Speech-Based Ad Targeting via User Profile Segmentation
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Solution Overview
Problem
Current advertising systems lack efficient targeting mechanisms, leading to unnecessary advertising to uninterested populations, and data mining techniques struggle with scalability and complexity in extracting actionable consumer purchasing patterns from large databases.
Innovation Solution
A software program that utilizes speech-to-text and text-to-speech engines to deliver targeted advertising, incorporating user profiles and dynamic content delivery, with features that encourage continuous usage and data collection, allowing for personalized and efficient advertising based on user interactions and preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional advertising systems deliver advertisements to all users, then advertising coverage is maximized, but advertising efficiency and relevance deteriorate due to targeting uninterested populations
Solution Approach 1:
The patent segments the user population into distinct groups based on demographics, interests, and browsing behavior. User profiles are created and maintained in a database, allowing advertisers to target specific segments rather than broadcasting to all users. This segmentation enables precise targeting of interested populations while excluding uninterested ones, resolving the contradiction between coverage and efficiency.
Solution Approach 2:
The system performs preliminary actions by collecting user data, creating profiles, and pre-segmenting audiences before advertising campaigns begin. Browsing behavior is tracked and analyzed in advance to predict user interests and preferences. This preliminary characterization of users allows advertisers to select pre-defined target segments, improving advertising efficiency while reducing waste on uninterested populations.
2Loss of information
If data mining techniques process large databases to extract consumer patterns, then actionable insights are obtained, but system complexity and computational requirements increase
Solution Approach 1:
The patent segments the large database into manageable user profiles with specific attributes (demographics, interests, browsing history). Instead of processing the entire database as one large entity, the system divides it into individual user records that can be independently analyzed and matched against advertiser criteria. This segmentation reduces computational complexity while preserving all consumer pattern information.
Solution Approach 2:
The patent introduces an intermediary layer (user profiles and segmentation database) between the raw data and the advertising delivery system. This intermediary structure organizes raw browsing and purchasing data into standardized profile formats, making the data more accessible and easier to query. The intermediary layer simplifies the matching process between advertiser requirements and consumer characteristics, reducing overall system complexity.
Data Source
AI summary
A method, and system for implementing the method, comprising the steps of providing an object browser user supporting at least speech communication with the user, permitting user-controlled browsing of objects received through a computer communication network; downloading an object through the computer communication network in dependence on a user input, the object having an associated data file defining a predetermined vocabulary and a predetermined grammar; presenting the downloaded object through the object browser, wherein speech information received from the user is interpreted in conjunction with both the predetermined vocabulary and the predetermined grammar; and selectively generating at least one communication through the computer communication network, in dependence on the interpreted speech information.