User Segmentation via Multi-Channel Data Normalization
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Solution Overview
Problem
Current techniques lack effective methods for segmenting users based on interactions with messages across multiple electronic communication channels, as data from different channels are often in disparate formats, making it difficult to target users with customized messages.
Innovation Solution
A computer-implemented method that normalizes user interaction data from various channels by applying time decay and volume adjustments, generating labels that combine insights from different channels to segment users effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data from multiple electronic communication channels are collected for user segmentation, then user targeting accuracy is improved, but data complexity and format incompatibility increase
Solution Approach 1:
The patent introduces a normalization layer as an intermediary that converts event data from multiple communication channels into a unified format. This normalization process handles the format incompatibility between channels (email, SMS, push notifications, etc.) by transforming all events into a common schema, enabling accurate user segmentation without being overwhelmed by data complexity.
2Productivity
If multiple message campaigns are sent across different channels to the same users, then user engagement is improved, but data reconciliation difficulty increases
Solution Approach 1:
The patent segments user interactions into discrete event types (opens, clicks, views, etc.) across different channels, then normalizes these segments into a unified structure. This segmentation approach allows the system to handle multiple message campaigns across different channels while maintaining data reconciliation through standardized event representations, reducing the complexity of aggregating and analyzing engagement data.
3Measurement precision
If user interaction data is normalized across channels, then user segmentation accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent applies parameter changes by transforming event data from various channels into standardized parameters and formats. The normalization process modifies event attributes (timestamps, interaction types, channel identifiers) into a consistent schema, which simplifies subsequent segmentation processing and improves accuracy without requiring complex manual reconciliation procedures.
Data Source
AI summary
Techniques are disclosed for segmenting users based on user interactions with messages transmitted over various electronic communication channels. In some embodiments, a segmentation application normalizes sets of event data associated with user interactions with messages that are transmitted over multiple electronic communication channels to generate intermediate labels associated with the sets of event data. The normalization includes applying a time decay while accounting for messaging cadence, messaging volume, and user interactions with messages associated with an industry. The intermediate labels are combined to generate a final label associated with the user via a pairwise combination technique that maintains a more favorable label when a pair of intermediate labels are combined. Additional messages can then be generated and/or transmitted based on the final label.