Smart App Rating Prompting via Engagement and Environment
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Solution Overview
Problem
The existing app rating system in online app stores is flawed as it can be skewed by ratings from users who do not actively use the app, and prompting users for reviews can be inconvenient, leading to biased ratings that affect app popularity and revenue.
Innovation Solution
A method and system that monitor environmental factors and user activity to determine an engagement score, prompting users for reviews when they are likely to provide positive feedback, ensuring they are engaged and available, thereby improving app ratings and rankings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If users are prompted for reviews continuously, then the quantity of reviews increases, but user convenience deteriorates and ratings become biased
Solution Approach 1:
The system dynamically changes the parameter of prompt timing based on user engagement metrics and environmental factors. Instead of continuous or fixed-interval prompting, the system adjusts when to prompt users based on their actual usage patterns, device state, and engagement level, thereby increasing review quantity only when appropriate conditions are met.
Solution Approach 2:
The system performs preliminary analysis of user engagement and environmental conditions before prompting for reviews. By pre-evaluating whether the user is engaged and the environment is favorable, the system avoids inconvenient timing and ensures that prompts are presented only when likely to receive positive responses.
2Measurement precision
If the app monitors user activity and environmental factors continuously, then the precision of review timing improves, but the complexity of the system increases
Solution Approach 1:
The system leverages existing mobile device sensors and data collection mechanisms that serve multiple purposes. Environmental sensors (GPS, accelerometer, microphone) are already used for various app functions, and the same data is reused for determining optimal review timing, avoiding the need for separate dedicated monitoring systems.
Solution Approach 2:
The system uses the device's own existing data infrastructure and sensors to self-determine optimal prompt timing without requiring external complex monitoring systems. The mobile device itself provides the engagement data and environmental information needed for precise timing decisions.
3Reliability
If prompts are provided only when engagement is high, then rating quality improves, but the quantity of reviews may decrease
Solution Approach 1:
The system dynamically adjusts the balance between review quantity and quality by continuously monitoring user engagement levels and environmental factors. When engagement is high and conditions are favorable, the system increases prompting frequency to capture quality reviews. When engagement is low or conditions are unfavorable, prompting is reduced or paused, maintaining quality while preventing unnecessary prompts.
Data Source
AI summary
Embodiments of the disclosure provide a method of providing a prompt to a user for reviewing an app. The method includes monitoring, by a mobile device, environmental factors; monitoring, b a mobile device and a server, a user's activity; determining, by the mobile device, a utility of the user using the environmental factors; determining, by the mobile device and the server, an engagement score using the user's activity; when the utility of the user is determined to be high, providing the prompt to the user; and when the utility of the user is determined to be low, determining whether the engagement score is above a score threshold, and providing the prompt to the user when the engagement score is above the score threshold.