Personalized Video Notification System Reducing Spam Perception
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Solution Overview
Problem
Users of content sharing platforms often receive irrelevant or spam notifications about new episodes of video series, leading to user dissatisfaction and potential disengagement, as existing systems fail to provide timely and relevant notifications based on individual viewing habits and interests.
Innovation Solution
A method and system for generating customized timely notifications by detecting notifiable events related to video series, determining user affinity scores based on viewing history, and sending notifications referencing unwatched portions of videos, ensuring that notifications are relevant and engaging to users who have partially consumed the series.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If generic notifications about new episodes are sent to all users, then notification coverage is maximized, but notification relevance deteriorates leading to spam perception
Solution Approach 1:
The notification system transitions from uniform generic notifications to personalized notifications tailored to each user's viewing history and preferences. The system analyzes individual user behavior patterns and sends targeted notifications only for content relevant to that specific user, thereby maintaining high notification coverage while eliminating spam perception through localized personalization.
Solution Approach 2:
The system dynamically adjusts notification parameters such as timing, frequency, and content based on user engagement metrics and viewing habits. By changing these parameters adaptively, the system optimizes notification relevance for each user while maintaining overall system-wide notification coverage, preventing spam perception through intelligent parameter modulation.
2Productivity
If timely notifications are sent to remind users of unwatched content, then user engagement is improved, but notification complexity increases
Solution Approach 1:
The system pre-processes and stores user viewing history, preferences, and engagement patterns in advance. This preliminary action enables the notification system to quickly generate personalized timely notifications without complex real-time processing, thereby improving user engagement while managing system complexity through advance preparation of user profiles.
Solution Approach 2:
The notification system automatically analyzes user behavior patterns and generates personalized notifications without requiring manual configuration or complex external intervention. The system serves itself by using its own collected data to drive notification decisions, improving user engagement through timely relevant reminders while keeping the system architecture relatively simple through self-service automation.
Data Source
AI summary
A notifiable event pertaining to a series of videos may be detected, wherein detecting the notifiable event comprises searching a log pertaining to the series of videos. A user who has watched a portion of at least one video in the series of videos or at least one video in the series of videos may be determined, wherein the user is assigned an affinity score indicating a user interest to continue viewing the series of videos. A notification identifying the notifiable event pertaining to the series of videos may be generated, the notification comprising a reference to an unwatched next video in the series of videos. The notification may be transmitted to the user.