Rule-Based User List Segmentation for Remarketing
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Solution Overview
Problem
Current online content distribution systems lack efficient methods to segment customer groups and accurately reflect advertiser preferences for remarketing, leading to ineffective targeting of advertisements based on user behavior and interests.
Innovation Solution
The implementation of a system that uses smart pixels to collect and process key-value pairs from user interactions, allowing for the creation and management of remarketing lists based on user attributes and rules, enabling targeted content delivery by adding or removing users from lists based on predefined criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional content distribution systems are used, then content can be delivered to users, but customer groups cannot be segmented efficiently and advertiser preferences cannot be accurately reflected
Solution Approach 1:
The patent segments users into distinct customer groups by creating remarketing lists based on user attributes (e.g., page views, interactions, demographics). This segmentation enables efficient targeting of specific customer groups with relevant content, directly improving the adaptability and versatility of the content distribution system without proportionally increasing complexity.
Solution Approach 2:
The system changes parameters by introducing user attributes and rules that dynamically define user segmentation criteria. By modifying the content distribution approach to incorporate these parameters (user behavior data, attribute-based filtering), the system achieves better customer group segmentation while maintaining manageable complexity through rule-based automation.
2Measurement precision
If remarketing lists are created without rules-based management, then users can be grouped, but the lists cannot accurately reflect advertiser preferences
Solution Approach 1:
The system incorporates feedback mechanisms where user interactions with content and resources are continuously tracked and used to update user attributes. This feedback loop ensures that remarketing lists accurately reflect current user behavior and advertiser preferences, improving measurement precision while the automated rule-based system maintains ease of operation.
Solution Approach 2:
The remarketing lists are made dynamic through rules that automatically add or remove users based on their behavior and attributes. This dynamic management ensures lists accurately reflect advertiser preferences without manual intervention, achieving high measurement precision while maintaining ease of operation through automation.
3Productivity
If manual user list management is used, then lists can be created, but they require significant manual effort and cannot adapt quickly to changing advertiser preferences
Solution Approach 1:
The system implements self-service automation where rules automatically manage user list membership based on predefined criteria. Users are automatically added or removed from remarketing lists based on their behavior and attributes without manual intervention, dramatically improving productivity while maximizing the extent of automation in list management.
4Ease of operation
If user behavior data is not tracked, then privacy concerns are reduced, but targeted content delivery cannot be achieved
Solution Approach 1:
The system applies local quality by collecting and using only the specific user behavior data necessary for targeted content delivery, rather than comprehensive data collection. User attributes are defined locally based on relevant interactions (page views, resource access), enabling targeted content while minimizing unnecessary data collection and addressing privacy concerns.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for receiving data including a user identifier associated with a user and one or more key-value pairs associated with the user's access of a resource. Each key-value pair includes a key and a value provided by the resource. Upon determining that the received data satisfies one or more rules associated with a user list comprising user identifiers, the user identifier is added to the user list.