Notification Delivery Policy Engine for User Engagement
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Solution Overview
Problem
Current social-networking systems face challenges in delivering notifications in a user-aware manner, as they often fail to consider individual user preferences, context, and past interaction patterns, leading to low engagement and conversion rates.
Innovation Solution
A notification-providing system that assesses various factors, including user demographics, location, available delivery channels, and historical notification data, to determine a personalized delivery policy, utilizing multiple channels and scheduling notifications for optimal engagement, such as SMS, email, or voice calls, based on user activity and context.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If notifications are sent through multiple delivery channels to increase user engagement, then the likelihood of user interaction improves, but the system complexity and resource consumption increase
Solution Approach 1:
The notification system is segmented into multiple independent delivery channels (SMS, email, push notifications, voice calls) that can be selected and executed independently based on user context and preferences, allowing the system to manage complexity through modular organization
Solution Approach 2:
A policy engine acts as an intermediary between the notification request and delivery channels, assessing user context, preferences, and historical data to determine the optimal delivery method, thereby simplifying the overall system architecture by centralizing decision-making logic
2Productivity
If personalized delivery policies are implemented based on user demographics, location, and historical data, then user engagement and conversion rates improve, but the computational resources and processing time required increase
Solution Approach 1:
User preferences, demographics, and historical notification data are pre-assessed and stored in user profiles before actual notification delivery, allowing the policy engine to make quick decisions based on pre-computed information rather than analyzing raw data in real-time
Solution Approach 2:
The system incorporates feedback loops where user responses to previous notifications are analyzed and stored, continuously refining personalized delivery policies based on actual user behavior patterns, thereby improving conversion rates while optimizing resource usage through learned preferences
3Reliability
If notifications are tailored to individual user behaviors and contexts, then notification effectiveness and user interaction likelihood increase, but the data processing and policy determination complexity increase
Solution Approach 1:
The system applies local quality by tailoring notification delivery policies to individual user characteristics, contexts, and preferences rather than using uniform approaches, with the policy engine assessing specific user attributes to determine optimal delivery methods for each user
Solution Approach 2:
The policy engine dynamically changes delivery parameters (channel selection, timing, frequency) based on user context, historical behavior, and real-time conditions, allowing the system to adapt notification effectiveness to individual users while managing complexity through parameter-based control
Data Source
AI summary
In one embodiment, a method includes accessing a notification to be sent to a user, where the notification has a context. The method also includes sending a request to a history service for historical notification data associated with the user with respect to the context of the notification and a ranking of the notification where the ranking indicates a probability of the user interacting with the notification. The method also includes receiving the historical notification data and the ranking from the history service. Moreover, the method also includes determining a delivery policy to apply to the notification based at least in part on the context of the notification, the historical notification data, and the ranking. Furthermore, the method also includes applying the delivery policy to the notification to be sent to the user.