Dynamic Target Selection via Adjustable Slider Axes
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Solution Overview
Problem
Current methods for selecting targets for advertisement campaigns are inefficient in utilizing demographic and behavioral data to accurately identify and prioritize potential responders, often relying on static filtering and ranking methods that do not adapt to user preferences effectively.
Innovation Solution
A method and system that utilize adjustable slider axes to control target selection, combining filtering and ranking criteria, allowing users to dynamically adjust the balance between filtering and ranking strengths, and using a user interface to input preferences and receive feedback for optimal target selection, with the system selecting a predefined number of targets based on demographic and behavioral data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If static filtering and ranking methods are used for target selection, then the process is simple and fast, but the accuracy of identifying potential responders is insufficient
Solution Approach 1:
The patent implements dynamic adjustment of filtering and ranking methods through a user interface with slider controls. Users can continuously adjust the balance between filtering strength and ranking strength, transforming a static selection process into a dynamic one that adapts to different campaign goals and audience characteristics, thereby improving accuracy without fixed complexity
Solution Approach 2:
The system changes the parameters of filtering and ranking by allowing users to adjust slider values that control the strength and type of filters applied, as well as the weighting of ranking criteria. This enables continuous variation in selection parameters to optimize the balance between process complexity and identification accuracy for different advertising scenarios
2Measurement precision
If multiple filtering and ranking methods are combined, then target selection accuracy improves, but the user interface complexity increases
Solution Approach 1:
The patent merges multiple filtering and ranking methods into a unified interface controlled by slider axes. Instead of presenting users with multiple separate complex controls, the system combines them into a coordinated adjustment mechanism where moving sliders simultaneously adjusts multiple parameters in a harmonized way, maintaining interface simplicity while enabling accurate multi-criteria selection
Solution Approach 2:
The slider-based control interface serves multiple functions: it controls filtering strength, ranking weightings, and the balance between different selection methods simultaneously. This universal control mechanism allows users to manage complex multi-method selection processes through a single intuitive interface paradigm, reducing perceived complexity while maintaining accuracy
3Adaptability or versatility
If dynamic adjustment of filtering and ranking is allowed, then adaptability to user preferences improves, but the time required for target selection increases
Solution Approach 1:
The system performs preliminary actions by pre-defining the range of adjustable parameters and preparing multiple filtering and ranking methods in advance. Users can immediately adjust sliders within pre-configured ranges without needing to configure complex parameters from scratch, enabling rapid adaptation to different preferences while minimizing setup time
Solution Approach 2:
The dynamic slider interface allows users to quickly adjust filtering and ranking parameters in real-time without requiring time-consuming reconfiguration. The continuous adjustment capability enables rapid exploration of different selection strategies, making the system highly adaptable to changing user preferences while maintaining fast operation through intuitive visual controls
Data Source
AI summary
Embodiments of the disclosure are directed to methods and systems for selecting targets for an advertisement campaign. A method may comprise adjusting one or more slider axes that control selection methods, wherein the selection methods may comprise using target demographic data, target behavioral data, filtering criteria, and/or ranking criteria. Then, an analysis application may complete analysis using the input adjustments to determine a selection of potential targets. The analysis application may be operable to complete multiple methods of analysis (or selection), wherein the user may have input and/or control over the use of the methods.