Cognitive tools spark innovative designs faster
Top designer JASONGRECH is transforming his creative process with a first-of-a-kind cognitive solution designed to distill hundreds of thousands of fashion images and social media conversations into usable inspirations for upcoming collections. The solution collects images from Instagram, Pinterest, Twitter and fashion archives, using visual recognition technology to identify and categorize key elements: faces, the human form, colors, patterns, fabrics and more. By analyzing the occurrence of these elements over time—and how the images are shared and discussed—the system can predict upcoming trends in color and style. It can also pull in images from outside the fashion world, such as architecture, and find similarities in lines, curves and textures to serve as inspiration for clothing. Plus, the solution analyzes unstructured, natural language social media content to understand which styles generate the most buzz among industry influencers, including the hemlines, necklines, dress lengths and more. Parsing comments and metadata such as shares and likes, the solution can also produce insights about the people behind the posts—whether they’re whimsical or serious, brash or reserved, earnest or sarcastic—which makes it possible to segment and understand the target audience.
Information-gathering phase accelerated
The first-of-a-kind cognitive solution accelerates the information-gathering phase of the creative process by 600 percent, from 28 to 4 days. With the insights and predictions from the cognitive tools, JASONGRECH can define the creative direction of a collection with greater confidence, using data to support decisions about color palette and other design elements. And the solution allows the designer to finish storyboards faster and focus on showstopping details such as beadwork, custom dyes and accessories.
JASONGRECH is approaching the creative process in a completely new way with a first-of-a-kind cognitive solution, gaining a competitive edge with the ability to predict where the fashion industry will go next rather than reacting to the work of other designers. By analyzing images and social media buzz for trends and inspirations, the designer can move with greater confidence and speed, with more time to spend on showstopping elements such as intricate embroidery and beading that strengthen his reputation as a couture fashion icon.
In the world of high fashion, it’s not unusual to spend a full year putting together a collection, with weeks or months of the creative process devoted to finding inspiration and building storyboards. JASONGRECH’s small team worked for months, manually gathering images and doing research to inform the creative direction. Now, the team can get the same insights from a cognitive computing engine that can understand and analyze images and social media content in a matter of hours or days, providing recommendations and predictions about fashion trends in upcoming seasons.
The cognitive solution collected 10 years of images and unstructured text from fashion archives and social media sources, including Instagram, Pinterest and Twitter. The data includes hundreds of thousands of images of runway looks, natural language conversations about fashion, and social media platforms’ metadata, such as numbers of likes and shares.