Data Science: the impact of Big Data on the fashion industry

Big Data

During the last decade, the concept of Big Data has become increasingly popular. In the fashion industry, data analysis has begun playing a key role in trend forecasting and understanding consumer behaviour, preferences, and emotions. Against this background, we have to ask ourselves about the competitive advantage offered by data science and act accordingly.

Data analytics is not new to the industry: fashion companies and retailers have always paid attention to sales information. The real revolution lies in the way data is now becoming available, such as Internet-based information and data from social media sites or mobile apps. The amount of data available from these non-sales-related sources is absolutely huge and can provide retailers with valuable information for trend prediction and the tracking of customer behaviour.

The competitive advantage of online sales platforms compared to traditional companies lies in the large volume of business information they can monitor and examine. In this scenario, data science is changing the dynamics of the industry as fashion turns from an “offer-based demand” to a “demand-based offer” model.

Thanks to predictive data analysis, fashion manufacturers are able to regulate their production and achieve the main goal of every business company: satisfying the consumer’s desires as soon as possible almost immediately.

Moreover, shifting from an “offer-based demand” to a “demand-based offer” perspective, retailers are able to reduce the volumes of initial purchases, scaling back their inventories and embracing a season cycle based on real sales.

Data science help manufacturers and retailers keep up with the latest trends and customer demands. By collecting a large volume of data and turning them into information, every step of the value chain is able to quickly make important decisions on the basis of the most popular styles, colors, fabrics, and sizes.

More and more online sales platforms are offering their customers the opportunity to create a “style profile” by answering simple questions about their body type, measurements, favorite colors and styles. The algorithm uses these data to choose the items that will be recommended to the user, and it will use the data about returned items to automatically recalibrate its advices and decrease return rates subsequently.

At the same time, manufacturers can use Big Data to quickly and easily identify their best sellers in order to adjust their production activities and provide their designers with useful insight.

The fashion industry is based on a delicate balance of different factors and problems such as changing trends, customers’ budget, and the absence of unified sizes – and it is just beginning to use data science as a tool to solve these problems.

Today, companies are expected to ride the wave in the best possible way in order to avoid the tragic scenario depicted by Geoffrey Moore: “Without Big Data, you are blind and deaf and in the middle of a freeway”.