User Data Modeling for Issue-Specific Outreach Targeting
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Solution Overview
Problem
Organizations face challenges in effectively targeting their outreach efforts to individuals most likely to respond well to advertising and outreach efforts, as existing digital communication data is not utilized efficiently to identify and engage potential consumers or donors.
Innovation Solution
A computer-implemented method and system for enhancing user data by detecting transaction requests in response to issue-specific invitations, generating datasets with issue-specific elements, associating and appending additional datasets to identify correlations and enhance user profiles for targeted outreach.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If organizations spend money on broad advertising segments, then reach is improved, but efficiency deteriorates due to wasted resources on uninterested individuals
Solution Approach 1:
The patent segments the broad population into specific interest groups based on digital communication behavior, transaction requests, and engagement patterns. By dividing the target audience into smaller, issue-specific segments, organizations can direct advertising efforts precisely to individuals likely to respond, thereby maintaining broad reach while improving efficiency.
Solution Approach 2:
The system changes the parameters of target identification by analyzing multiple data dimensions including digital communication patterns, transaction history, and engagement metrics. This multi-parameter approach enables dynamic segmentation that adapts to individual user interests, allowing efficient targeting without sacrificing reach.
2Loss of information
If organizations collect more digital communication data, then user profiling capability is improved, but data utility deteriorates due to inability to effectively target individuals
Solution Approach 1:
The system implements feedback loops where digital communication data is continuously analyzed, user responses to outreach efforts are tracked, and targeting strategies are refined based on measured outcomes. This feedback mechanism ensures that collected data translates into actionable insights, improving both profiling capability and targeting effectiveness.
Solution Approach 2:
The patent introduces an intermediary analysis layer that processes raw digital communication data and transforms it into actionable user profiles and targeting criteria. This intermediary system bridges the gap between data collection and effective targeting by applying analytical algorithms that identify patterns and predict user interests.
3Productivity
If time and resources are increased for contacting individuals, then outreach effectiveness is improved, but resource efficiency deteriorates due to limited resources relative to large audience size
Solution Approach 1:
The system performs preliminary actions by pre-segmenting audiences and pre-analyzing user profiles before outreach campaigns begin. By preparing targeted lists and predicting user interests in advance, organizations can deploy resources more efficiently during actual outreach, improving effectiveness without proportionally increasing time and resource investment.
Data Source
AI summary
A computer-implemented method for enhancing and utilizing user data derived from digital interactions includes receiving user submission data comprising records generated by input into a client side application interface by a first user on a first computing device and transmitted from the first computing device to the aggregation point via at least one of a data transmission service and a data transmission provider. The method includes generating a first dataset associated with the first user, generating a data model based on data in the first dataset and one or more correlations based on attributes in the first dataset, and generating a modeled dataset based on the data model.