True Fit’s Fashion Genome is the industry’s largest data collective of valuable insights, trends, and data that enables retailers to power personally relevant shopping journeys for every shopper. In order to compete with the constantly evolving industry and modern-day customer, our Data Science team consistently explores the importance of customer’s expressed preference and the details that make our collective stronger and the experience better.
Based on findings from True Fit’s Data Science team, feedback from retailers, and trends across the industry as a whole— we have created the first Consumer Behaviors Report in a series called “The Art of The Algorithm.” These reports will uncover the insights, findings and data that are derived from a single consumer behavior.
In the first edition of these reports, our team sought to answer the question: Does age drive consumer behaviors?
Many recommender systems offer “personal” shopping experiences by collecting general demographic data from consumers— age, height, weight. In developing algorithms to power consumer recommendations around size, fit and style, the Data Science team at True Fit recognized inconsistencies with patterns that relate style preferences to age.
Understand if a consumer's age is the primary driver of personal shopping preferences, or is it just one of several factors that influences preference instead?
Explore the importance of a consumer's expressed preference when developing personalization strategies.
Learn how True Fit's recommendations utilize consumers’ personal preferences to offer them the clothes and shoes they will love and keep.
SHARE THIS ON: