Dynamic TV Ad Selection via Common Purchase Profiles
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Solution Overview
Problem
Existing personalized television advertising systems are ineffective in dynamic environments like offices, hotels, and restaurants where multiple groups of people with different interests watch TV at different times, leading to frustration and reduced advertiser benefit.
Innovation Solution
A method where users define their purchase plans on mobile devices, which are transmitted to a provider server to identify and display advertisements based on common purchase profiles and plans among viewers within a given area or distance, ensuring relevant ads are shown to all nearby users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static personalized advertising profiles are used in places with rapidly changing viewers (offices, hotels, restaurants), then individual user preferences can be accommodated, but the advertising becomes ineffective when viewers change rapidly and creates viewer frustration
Solution Approach 1:
The system transitions from static advertising profiles to dynamic profiles that automatically update based on real-time detection of viewer presence. Mobile devices transmit viewer information to the media device, which then retrieves updated profile data from a server, ensuring the advertising content continuously adapts to the current audience composition in dynamic environments like restaurants and offices.
Solution Approach 2:
The system implements a feedback loop where mobile devices continuously transmit viewer information to the media device, which then queries the server for updated profile data. This closed-loop feedback mechanism ensures that advertising profiles remain current and relevant even as viewers come and go in dynamic environments, resolving the reliability issue.
2Adaptability or versatility
If personalized advertising systems are implemented, then advertising relevance to individual viewers improves, but the system complexity and infrastructure requirements increase
Solution Approach 1:
The system introduces a server as an intermediary that centralizes profile storage and management. Mobile devices and media devices communicate through standardized protocols with the server, which handles the complex tasks of profile retrieval and updates. This intermediary approach simplifies the overall system architecture while enabling sophisticated personalized advertising capabilities.
Solution Approach 2:
The server infrastructure serves multiple functions: storing user profiles, receiving viewer information from mobile devices, retrieving appropriate profile data, and managing advertising content delivery. This multi-functional approach consolidates system complexity into a single universal platform that supports personalized advertising across multiple media devices and locations.
3Productivity
If advertisements are targeted to specific individuals based on personal information, then advertising effectiveness increases, but the system cannot accommodate rapidly changing groups of viewers in shared spaces
Solution Approach 1:
The system dynamically updates advertising profiles by continuously receiving viewer information from mobile devices and retrieving fresh profile data from the server. This dynamic approach allows the system to maintain high advertising effectiveness even as viewer groups rapidly change in shared spaces like restaurants and offices, resolving the adaptability issue.
Solution Approach 2:
The server pre-stores detailed user profiles with advertising preferences before users arrive at the media device. When viewers are detected, the system quickly retrieves the pre-prepared profile data, enabling rapid adaptation to changing viewer groups without real-time processing delays. This preliminary preparation maintains advertising effectiveness in dynamic environments.
Data Source
AI summary
A method, system, and computer program product are disclosed for selecting an advertisement for play on a specified device for one or more users. Each of the users has a defined relationship with the specified device, and has an information description stored on a mobile communications device. In one embodiment, the method comprises transmitting the respective information description of each of one or more users from the user's communications device to a provider server. The server analyzes one or more information descriptions to identify an advertisement for playing on the specified device. The specified device, in one embodiment, is a television. In an embodiment, advertisements are displayed based on common purchase profiles and common purchase plans among different people. The purchase plans may be sent to the television when the users are in a defined area or come within a given distance of the television.