Personalized Interactive TV Offer Presentation System
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Solution Overview
Problem
Current interactive television offer systems provide passive and static promotions that do not differentiate between subscribers within a household, failing to recognize individual interests and preferences, leading to missed marketing opportunities.
Innovation Solution
A method and system that assign unique marketing keys to subscribers, storing their information in a database, and using a decision engine to make dynamic and active offers based on their interests, viewing habits, and previous purchases, allowing for personalized marketing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If offers are made to all subscribers viewing a program at a given time, then the system is simple and easy to implement, but it fails to distinguish between different subscribers leading to lost marketing opportunities
Solution Approach 1:
The system segments subscribers by assigning unique marketing keys to individual subscribers within households. This allows the offer system to differentiate between multiple subscribers (e.g., male subscriber interested in fitness equipment vs. female subscriber interested in clothing) and deliver personalized offers based on their specific interests and viewing habits, rather than treating all viewers the same
Solution Approach 2:
The system implements feedback mechanisms by tracking subscriber responses to offers and using this information to refine future offer presentations. The marketing key system captures subscriber interactions and preferences, feeding this data back into the offer generation process to continuously improve personalization and marketing effectiveness
2Adaptability or versatility
If static and passive offers based on previous purchases are provided, then the system is easy to maintain, but it fails to recognize individual subscriber needs resulting in missed marketing opportunities
Solution Approach 1:
The system transitions from static offers to dynamic offer generation by using real-time data about subscriber viewing habits, interests, and behavior patterns. The offer presentation adapts dynamically based on what the subscriber is currently viewing or has shown interest in, rather than relying solely on historical purchase data. This creates active, context-relevant offers that respond to current subscriber needs
Solution Approach 2:
The system performs preliminary actions by pre-processing and storing subscriber information, viewing habits, and preferences in a database before offer generation is needed. This allows the system to quickly retrieve and personalize offers in real-time without complex automation during the actual offer presentation, balancing personalization with system simplicity
Data Source
AI summary
A method, a system, and computer readable medium comprising instructions for interactive television offer presentation are provided. The method comprises assigning a unique marketing key to a subscriber, storing the unique marketing key and information of the subscriber in a database, detecting a request from the subscriber comprising the unique marketing key, retrieving the information from the database based on the unique marketing key, and making at least one offer of a product or service to the subscriber based on the information.