Wednesday, April 19, 2017

Fashion & Big Data





Big data can explain multiple components in the fashion industry. The article states how “Big data explains when customers make their purchases, how large their purchases are and how many items are sold.” This data can help companies and designers decide which items are absolutely necessary to sell in their line and which ones will do well. Another component big data aids in is pricing within items. Clothing needs to be priced accordingly so that customers will actually buy the items. Items cannot be priced too high because then customers will not make any purchases. Big data is easy to average, and the average price can be placed on garments to make sales easier to complete. Items that are priced for sale to the general population must be reduced greatly after their conversion, and designers may use big data to price their products, and each product may take on a price that is derived from the previous year's data. Big data can also uncover new product categories. Big data shows which products will be successful and which such be avoided. There are several different ways a fashion house can expand its offerings, and the data you collect will help you remain competitive in the fashion industry. Your business must release products that are most likely to sell, but you cannot create any product without first consulting the data you have collected. 
The fashion industry is changing as creative designers use analytics to operate their businesses, and each step in this article will help guide your business. Selectively use your data to create and convert product lines your customers are sure to buy in the future. Data can also help predict the future, Analysis of data over time can help designers and retailers predict upcoming trends. It is important for designers to have reasonably accurate forecasts of pending trends so that they do not design for a trend that does not come to fruition. Production paired with insightful business analytics, enables successful designers to appear prescient with their new lines. They can even foresee how desirable certain pieces will be. Gaining data helps to define customer interaction with various different brands and helps retailers create better pricing models, markdown schedules, inventory planning, and seasonal availability. Data and the fashion industry are strongly correlated and data contributes to consumers buying behavior and patterns. Through the analyzation of this data designers and retailers can make more sales and create better revenue. 
   


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