Application of Big Data in the fashion industry


by Aishwarya Banik


November 26, 2021

The fashion industry is experiencing changes in the way designers produce and promote their items due to the emergence of big data. Fashion appeals to virtually everyone, regardless of status or culture, but different buyers want different clothing products. Big data provides vital information to designers, enabling them to create things that will sell well. The fashion industry relies on a delicate balance between several aspects and challenges, such as changing trends, customer budgets and the lack of standardized sizes – and big data analytics has already started to address these issues.

Analyze trends

Trends in the fashion industry are changing at a faster rate than you can alter your outfits. What was popular yesterday could be obsolete in the next two weeks? Fashion companies can easily monitor market trends using big data analysis techniques like social media sentiment analysis and know their target audience. Data analysis can be used to examine the influence of various seasonal trends on purchasing behavior.

Fashion show in retail stores

Retail shoppers are rarely exposed to the models worn by models on fashion shows. These elements contribute to the brand’s public awareness, although they are almost always tweaked before reaching retail stores. Designers can use big data to determine which of their items and outfits would be the most popular once they hit retail outlets around the world. Applicants should be prepared to work in the fashion industry not only in terms of fashion design, but also in terms of business subjects.

Cost calculation

The price of clothes after the fashion show is over and the sets are off the catwalk is also a big part of the formula for success. Each garment is assigned a price that will be displayed in stores, and big data makes it easy to calculate an average price that will increase sales. To sell their products to targeted customers, designers must be prepared to accept this price.

Audience targeting

Retailers are not new to collecting digital impressions from customer groups. Age, gender, ethnicity, region and other criteria can be used to categorize customers. It is a popular marketing strategy with several advantages. Big data goes even further. It can be used to study customer behavior across a variety of factors. Social media sentiment can be used to monitor consumer engagement, buying times can be used to estimate when people are most likely to buy, and touchpoints can be analyzed to see how customers are doing. connect with a business.

Personalized marketing campaigns

Personalization is crucial in marketing campaigns, especially in the fashion industry, because every marketer knows that using personalized texts, product promotions and special offers to target certain categories of customers results in improvement. sales and better consumer engagement. Big Data is capable of capturing much more than just basic customer data. A variety of consumer behaviors can be collected and assessed, providing insight not only into who a customer is, but also what they are.

Popularity of taste and design

This level of detail in customer behavior will lead to a more scientific approach to forecasting – and to profiting from fashion trends. Big data will allow the fashion industry to examine popularity patterns at a granular level, allowing them to understand who is buying what and why. Labels can focus their efforts on promising articles once they have this information. Where once engaged fashionistas were eagerly awaiting the next edition of Vogue or the fashion week show for the latest trends, they are now turning to social media.

Streamlined product lifecycle

Manufacturers and developers can simplify the lifecycle of their products at virtually every level with access to such a plethora of customer data, thereby eliminating unnecessary inventory. Customers’ reactions to samples and ideas can be measured, and then the product can be adjusted accordingly. Consumers thus participate in the design process. A high level of customer acceptance almost ensures the success of a product. Big data has a direct role in the socialization of design. In the past, companies kept all design work in-house.

Favorite color trends

The fashion industry is influenced by global trends, but retailers also need to know what colors their consumers want. Big data plays a role here, revealing the most popular color trends among customers and allowing the design to be easily tweaked and tweaked to meet demand. Big data indicates the most preferred color palette, allowing the company to choose the most popular spectrum. Big Data is simply about analyzing the colors provided by different companies and leading the design and manufacturing team to keep the customer’s desires in mind.

New product categories

Every business has to create new items that will be profitable in the future. Big data can help with this by identifying which assets should be explored and which should be avoided. Many fashion companies have to follow a narrow line when considering whether or not to create a new product that will make or destroy them. The ability to rely on the mass appeal of consumers can make or kill a business. When it comes to selecting a product that can help you, big data can be very helpful.

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