User Behavior Scoring for Warm-Prospect Content Targeting
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Solution Overview
Problem
Conventional technologies face challenges in effectively selecting recipients for content delivery, such as advertisements, due to factors like cost and advertiser requests, making it difficult to optimize targeting.
Innovation Solution
An information processing apparatus utilizes generative AI to classify users into groups based on attributes, score users based on behavior history, and identify 'warm-prospect' users for targeted content delivery by comparing behavior patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to select advertisement recipients, then implementation cost and delivery record management are simplified, but the precision of recipient selection and targeting effectiveness deteriorates
Solution Approach 1:
The patent segments users into multiple user groups based on attributes (e.g., age, gender, interests) and further divides them into sub-groups based on behavior history. This segmentation enables precise targeting by analyzing specific user segments rather than treating all users uniformly, thereby improving recipient selection precision while managing complexity through structured organization.
Solution Approach 2:
The patent performs preliminary scoring of users based on behavior history before final recipient selection. By pre-calculating scores for multiple users and identifying warm-prospect users in advance, the system optimizes recipient selection without increasing real-time processing complexity, thus improving precision while maintaining operational simplicity.
2Productivity
If detailed user behavior analysis is performed to improve targeting, then content delivery effectiveness is improved, but processing time and computational resources increase
Solution Approach 1:
The patent pre-calculates behavior scores for users based on their history before the actual content delivery decision is made. By performing this scoring action in advance and storing the results, the system can quickly identify warm-prospect users during delivery time without performing complex real-time analysis, thus improving delivery effectiveness while minimizing processing time delays.
Solution Approach 2:
The patent creates a simplified representation (copy) of user behavior patterns through scoring mechanisms that capture essential characteristics without requiring full analysis of all behavior data. This copied representation allows for quick comparison and selection while reducing the computational burden of analyzing complete behavior histories in real-time.
3Measurement precision
If users are classified into multiple groups with detailed attributes, then targeting precision is improved, but the complexity of managing and processing user data increases
Solution Approach 1:
The patent organizes user data into hierarchical segments: first by broad attributes (age, gender) and then by behavior patterns. This segmented structure allows for precise targeting by combining multiple classification dimensions while managing data complexity through a systematic organization that prevents information overload and simplifies processing.
Solution Approach 2:
The patent extracts key behavioral characteristics from comprehensive user data to create simplified scoring representations. By taking out only the essential behavior patterns needed for classification and discarding redundant information, the system maintains high classification precision while reducing data management complexity and improving processing efficiency.
Data Source
AI summary
An information processing apparatus includes, a setting unit that sets a condition for a user classified into a user group from input data; a selecting unit that selects a to-be-analyzed group based on a user attribute corresponding to each condition with respect to each the condition; a scoring unit that scores each user meeting the condition based on a behavior history of each user corresponding to each condition with respect to each the condition; an extractor that extracts a warm-prospect user having a higher score than other users in the to-be-analyzed group based on a result of scoring by the scoring unit; and a provision unit that selects a to-be-compared user, specifies information on a characteristic behavior of the warm-prospect user, transmits information on the specified characteristic behavior and attribute information indicating the attribute corresponding to the warm-prospect user to a terminal device, and provides the specified and attribute information.