Cross-Channel Recommendation Processing via Unified Data Aggregation
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Solution Overview
Problem
Current systems lack a holistic view of consumer transactions across disparate channels and sources, leading to inaccurate campaign management and ineffective promotions, as well as difficulties in capturing cross-channel transactions.
Innovation Solution
A method and system for cross-channel recommendation processing that aggregates data from various sources into a normalized dataset, processes prediction criteria to segment customers, and dynamically adjusts based on campaign success and failure data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data is aggregated from disparate communication channels and sources, then a holistic 360-degree view of consumer transactions is achieved, but system complexity increases
Solution Approach 1:
The patent introduces an intermediary data aggregation system that acts as a mediator between disparate communication channels and the analytics platform. This intermediary layer normalizes and consolidates data from multiple sources (online transactions, mobile apps, social media, email, etc.) into a unified format, enabling a holistic 360-degree view of consumer transactions without requiring direct complex integrations between all source systems.
2Device complexity
If consumer segments are defined using limited data, then segmentation is simpler to implement, but campaign accuracy and promotion success decrease
Solution Approach 1:
The patent implements a feedback mechanism where the system tracks campaign successes and failures, then uses this performance data to dynamically refine and adjust consumer segmentation. The analytics platform continuously learns from campaign outcomes, identifying which segment characteristics correlate with successful campaigns, and uses this feedback to improve future segmentation accuracy and targeting precision.
Solution Approach 2:
The system performs preliminary data normalization and aggregation from all available sources before segmentation occurs. By pre-processing and consolidating data from disparate channels into a unified consumer profile, the system prepares comprehensive consumer data in advance, enabling accurate segmentation without adding complexity during the actual segmentation and campaign execution phases.
3Device complexity
If cross-channel transactions are not captured, then data collection is simpler, but promotional effectiveness and campaign management deteriorate
Solution Approach 1:
The patent creates a universal data aggregation platform that handles multiple communication channels and data sources through a single unified system. This multi-functional platform can ingest, normalize, and process data from online transactions, mobile applications, social media interactions, email communications, and other channels through the same infrastructure, enabling comprehensive cross-channel transaction capture without proportionally increasing system complexity.
Data Source
AI summary
Cross-channel and cross-source data are aggregated into an aggregated data store. Custom segmentation is generated from the aggregated data. A campaign is monitored for the custom segmentation with successes and failures provided as dynamic feedback to a machine learning process that dynamically adjusts the segmentation and the campaign for optimal performance. In an embodiment, a final recommendation is provided identifying a final optimal segmentation and campaign.