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, Modaes.com, 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".



More on this topic

Clothing: New Investment in Panama Announced

January 2020

The Swedish chain of stores Hennes and Mauritz announced that among its expansion plans is the opening of a sales point in Panama, which would be the first in Central America.

According to an official statement that was released in mid-January, the plan of the company Hennes and Mauritz (H&M) is that its first store in the region will be open to the public by the end of the year.

Brands: Create or Not Mobile Apps?

September 2019

If brands want to take advantage of the 6 hours a day that Central American consumers connect to their cell phones through the creation of apps, it is recommended that they have clear objectives that are agile and quickly updated.

The study "Engagement República 2020", carried out by the social networking company Ilifebelt, reveals interesting data on consumer behavior when they connect to the Internet.

Internet Searches and Consumer Preferences

June 2019

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.

Every time consumers enter the Internet and conduct searches, their transactional historical information, including geographic location data, customer behavior across digital channels, financial options, tastes and interests, and even their propensity to leave brands, among others, can be collected and leveraged by businesses.

Big Data Improves Tax Collection

May 2018

The predictive model designed with data mining techniques used by the Ministry of Finance in Costa Rica has detected payments to third parties totalling more than $31 million.

By cross matching information from the 132 databases available to the Ministry of Finance, the Tax Intelligence Office is trying to predict which companies are more likely to evade tax payments, depending on their historical behavior measured through transactions, tax returns and other data. By linking together all of the information, they are identifying patterns of behavior similar to those of other companies that have evaded taxes in the past.

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