Brand Engine Dynamic Content Mapping for Social Advertising
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Solution Overview
Problem
Current online advertising techniques in social networking services lack variability and relevance, failing to effectively utilize social networks to provide interesting and targeted advertising to users.
Innovation Solution
The system enables users to create shareable brand profiles with brand objects, allowing for context-based modification and display of content, using a brand engine that maps user information to generate personalized and relevant advertising based on spatial, temporal, social, and topical data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional online advertising techniques are used in social networking services, then advertising can be delivered to users, but the advertising lacks variability and relevance
Solution Approach 1:
The advertising content is made dynamic by modifying it based on real-time user profile data, friend network information, and contextual factors. The system generates different ad variations automatically adapted to each user's social graph and preferences, transforming static ads into dynamic, personalized content that evolves with user interactions.
Solution Approach 2:
The system applies local quality by customizing advertising content for specific users based on their unique social networks, interests, and behaviors. Each user receives tailored ad content localized to their individual context rather than a uniform approach, improving relevance while maintaining overall advertising effectiveness.
2Adaptability or versatility
If users are provided with detailed user information for mapping, then personalized advertising can be generated, but system complexity increases
Solution Approach 1:
The system introduces an intermediary processing layer that automatically maps and transforms diverse user information into standardized advertising parameters. This intermediary layer handles the complexity of data transformation and relationship mapping, shielding users from system complexity while enabling detailed personalization through automated data processing and relationship inference.
Data Source
AI summary
A brand engine receives a request from a user device operated by a first user to display user information of a second user. User information of the first user is mapped to at least the user information of the second user by the brand engine. The mapping may map the user information of the first user to user information of further users in a social network. The mapping may map of any combination of spatial, temporal, social, and topical data related to the users. A modified representation of received content is generated by the brand engine based on the mapping. The modified representation is transmitted to the user device. The user device displays the modified representation for the first user. The modified representation of the received content may include any combination of filtered and/or sorted content items, recommended content items, and/or modified content items.


