Item Ranking via Virtual Shopping Cart Activity Metrics
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Solution Overview
Problem
Online merchants face challenges in helping customers select items from numerous options, as existing systems lack effective methods to rank items based on customer shopping cart activity, which can indicate interest and desirability.
Innovation Solution
The implementation of an item ranking process that scores items based on virtual shopping cart activity, including factors such as average time in the cart, addition frequency, removal frequency, and checkout process involvement, to provide a ranked listing that reflects customer interest and marketability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If items are listed without ranking, then all items are equally visible, but customers cannot easily identify the most desirable items among many options
Solution Approach 1:
The patent changes the parameter of item presentation from unranked to ranked based on shopping cart activity metrics. By calculating scores based on addition frequency, removal frequency, and time in cart, the system transforms raw activity data into a meaningful ranking parameter that highlights desirable items, resolving the contradiction between equal visibility and easy identification of popular items
Solution Approach 2:
The system implements feedback by using customer shopping cart activity (additions, removals, time spent) to generate rankings that are then displayed to influence future customer behavior. This closed-loop feedback mechanism continuously adapts the item presentation based on actual customer interactions, making it easier to identify desirable items while preserving the information about customer interest
2Productivity
If items are ranked based on shopping cart activity, then desirable items are highlighted, but the system complexity increases due to tracking and scoring mechanisms
Solution Approach 1:
The shopping cart data structure is designed to serve multiple functions: it tracks items for purchase processing and simultaneously collects data for ranking calculations. By making the shopping cart system multi-functional, the patent avoids creating separate complex tracking infrastructure, thus improving sales effectiveness while limiting the increase in system complexity
Solution Approach 2:
The ranking system is designed to automatically calculate scores and generate rankings without requiring manual intervention. The system self-services by continuously monitoring shopping cart activity, computing ranking scores based on predefined metrics, and updating item presentations automatically, thereby improving productivity while keeping operational complexity manageable
3Measurement precision
If multiple shopping cart activity factors are considered, then item ranking accuracy improves, but the calculation complexity increases
Solution Approach 1:
The ranking score is segmented into distinct components based on different shopping cart activities: addition frequency, removal frequency, and time in cart. Each component is calculated separately using simple metrics, then combined to form the overall ranking score. This segmentation approach improves measurement precision by considering multiple factors while managing calculation complexity through modular, independent computations
Data Source
AI summary
Disclosed are various embodiments for ranking items in an electronic commerce system. A subset of a plurality of items is identified in at least one computing device, where the items are sold through an electronic commerce system. The items in the subset are ranked relative to each other based, at least in part, on the virtual shopping cart activity of a plurality of users with respect to the items.