Data Science Re-styling Fashion Industry in 2021
Know how data science is re-styling fashion industry with big data and AI
The fashion industry is infused with extreme dynamism. There is stiff competition to take the brand to the top. Many talents are involved in fashion/brand marketing but there is a need to track changes and trends to retain the competitive fervor. This accords central role to data science. Since the last decade it is lending necessary techniques and skills to fashion professionals to understand the prevailing market scenario and make precise predictions to forge ahead. Let’s explore the benefits of data science in fashion industry in 2021.
Without the cutting-edge technologies like big data analytics, machine learning and deep learning algorithms, artificial intelligence (AI)-based applications nothing can move easily now in the fashion industry. It is a highly sophisticated field specializing in forecasting trends and understanding consumer behaviors based on specific choices and sentiments. Be it a physical store or virtual e-commerce websites data science in fashion industry marked by constant demand for designing, merchandising and marketing to identify and fulfill customer needs and preferences.
Main channels through which data science operates in the fashion industry
Precise trend prediction: Such process involves tracing both change and continuity. Data science in fashion industry provides segmental divisions of consumer choices, purchases and so forth. It has the technological and computational competence with big data to detect any kind of changing preferences. The circulation of the likes, dislikes, suggestions and aspirations of the consumers in the social media enables data analysts to create guidelines on new fashion brands and make changes in existing brands.
Personalization: The future of the fashion industry is to a great degree dependent on personalization which is no longer a privilege of the urban upper class. Latest technology and big data have made it possible for almost everyone to be part of it. Customers do not have time to go through vast collection of clothing to choose one of their choice. Most prefer to be shown clothes which cater to their preference and choice. Data science in fashion industry comes to the aid of consumers by supplying the relevant and appropriate data about the lifestyle of targeted customers, and also of localized trends. Big data analyzes vast amount of real-time data to categorize customers into various segments. This helps the fashion industry to customize and present the products according to individual orientations.
Production Modification: It is not just fashion but also the product which are often subject to changes in preferences. Data science here too plays a key role, through what is known as predictive analysis with actionable product intelligence, to inform the industry professionals to know about future customer choices and preferences— be it fabric, colour, price, size or something else— and to know which may succeed and which may fail. This raises the possibility of ‘great customer experience’.
Reducing Wastage and Managing Inventory:Return of products from ‘dissatisfied’ customers poses a major problem. It proves costly by causing waste of resources. Data Science predicts customer behaviours, contextualizing specific choices, preferences. It provides indications of what products are to displayed and publicized and what may not be in demand. Regarding the management of inventory levels by retailers, data science in fashion industry aids by giving clues about optimizing stocks, product assortment, and efficient allocation of products in demand.
No wonder then, there is an increasing awareness among fashion brands and retailers about the importance of data science in the fashion industry as it styles it not just to survive but to move ahead with the times.