Abstract: Embodiments of the invention may provide a personalized fit prediction to a particular consumer about a particular product. Personalization of the fit prediction may be accomplished by processing various types of data, including data about consumers, products, and previous purchases by consumers. For example, this data may be used to generate a model (e.g., set of rules), which can then be applied to predict whether and/or how well a particular product will suit a particular consumer.

Abstract: Embodiments of the invention may provide a personalized fit prediction to a particular consumer about a particular product. Personalization of the fit prediction may be accomplished by processing various types of data, including data about consumers, products, and previous purchases by consumers. For example, this data may be used to generate a model (e.g., set of rules), which can then be applied to predict whether and/or how well a particular product will suit a particular consumer.

Abstract: Some embodiments of the invention enable a buyer to shop for and purchase items for a recipient with confidence. For example, some embodiments of the invention enable a recipient to create a profile that may be accessed to make recommendations to a buyer on items deemed likely to suit the recipient in any of numerous ways (e.g., those deemed likely to fit the recipient, be age-appropriate, reflect the recipient's style, suit the recipient's fit preferences, conform to the recipient's measurements, etc.). In some embodiments, a recipient may indicate that certain, or all, aspects of the profile be kept private, so that the buyer need not know information about the recipient such as his/her body measurements, fit preferences, style preferences, and/or other information to be able to shop confidently for the recipient.

Abstract: Embodiments of the invention may provide a personalized fit prediction to a particular consumer about a particular product. Personalization of the fit prediction may be accomplished by processing various types of data, including data about consumers, products, and previous purchases by consumers. For example, this data may be used to generate a model (e.g., set of rules), which can then be applied to predict whether and/or how well a particular product will suit a particular consumer.