Fashion retailers need to keep up with the latest trends and client demand. Customers want the latest designs from catwalk in stores the instant they appear – retailers have to therefore meet the demands of “fast fashion”.
They are increasingly turning to data analytics to integrate the “fast fashion” concept or to just keep up with the latest trends. Data analytics isn’t new to the industry. It used to only be spreadsheets and analyzing sales information.

New sources of data are now available. Mostly unstructured data (data not stored in databases) and information from mobile devices or social media sites (like data from Instagram, tweets from twitter, etc.). The immense challenge with Big Data is its rapid growth. New data, trends and styles becomes available (on the world wide web) instantly. Fashion especially sets a fast pace and changes so quickly. Which can be quite challenging but also an opportunity for new entrants. With the right data and real-time insights you can build and monitor a brand or expand into new markets.

Modern statistical data analytics and machine learning helps to recognize:

  • geographical clusters
  • right pricing for items and when to reduce them
  • relevant styles, colors, fabrics and sizes
  • ensure that stores are well supplied and operate efficiently (season, lead-markets, etc.)

The Goal is to move product and retail based on the true state of market. Combining data with established design models, production and logistics will help a company to gain strategical and operative competitive advantage.