Rating Service Location-Based Delay Mechanism
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Solution Overview
Problem
Existing systems lack an efficient method to request and manage user ratings for products or services based on location and interaction, with limited options for delaying rating completion.
Innovation Solution
A server computer executes a rating service that detects user device interactions and location, requesting ratings based on predefined constraints such as location or time, allowing users to delay rating completion until specific conditions are met, and tracks travel history for visual display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If rating requests are sent immediately upon user interaction, then rating completion speed is improved, but user burden and annoyance increase
Solution Approach 1:
The system performs preliminary actions by detecting user interactions (such as product scans or store visits) and preparing rating requests in advance, but delays the actual rating prompt until appropriate conditions are met (such as leaving the store or reaching a convenient time), thus resolving the contradiction between speed and user burden
Solution Approach 2:
The system dynamically adjusts when to prompt for ratings based on real-time conditions such as user location, time of day, and interaction context. The rating request timing is not fixed but adapts to user behavior patterns, optimizing both completion speed and user convenience
2Ease of operation
If rating requests are delayed until later times, then user burden is reduced, but rating completion time increases
Solution Approach 1:
The system uses feedback mechanisms to monitor user behavior patterns and interaction history, continuously learning when users are most likely to complete ratings. This feedback loop optimizes the delay timing to balance user convenience with completion efficiency, addressing the trade-off between reduced burden and completion time
3Reliability
If location-based rating requests are implemented, then rating relevance is improved, but system complexity increases
Solution Approach 1:
The system introduces location services and context detection mechanisms as intermediaries between user interactions and rating requests. These intermediaries automatically analyze user context (location, time, interaction type) and determine optimal rating timing, improving relevance while managing complexity through automated decision-making layers
Data Source
AI summary
Concepts and technologies are disclosed herein for obtaining ratings using a rating service. A server computer executing a rating service can detect arrival of a user device at a vendor location. The server computer also can detect an interaction with a product offered at the vendor location by the user device. The server computer can determine that a rating for the product is to be requested, and can request the rating from the user device.