The fashion industry is a competing market - it is a place where talented people showcase their talent to be on the top or sustain their brand. Thus, to be ahead of everyone- you need to perceive trends, changes, and many other factors. It is only possible with Data Science- as it provides data that helps you predict and understand the situation of the current market.
Hence, it proved that after embracing Data Science in the fashion industry, an emerging witness by the industry. Data Analytics plays a pivotal role in forecasting trends and understanding consumer behaviors, choices, and sentiments. Big Data helps to obtain advantages of data towards the fashion industry. Data Science in the fashion industry will soon be mandatory in the upcoming years because of benefits.
Over the decade, the latest technology and Data Science have changed the game of the fashion industry. No matter what it is- physical retail store, enormous brands, e-commerce website, or any other fashion chain- everyone has been influenced by Data Science, Big Data, and Big Data Analytics
. It has helped them to meet the expectations of the customers to the end and with the facility.
So far, we have seen what Data Science has done to the fashion industry- now, let us see how they have executed it in the fashion industry.
Accurate Prediction for Trends
Well, this has to be the foremost reason for Data Science enhancing the fashion industry. As we mentioned earlier, using Data Science helps the fashion industry to forecast future trends. Whether there will be changes or not can be predicted by using Data Science. But the question is how?
Data Science helps businesses gather all information regarding people's purchases, preferences, influencing, and every factor. It has been observed by the analysts and they are classified into different parts to know about the trends and challenges. The changing preferences and tastes of the target audience can be known with the data provided by Big Data.
The forecast data helps designers to know about their clothes, fashion, brand. It supports them in curating products according to the customer's choice and needs. Amidst the increased use of social media, customers share what they purchase, how they like and dislike, where they want to see changes, suggestions, and more. The necessary change in products and offering is unavoidable, and to grow the brand need to acquire the development.
The projection can be done on the basis of style, age group, taste, usage, and others. The response from the customer also matters as it helps to develop changes. The survey can only be conducted with the help of Data Science.
Personalized in Fashion
Earlier, personalization was the only privilege to the urban higher class- now, thanks to technology and data, everyone can access personalization in fashion. There is more future fashion in personalization and significance. Customers do not want to go through every piece of clothing to find their own- instead, they want to be shown the clothes according to their relevance and choice. Data Science and Big Data come to the picture- as they provide data of the customer choice and preference. By using data, fashion businesses are clear about what their customers want and ask.
The tool helps them to categorize customers and display the fashion product as per their needs. The scale is extensive- but Big Data manages everything and collects a large amount of data. By adopting Data Science- brands can see the process and understand their target audience much better. According to research from Forrester,
only 29% of people from the industry are able to utilize analytics to make data-driven decisions.
Not just trend is limited to fashion but is limited to products also. For instance, cotton clothes were in fashion for quite a few times but with variable changes, today people prefer satin.
helps to know about the current trending products and even predict which type of product people may favor in the future. Large brands call predictive analysis actionable product intelligence. As everything about the product can be discovered through analytics and Data Science.
Even the smallest things like design detail, product fabric, colors, price, short or large, and others can be discovered with this method. Even the tools help stay engaged with the target audience, celebrities, influencers, and many more relevant people. What might be successful and what might fail in the fashion industry can be known with Data Science.
Lessening Wastage and Handling Inventory
In the case of online shopping, customers receive the product but do not like it- so they return it to the website or mobile app whenever they shop from. In a similar case, if the customer is unhappy with the product in-retailer store they return it- eventually this also leads to waste for the business owner and brings an additional cost.
So, to avoid such a situation, Data Science comes to the rescue. They help in knowing about customer choice and tastes- so, you would show what customer wants to be shown. Data Science makes it easier for both users and owners in the fashion industry. It plays a major role in forecasting the shopping behavior of customers.
Imagine a brand producing a certain product on a large scale and later finds out it turns out to be a big failure in the fashion industry. Here, Data Science helps to forecast the demand for a certain product and lessen the production of a product that may not attract the demand.
It also helps retailers manage maximum inventory levels. With fashion trends changing now and then, it has become a task for brands to guarantee that the appropriate products are in stock. With the adoption of Data Science
, they can reduce inventory queries and provide products- that are in style.
So that was our take on how and why Data Science is so pivotal in the fashion industry. Moreover, Data Science helps the fashion industry to operate, gain monetary, potential work, latest trends, and many more. Adding Data Science to the fashion industry is a valuable decision.