How Is Data Science Affecting Fashion And Beauty Market?

The retail sector, since time immemorial, has been the slowest to adopt the new technological advances. Right after the Amazon effect, which almost pushed the retail sector into the corner, the sector started showing attention to the technical revolution. In reality, big data analytics and data science play a major role in pinpointing the changes, shifts, and trends in the fashion industry. A vast amount of data sets reveal patterns, associations which in turn help trendsetters to pave a new way for the fashion industry.

Both structured and unstructured data have the ability to provide deep insights which will form a definition of the present and upcoming trends in the fashion and beauty market. Accumulation of Big Data will take one to the future of the fashion industry. Traditionally, brands and fashion houses keep necessary information like inventory details, sales records etc. However, the working is restricted in a siloed form of record keeping. Vital details like pricing trends, competitive analysis, and other insights have been missing to complete the entire puzzle.

Fashion in the Digital Age

In the fashion and beauty industry, each and every product is under scrutiny. From fabric to sizes and colors, everything is analyzed. For the creative and analytical mind, this data provides an eclectic opportunity- gaining deep insights into the trend, how to stay focused before the trend of forgotten. The explosion of social media is breathing new life into the industry where people like, share, tweet and pin all sorts of fashion ideas together. The data hidden here helps the industry pinpoint what the customers and prospective customers are talking about. A fashion rental service collects all the data about styles its customer prefer. This data helps the designers to create items which are loved by the customer, is in trend and affordable. Right from the moment when a customer signs up for their services, the backend system is already at work by analyzing their choices and suggesting items accordingly.

Another notable fashion-forward retailer is using data science to predict styles that customers might like- despite the clothes not being designed at all at that point in time. The AI algorithm goes through the inventory and brings forth a list of suggestions based on the categories. The system then goes to the other clothing options to create different data-built designs. This only a small example of what data science can do for the fashion industry.

The fashion industry is obviously under constant risk because of new product introductions. In today’s digital-driven world, companies are using predictive analytics termed as ‘actionable product intelligence’. Globally known brands like Ralph Lauren use this kind of predictive intelligence to discover how certain changes in color, fabric, design, and price affects consumer’s response to a product. Data can also help understand a costumer’s need and their shopping behavior. Data science is also used to predict a product’s shelf time. This helps the retailers and manufacturers to have an estimate of the production and dispatch it within a given market.

Data influences a lot of decisions related to the manufacturing of products and helps industry leaders and customers to better understand each other. Data science provides an opportunity to engage the audience in a fashion-centric crowd using effective content. Big brands use people’s comment and turn them into an interactive session. This constant engagement becomes home to large data which in turn can be used innovate new ideas and concepts.

Leaps in artificial intelligence, machine learning, and other data science sectors show no sign of slowing down. It now presents an exciting time to make an entrance into the world of data science.