stories, knowledge and visual inspiration provided by fashion advice purveyors like WGSN or Editd – and many more to follow.

Another cool analytics success story is the one of Reebonz: Singapore based online luxury retailer, which is leveraging the commercial insights provided by one of the leading cloud analytics providers.

There are many components I have missed, please let me know of any others in the comment section below.


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