Embedded Content Cards With On-Demand Data Set Generation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing content card systems generate large numbers of data sets in advance, requiring significant processing resources and storage capacity, with a significant portion of these data sets going unused due to infrequent user engagement, leading to inefficiency and waste.
Innovation Solution
Implement a dynamic data set generation approach where data sets are generated on demand based on user interactions and triggers, reducing unnecessary processing and storage by only creating data sets when needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data sets are generated in advance for all users, then personalized content delivery is enabled, but processing resources and storage capacity are significantly consumed
Solution Approach 1:
The system performs preliminary identification of users who are likely to engage with content cards before generating data sets for them. This selective preliminary action ensures that data sets are prepared in advance only for relevant users, enabling personalized content delivery while avoiding the generation of excessive data sets for all users.
Solution Approach 2:
Instead of generating data sets for all users (excessive action), the system generates data sets only for a subset of users who are identified as likely to engage with the content cards (partial action). This reduces the quantity of data sets while maintaining the capability for personalized content delivery to those who need it.
2Speed
If data sets are generated in advance, then content can be delivered quickly to users, but a significant portion of data sets remains unused due to infrequent user engagement
Solution Approach 1:
The system performs preliminary identification and data set generation only for users likely to engage with content cards, rather than waiting for user requests. This ensures that when these users do access the application, content is delivered quickly, while avoiding the waste of generating and storing data sets for users who would not use them.
Solution Approach 2:
The system uses user engagement patterns and triggers to automatically determine when and for whom to generate data sets, eliminating the need for continuous generation of data sets for all users. This self-service approach optimizes resource usage by generating data sets only when and where they are likely to be used.
3Loss of energy
If data sets are generated on demand, then resource usage is optimized, but processing time may increase when users first access the application
Solution Approach 1:
The system performs preliminary identification of likely engaging users and generates their data sets in advance, before they access the application. This preliminary action eliminates the need for time-consuming data set generation at the moment of user access, thus reducing the perceived processing time while maintaining resource efficiency.
Solution Approach 2:
The system uses periodic triggers based on user engagement patterns to determine when to generate data sets. This periodic approach balances resource efficiency with timely content delivery, generating data sets at optimal intervals rather than continuously or only on demand.
Data Source
AI summary
Systems and methods for presenting information, messages, sound recordings and video to a user via content cards embedded in a software application includes generating content card data sets at the time that the software application is started and run. The software application requests content card data sets upon startup, and a data service then generates content card data sets at that time. The software application uses the newly created content card data sets to display information, messages, images, sound recordings and video to a user within the embedded contact cards.