How Can Data Science Help the Fashion Industry?

By: Retail CIO Outlook | Thursday, January 30, 2020

With the help of analyzing big data, companies were able to stay on top of the game, figuring out the trends.

FREMONT, CA: With the progress of technology, the internet, as well as e-commerce, has turned out to be a good thing, but has several significant casualties when it comes to the fashion industry. The challenges faced in retail are infamous for being one amongst the slowest sectors to adjust and implement the new technological advances.

In the past, notable brands used to work in secrecy and keep their vital information within their companies only. All these formats changed when Amazon came along. The use of an abundance of modern technology, such as machine learning (ML) and artificial intelligence (AI), the retail realm began to highlight the significance of data science.

In the marketplace today, the traditional closed-book method is changed, and the fashion industry has gone more dependent on data science than ever before. Particularly, when it comes to trained data scientists, they can predict whether a new collection is likely to be a hit or not, only by assessing the sales data recorded from the past. Additionally, it helps the companies to make sure that their investments are being spent sensibly.

By leveraging predictive algorithms, visual search, natural language (NL) techniques, and structured photographic data, companies can easily recognize trends much before they get into fashion. Subsequently, they can develop customized designs that can resonate with the target audience. In the present time, many well-known brands are using actionable product intelligence that can determine the possible changes in product fabric, design details, color patterns, and price impacts on a customer’s response.

Besides, the rise of the internet and the mass of data the internet provides are the two significant changes in recent years. The introduction of social media has brought a wealth of information that is available for fashion data scientists to evaluate and benefit from. Irrespective of monitoring post engagement, watching out social media trends, studying hashtags, analyzing the clothing styles of famous vloggers, numerous valuable insights become available for the cloth designers and fashion campaign managers to endure.

Moreover, brands can use the comments to make whatever changes are required before they launch a product, and the whole process is known as sentiment analysis, which converts information into structured, usable data.