Systems and methods for optimizing wearable item selection in electronic clothing transactions platform

Abstract

Disclosed are methods, systems, and non-transitory computer-readable medium for assigning wearable items in a subscription electronics transactions platform. For example, a method may include: generating a grid based on information regarding historically shipped wearable items, wherein the grid comprises at least a first cell and a second cell; determining an average percentage indicating how many wearable items have been used and an average predictive wearability metric for wearable items indicative of a propensity of a user to use the wearable items per number of wearable items shipped for each cell; generating a mapping configured to convert a predictive wearability metric to a squashed predictive wearability metric; and converting a first predictive wearability metric to a first squashed wearability metric based on the generated mapping.

Description

TECHNICAL FIELD[0001]Various embodiments of the present disclosure generally relate to systems and methods for optimizing wearable item selection in electronic clothing subscription platform, and more particularly, optimizing wearable item selection based on user satisfaction.BACKGROUND[0002]It is a challenge for rental clothing subscription services to optimize the selection and delivery of clothing in a way that maximizes both user satisfaction and business objectives. In particular, it can be difficult to determine optimization objectives of wearable item selection that are aligned with multiple types of business objectives. Some systems and methods for wearable item selection optimize wearable item selection based on users who have had positive and high wearability experiences (e.g., instances in which the users have used the selected wearable items) because wearability prediction for such users to wear high-quality garments may be relatively higher compared to other users. Ther...

AI Technical Summary

Benefits of technology

The patent text describes a system and method for optimizing the selection of wearable items in a subscription electronics platform. The system uses data on historically shipped wearable items to create a grid with cells that include information on the percentage of wearable items that have been used and the predictive likelihood of a user to use a specific wearable item. The system then uses a mapping system to convert the predictive wearability metrics of the wearable items to a squashed form based on the average percentage and predictive wearability metrics for each cell. This allows for a more accurate prediction of user satisfaction with the wearable items. The system can also obtain information about the first pairing of a unique user identifier and a wearable item to better understand user preferences. Overall, the system improves the selection and optimization of wearable items in subscription electronics services.

Problems solved by technology

It is a challenge for rental clothing subscription services to optimize the selection and delivery of clothing in a way that maximizes both user satisfaction and business objectives.

In particular, it can be difficult to determine optimization objectives of wearable item selection that are aligned with multiple types of business objectives.

This may allow relatively satisfied users to remain satisfied, but may similarly cause relatively dissatisfied users to remain relatively dissatisfied.

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