Notification Timing Based on Shopping Duration and Location Tracking
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Solution Overview
Problem
Current location tracking techniques in merchant areas are imprecise, leading to unnecessary notifications and resource wastage, as they lack awareness of shopping behavior and activity associated with users, often transmitting notifications after transactions are completed.
Innovation Solution
A notification management platform that determines shopping and checkout durations using a combination of location data from user devices and transaction data, allowing for precise location tracking and selective notification transmission based on these durations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If location tracking is performed continuously in merchant areas, then location awareness is improved, but resource consumption increases and notifications become less relevant
Solution Approach 1:
The system performs preliminary actions by detecting user entry into the merchant area and predicting shopping duration before the shopping experience concludes. This allows the system to proactively determine when to transmit notifications based on predicted checkout times, rather than continuously tracking location throughout the entire shopping period.
Solution Approach 2:
The system dynamically adjusts tracking intensity based on user behavior phases. Continuous location monitoring is applied only during critical phases (entry detection, shopping duration monitoring), while reducing or suspending tracking during intermediate periods, thereby optimizing resource consumption while maintaining measurement precision when needed.
2Productivity
If notifications are transmitted frequently to users, then user engagement is improved, but notification relevance deteriorates
Solution Approach 1:
The system uses feedback from transaction data and location information to dynamically determine notification timing. By analyzing shopping durations from previous transactions and real-time location data, the system adjusts when to send notifications, ensuring they are transmitted at optimal moments when users are most likely to be receptive, thereby maintaining both frequency and relevance.
Solution Approach 2:
The system performs preliminary analysis of shopping patterns and predicts checkout times before users actually leave. This allows notifications to be scheduled in advance at the most relevant moments, rather than being sent uniformly or reactively, thus improving both the frequency and relevance of notifications.
3Device complexity
If shopping duration is determined using only entry and exit times, then measurement simplicity is improved, but measurement precision deteriorates
Solution Approach 1:
The system segments the shopping experience into distinct phases: entry detection, shopping duration monitoring, and checkout prediction. By dividing the overall shopping process into these segments and applying different detection methods to each phase, the system achieves precise shopping duration measurement without requiring complex continuous tracking throughout the entire experience.
Solution Approach 2:
The system merges multiple data sources including location information, transaction data, and shopping behavior patterns to determine shopping duration. This combination of multiple relatively simple data streams creates a precise measurement system that is more accurate than any single method alone, while avoiding the complexity of continuous sophisticated monitoring.
Data Source
AI summary
A device may detect a first entry of a first user device of a first user into a merchant area. The device may monitor a movement of the first user device within the merchant area. The movement may include a transition from a shopping area of the merchant area to a checkout area of the merchant area. The device may detect a transaction between the first user and the merchant. The device may determine a shopping duration for the first user and a checkout duration for the first user. The device may detect a second entry of a second user device of a second user into the merchant area. The device may perform one or more actions based on detecting the second entry. The one or more actions may be performed selectively based on the shopping duration or the checkout duration of the first user.