Adaptive Ad Delivery for App Usage and Revenue
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current monetization models for application programs, such as sales-based models and in-application advertisements, fail to maximize revenue opportunities as users resist upfront costs and are deterred by intrusive advertisements, leading to reduced application usage and lower ratings.
Innovation Solution
A system that generates user profile information based on interaction with application programs to customize and control advertisements, determining user interests and behavior, allowing for targeted and timed ad display, thereby enhancing user experience and increasing application usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If in-application advertisements are provided in free application programs, then developers can generate revenue, but user experience is detracted and frequency/duration of use decreases
Solution Approach 1:
The patent implements dynamic advertisement delivery by measuring user behavior metrics (session duration, interaction frequency, completion rates) and adjusting ad frequency and timing in real-time. The system dynamically adapts the balance between monetization and user experience based on individual user patterns, allowing more ads for engaged users while protecting experience for less engaged users.
Solution Approach 2:
The system changes key parameters including ad frequency, ad timing, and ad placement based on measured user behavior. By modifying these parameters responsively, the system optimizes the trade-off between revenue generation and maintaining positive user experience, delivering personalized ad strategies that adapt to each user's interaction patterns.
2Ease of operation
If users are provided with free application programs with advertisements, then users can access applications without upfront cost, but application ratings decrease
Solution Approach 1:
The patent implements a feedback loop where user behavior is continuously measured and fed back into the advertisement delivery system. This feedback mechanism allows the system to adjust ad strategies based on actual user responses, preventing rating degradation by adapting to user preferences and minimizing intrusive ad experiences that would lower ratings.
3Productivity
If users are charged for application programs, then developers can maximize revenue, but users resist due to upfront cost and financial information requirements
Solution Approach 1:
The patent segments the user base into different cohorts based on measured behavior patterns and monetizes them differently. High-value users who demonstrate strong engagement receive more aggressive ad delivery, while new or less engaged users receive reduced ad frequency, allowing the system to capture value from different user segments without alienating them with excessive advertising.
Data Source
AI summary
User profile information is generated which characterizes measured user interaction with an application program that is encapsulated by the computer readable program code and processed by the processor. Operation of an advertisement displayed while the application program is being processed is controlled based on the user profile information.