Social Network Ad Targeting via Group Interaction Analysis
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Solution Overview
Problem
Advertisers face challenges in creating relevant advertisements as they lack sufficient information about dynamics affecting consumer purchasing decisions beyond individual online activity, limiting the effectiveness of their ads.
Innovation Solution
A social networking system identifies and targets groups of users based on their common interactions, serving advertisements to members of these groups simultaneously to enhance ad relevance and conversion rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If advertisers use consumer data such as websites visited or content viewed to improve advertisement relevance, then advertisement relevance is improved, but the system lacks sufficient information about other dynamics affecting consumer purchasing decisions
Solution Approach 1:
The patent transitions from analyzing individual user online activity (one dimension) to analyzing group-level social interactions and dynamics (another dimension). By observing interactions among connected users within groups, the system captures social dynamics that individual data cannot reveal, thereby reducing information loss about purchasing decision factors.
2Measurement precision
If advertisers target advertisements to individuals based on their online purchasing activity, then targeting precision is improved, but the system cannot leverage social interactions affecting the consumer purchasing decision process
Solution Approach 1:
The patent merges individual user targeting with group-level social dynamics. Instead of treating users as isolated individuals, the system combines individual online activity data with observed social interactions among connected users. This merging enables the system to maintain individual targeting precision while simultaneously leveraging group-level social dynamics that influence purchasing decisions.
3Productivity
If the social networking system observes interactions of connected users to identify groups, then the system can target advertisements to groups effectively, but the complexity of the system increases
Solution Approach 1:
The system employs self-service mechanisms where users' existing social connections and interaction patterns automatically define groups. Rather than requiring complex manual configuration or external data sources, the system leverages the social networking infrastructure that already exists, allowing groups to form naturally through observed user interactions without adding significant system complexity.
Data Source
AI summary
Embodiments of the present disclosure target advertising to a group of related users of a social networking system. To target advertising to a group of users, the social networking system receives targeting criteria specifying a group to receive an advertisement at substantially the same time. To identify a group of users of the social networking system satisfying the targeting criteria, the social networking system observes the interactions of connected social networking system users. Connected users interacting with each other in a manner that satisfies the targeting criteria may be added to a group. The social networking system serves the advertisement to a set of users included in the group because the served users are members of the group.