Real-Time User Segmentation for Sub-Second Personalized Experiences
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Solution Overview
Problem
Existing systems face challenges in classifying users into segments with sub-second latency, especially as the number of users increases, to provide customized experiences efficiently, particularly in scenarios like e-commerce where timely promotions are crucial to prevent business loss.
Innovation Solution
A method and system that utilize a key-value pair store to retrieve user events, apply segment definitions to classify users into segments, and provide customized experiences within sub-second latency by using efficient data structures and real-time evaluation, including a load balancer, user action processor, and condition evaluator to manage user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional user segmentation systems are used, then user classification can be performed, but the system latency exceeds sub-second requirements and cannot handle increasing user numbers efficiently
Solution Approach 1:
The system segments user classification into distinct modular components: event collection service, segment evaluation service, and real-time recommendation service. Each component handles specific tasks independently, enabling parallel processing and reducing overall latency while maintaining high throughput for user segmentation operations
Solution Approach 2:
An event collection service acts as an intermediary layer between user actions and segment evaluation. This mediator buffers and pre-processes user events before they reach the segment evaluation service, reducing the processing burden and enabling sub-second latency responses even as user numbers increase
2Measurement precision
If detailed user event tracking is implemented to provide personalized experiences, then customization accuracy improves, but system complexity and processing time increase
Solution Approach 1:
The system divides complex user behavior tracking into discrete event types (clicks, views, purchases, etc.) handled by specialized collectors. Each event type is processed according to specific rules, maintaining high tracking accuracy while reducing overall system complexity through modular design
Solution Approach 2:
The system dynamically adjusts tracking parameters and event collection depth based on user segments and context. Not all users are tracked with the same level of detail at all times, which maintains measurement precision for critical events while reducing processing complexity for routine interactions
3Loss of time
If real-time user segmentation is performed to enable timely promotions, then business opportunity capture improves, but computational resources and processing power increase
Solution Approach 1:
User events are collected, buffered, and pre-processed in real-time before segment evaluation is triggered. This preliminary action prepares data in advance, enabling rapid segment determination and timely promotion delivery without requiring excessive computational resources at the moment of decision
Solution Approach 2:
The system applies different levels of processing intensity to different user segments and event types. High-value users or critical events receive more intensive real-time analysis, while routine events use streamlined processing, optimizing resource consumption while maintaining timely delivery of personalized experiences
Data Source
AI summary
A method for providing one or more customized experience to a user profile associated with an application is disclosed. The method comprises querying a key-value pair store for retrieving a key-value pair associated with the user profile. The retrieved key-value pair is loaded into a first memory. Further, one or more segment definitions for the one or more segments are received from a second memory. The one or more segment definitions are based on at least one of the user profile, user behaviour, user transaction on the application, user interaction with the application, and user subscription. Further, the one or more segment definitions and the one or more user events are evaluated in the first memory. The customized experience is provided to the user profile within sub-second latency and the customized experience is updated based on change in the one or more user events associated with the user profile.