Campaign Feedback Data Segmentation for Storage Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional approaches to processing feedback data from message campaigns are inefficient, leading to less relevant and effective campaigns, as they fail to utilize the collected data effectively, resulting in storage issues and limited query flexibility.
Innovation Solution
A system and method that involves storing and analyzing feedback data in a remote storage system, allowing for arbitrary queries without local storage overload, by transmitting raw data and using a distributed client-server system to manage user profiles and campaign feedback, enabling more flexible and effective campaign analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If feedback data is stored locally, then data availability for analysis is improved, but storage space requirements increase
Solution Approach 1:
The patent segments the storage system into local storage components (for recently collected raw feedback data) and remote storage components (for historical and archived data). This segmentation allows the system to maintain data availability locally while offloading long-term storage to remote systems, thereby resolving the contradiction between data availability and storage space requirements.
Solution Approach 2:
The patent introduces a temporal dimension to data storage by implementing different retention policies for different time periods. Recently collected data is stored locally for immediate analysis, while historical data is archived remotely. This dimensional approach to storage management allows the system to optimize both data availability and storage space utilization.
2Volume of stationary object
If data is pre-aggregated, then storage requirements are reduced, but query flexibility is limited
Solution Approach 1:
The patent implements a dynamic data management system that can adapt the level of data aggregation based on query requirements. The system maintains raw data in local storage for flexible querying while using pre-aggregated data in remote storage for routine analyses. This dynamic approach allows the system to optimize storage space while maintaining query flexibility when needed.
Solution Approach 2:
The patent introduces an intermediary data layer that sits between raw feedback data and aggregated statistics. This intermediary layer allows the system to generate aggregated views for storage efficiency while preserving the ability to drill down to raw data for flexible querying, thus resolving the contradiction between storage reduction and query flexibility.
3Volume of stationary object
If raw feedback data is transmitted to remote storage, then local storage needs are reduced, but data processing time increases
Solution Approach 1:
The patent implements preliminary data processing and validation at the local system before transmitting data to remote storage. By performing initial data cleaning, formatting, and validation locally, the system reduces the amount of data that needs to be transmitted and processed remotely, thereby reducing both local storage requirements and remote processing time.
Solution Approach 2:
The patent implements continuous data transmission and processing pipelines that maintain steady data flow between local and remote systems. By establishing continuous data synchronization mechanisms, the system minimizes batch processing delays and ensures that data is progressively transferred and processed, reducing overall processing time while maintaining reduced local storage needs.
Data Source
AI summary
A server system comprising one or more processors and memory initiates delivery of a respective message campaign that includes one or more messages addressed to a plurality of users. The server system receives, from the plurality of users, campaign-feedback data indicative of user interaction. The campaign-feedback data includes information that enables generation of campaign reports including quantitative information about the message campaigns. After receiving the campaign-feedback data, the server system transmits, to one or more remote storage systems, campaign-tracking data that is based on the campaign-feedback data and then receives, from a requestor, a first request for analysis of the campaign-feedback information. In response to receiving the first request for analysis of the campaign-feedback information, the server system obtains a campaign report generated using the campaign-tracking data from the one or more remote storage systems; and provides the campaign report to the requestor.