While many dismiss the fashion industry as frivolous, it’s a very big, demanding, and profitable business—projected to create $3.75 trillion in revenues in 2016. Today’s fashion industry has embraced big data analytics in every part of the product lifecycle. In this updated O’Reilly report, you’ll learn how fashion brands and startups alike are using data in shrewd ways that other industries would do well to incorporate.
By interviewing experts throughout the industry, Liza Kindred and Julie Steele reveal that fashion companies are finding ways to turn self-expression and identity—two things that are difficult to quantify—into actionable data. You’ll learn that fashion’s success in this endeavor is partly based on a willingness to pursue difficult data techniques, such as visual search and natural language processing.
This report also explores:
- The challenges of using algorithms to predict style preferences
- How fashion companies are using natural language processing
- What startups are doing to capture structured data from photographs
- How companies are digitally tackling the fit of menswear
- The value in using in-store smart fixtures to collect and share data
Liza Kindred is the founder of fashion tech think tank Third Wave Fashion, editor of Third Wave Magazine, the world’s first print magazine dedicated to fashion tech and wearables, and the author of the upcoming O’Reilly book How We Buy Now.
Julie Steele is Director of Communications at Silicon Valley Data Science and coauthor of Beautiful Visualization and Designing Data Visualizations (both O’Reilly).