Dynamic Interface Positioning via Bid Scores for Mobile Apps
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Solution Overview
Problem
Users often face difficulty accessing recently installed applications or content on a client device due to their placement in the interface, which is determined by the order of installation, leading to decreased interaction likelihood.
Innovation Solution
A system that determines the position of content in a client device's interface based on a bid amount and expected user interaction, using scores calculated from bid amounts and interaction probabilities, to prioritize recently installed applications and increase visibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If content is presented based on installation order, then the interface structure is simple and stable, but recently installed applications become difficult to access and user interaction decreases
Solution Approach 1:
The system pre-determines positions for content items in the interface based on bid amounts and expected interaction metrics before the user actually accesses them. This preliminary positioning ensures that recently installed applications with high bid amounts are automatically placed in optimal positions, eliminating the need for users to navigate through multiple screens to find them.
Solution Approach 2:
The interface positioning system transitions from a static installation-order-based arrangement to a dynamic system that continuously adjusts positions based on real-time factors including bid amounts, expected interaction metrics, and user behavior patterns. This dynamic repositioning allows recently installed applications to automatically appear in prominent positions without manual intervention.
2Adaptability or versatility
If more applications are installed on the device, then the device functionality increases, but navigation time to access specific applications increases
Solution Approach 1:
Different regions or positions in the interface are assigned different qualities or priorities based on expected interaction metrics. Recently installed applications with high interaction potential are placed in premium positions with higher visibility and accessibility, while less important content is placed in secondary positions. This local differentiation allows the interface to optimize for specific content items without requiring complete reorganization.
Solution Approach 2:
The system changes the positioning parameter from a fixed installation-order metric to a dynamic metric that incorporates bid amounts, expected interaction probabilities, and user behavior patterns. This parameter transformation allows the interface to automatically adapt to new applications and content, ensuring that important recently installed applications are quickly accessible regardless of the total number of applications on the device.
3Productivity
If content positioning is based on installation order, then the system is simple to implement, but user interaction with recently installed content decreases
Solution Approach 1:
The system incorporates feedback loops that continuously monitor user interaction with content at different positions in the interface. This feedback information, combined with bid amounts and expected interaction metrics, is used to refine and adjust positioning decisions. The system learns from actual user behavior patterns and adapts positioning strategies accordingly, improving interaction rates for recently installed applications over time.
Solution Approach 2:
Rather than waiting for user behavior patterns to emerge naturally, the system performs preliminary positioning of recently installed applications based on predicted interaction metrics and bid amounts. This proactive positioning ensures that important content is immediately visible and accessible upon installation, maximizing initial user engagement while the system continues to learn and refine positioning based on actual usage patterns.
Data Source
AI summary
A client device or an online system determines a position in an interface presented by a client device for presenting content associated with an application installed on the client device based in part on a bid amount associated with the application. Scores are determined for the application and other applications installed on the client device based on an expected amount of user interaction with each application and bid amounts associated with one or more of the applications. Based on a score associated with an application, a position in the interface for presenting content associated with the application is determined. If the determined position satisfies a position specified by the bid amount and content associated with the application is presented in the determined position for at least a threshold amount of time, an online system charges a third party system associated with the application an amount.