Audience Retargeting via User Profile Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing content delivery systems are inefficient in targeting users due to simplistic methods that fail to consider various factors beyond initial user interactions, leading to suboptimal presentation of invitational content and low response rates.
Innovation Solution
The system analyzes user data, including contextual, behavioral, and temporal characteristics, to create user profiles, allowing for intelligent retargeting of invitational content by modifying its form, channel, or timing to increase the likelihood of desired user responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If content delivery systems use simplistic targeting methods based on limited user inputs, then the system complexity is reduced, but the effectiveness of content targeting deteriorates
Solution Approach 1:
The system changes multiple parameters simultaneously including user behavior data, contextual information, temporal patterns, and content attributes to create a multi-dimensional targeting approach. This transforms the simplistic single-parameter targeting into a comprehensive multi-parameter analysis system that improves targeting effectiveness without excessive complexity
Solution Approach 2:
The patent introduces user profiles as an intermediary data structure that mediates between raw user inputs and content delivery decisions. These profiles aggregate and structure user behavior, preferences, and contextual data, enabling sophisticated targeting while abstracting the complexity from the content delivery mechanism
2Productivity
If invitational content is presented to users without retargeting, then the content delivery process is simple, but the conversion rate deteriorates
Solution Approach 1:
The system implements feedback loops where user responses to invitational content are tracked and used to refine future content delivery. User behavior data, engagement metrics, and conversion patterns feed back into the user profile system, enabling continuous optimization of retargeting strategies to improve conversion rates
Solution Approach 2:
The system performs preliminary analysis of user profiles and contextual factors before delivering invitational content. By pre-processing user data and identifying optimal targeting opportunities in advance, the system prepares retargeting strategies that increase conversion likelihood while managing complexity through structured decision-making
3Quantity of substance
If content providers use broad audience targeting, then the reach is maximized, but the resource efficiency deteriorates
Solution Approach 1:
The system applies local quality by tailoring content delivery to specific user segments based on their profiles and contextual characteristics. Instead of uniform broad targeting, the system delivers customized invitational content to locally optimized audience segments, maximizing reach within each segment while improving overall resource efficiency through precise matching
Data Source
AI summary
A present technology intelligently retargets invitational content to a user by maintaining a user profile that includes data descriptive of the user's interaction with invitational content previously presented to the user and making decisions regarding retargeting based on an analysis of the user profile. The information in the user profile is not limited to whether or not the user completed a conversion action associated with invitational content presented. Rather, the profile is expanded to include such information as where on the conversion continuum the user abandoned the process and details of how the invitational content was presented to the user, e.g. colors used, situation, and message. When presented with a request for invitational content, the system uses the profile information to influence which content is selected and how it is presented to the user. This enables the system to re-present invitational content in a form and/or situation where the user is more likely to complete the conversion action.