Usage-Based Revenue Targeting for Mobile Apps
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Solution Overview
Problem
Existing monetization models for mobile applications, such as sales-based and advertisement-based models, have been ineffective in generating revenue due to user resistance to paying for applications and annoyance with advertisements, respectively.
Innovation Solution
A mobile application usage-based revenue targeting system that profiles applications, tracks user interactions, scores user engagement, and groups users into analytics groups for targeted advertising, facilitating the transmission of user data to advertising campaigns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sales-based monetization model is employed, then revenue can be generated from application purchases, but users resist providing financial information and prefer free applications
Solution Approach 1:
The patent introduces a third-party payment processing intermediary that handles financial information securely, separating the payment function from the application itself. This mediator reduces user resistance by providing trusted financial handling and simplifying the payment process, allowing revenue generation without direct user confrontation with payment barriers.
Solution Approach 2:
The patent transforms the monetization parameter from direct application purchase to in-app purchase events. By changing the timing and context of the transaction parameter, the system generates revenue through optional in-app purchases rather than requiring upfront payment, thereby reducing initial user resistance while maintaining revenue potential.
2Productivity
If advertisement-based monetization model is employed, then revenue can be generated from advertisers, but users find advertisements annoying and detracted from application engagement
Solution Approach 1:
The patent applies local quality by delivering customized advertisements tailored to specific user profiles, application contexts, and engagement levels. Instead of uniform advertisements, the system provides locally optimized ad content that is relevant to each user's interests and behavior, reducing annoyance while maintaining revenue generation effectiveness.
Solution Approach 2:
The patent implements dynamic advertisement delivery that adjusts ad frequency, timing, and content based on real-time user engagement metrics and application state. This dynamic approach allows the system to optimize revenue generation while minimizing user annoyance by adapting advertisements to current user context and preferences.
3Productivity
If traditional monetization models are used, then simple revenue streams are maintained, but revenue opportunities are insufficient and user engagement is compromised
Solution Approach 1:
The patent implements a universal monetization framework that integrates multiple revenue streams including in-app purchases, advertisements, and subscription models within a single system. This multi-functional approach allows the application to adapt to different user preferences and market conditions, increasing overall revenue opportunities while maintaining flexibility in monetization strategies.
Solution Approach 2:
The patent performs preliminary user profiling and engagement analysis before implementing monetization strategies. By pre-analyzing user behavior patterns and preferences, the system can optimize revenue generation opportunities in advance while tailoring approaches to maximize user engagement, thereby increasing both revenue potential and model adaptability.
Data Source
AI summary
Disclosed is a method that includes: profiling a set of mobile applications according to revenue-related parameters; tracking a user's interaction with a mobile application; scoring the user's interaction levels, and based on the score, grouping users into mobile analytics groups associated with the targeting profiles; facilitating the transmission of user information, user interaction data, and specific mobile analytics groups to advertising campaigns. The method may be executed on a digital device. A related system is disclosed.