Big Data, Fashion and Internet

Through geolocation tools and techniques for analyzing large volumes of information, the fashion firm H&M studied what users in a specific city were looking for on the Internet, in order to design a collection tailored to their preferences.

Friday, August 2, 2019

Although some think that the tools and techniques of Big Data, Artificial Intelligence and Machine Learning are only for some industries, the bet recently made by the famous fashion house H&M refutes those who use that argument, confirming that there are multiple markets and industries that are increasingly taking advantage of the great value that these tools have in optimizing processes and generating more and better business.

An article published by the economic information portal of the fashion business,, analyzed what H&M has done.

"... The Swedish chain has chosen Berlin to launch a clothing collection based on big data. From data collected from 'cookies', which follow the pattern of consumers when they surf the Internet, the Swedish giant has arranged the tastes and trends that the consumer seeks, to launch a clothing line according to that demand."

You may be interested in: "Big Data for Business Optimization

The main objective of the Swedish group has been to test production on demand. In this way, the company saves unnecessary transport costs as well as other storage and overproduction costs. H&M is also giving a nod to sustainability because, according to the company, producing on demand "is good for the environment".
In particular, H&M has handled a number of very specific data, such as silhouettes and preferred colors, as well as information on materials and prints. In this way, the collection, produced in Europe, has consisted exclusively of overalls, gabardines, skirts, tops and even cycling tracksuits and trousers. The collection premiered on 16 May and is only available in the eight stores that the Swedish chain has in Berlin

Read the full article "H&M takes advantage of 'big data': launches a collection according to what is searched on the Internet in each city".

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The information deriving from the searches made by people in a social network or a website can be analyzed through Big Data techniques, allowing the identification of consumer habits and their potential for growth.

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