Customer Genome System for Real-Time Contextual Targeting
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Solution Overview
Problem
Traditional customer segmentation and association rules are inadequate in providing personalized experiences, especially in the digital era where customers are highly connected and informed, as they rely on approximating preferences based on broader population segments and are limited in insight and scalability.
Innovation Solution
The development of a customer genome system that processes data from multiple channels to create robust recipient profiles, generating custom metadata recommendations by analyzing attributes, preferences, and behaviors, allowing for real-time updates and contextual offer provision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional customer segmentation and association rules are used, then businesses can process data more simply, but the personalization quality and customer insight depth deteriorate
Solution Approach 1:
The patent segments customer data into multiple distinct channels (transactional data, contextual data, engagement data, operational data) and processes each channel separately through dedicated processing logic. This segmentation allows the system to handle complex multi-channel data while maintaining organizational clarity and processing efficiency, resolving the contradiction between personalization quality and system complexity
Solution Approach 2:
The patent introduces a data normalization layer that acts as an intermediary between raw multi-channel data and the profiling engine. This normalization layer standardizes data from different channels into a unified format, enabling complex cross-channel analysis without overwhelming the core processing system, thus achieving high personalization quality while managing system complexity
2Measurement precision
If data from multiple channels is processed to create robust recipient profiles, then customer insight accuracy improves, but data processing time and computational resources increase
Solution Approach 1:
The patent implements data normalization as a preliminary action that occurs before detailed profile analysis. By pre-processing and standardizing data from multiple channels in advance, the system reduces the computational burden during real-time profiling, thereby improving customer insight accuracy while minimizing additional processing time
Solution Approach 2:
The patent employs dynamic profile generation that adapts to available data and processing requirements. The system can adjust the depth and scope of multi-channel data processing based on real-time needs, allowing high accuracy profiling when resources are available while enabling faster, lighter processing when time is critical, thus balancing accuracy and processing time
3Adaptability or versatility
If real-time updates and contextual offer provision are implemented, then customer engagement quality improves, but system response time requirements and operational complexity increase
Solution Approach 1:
The patent implements feedback loops where customer responses to contextual offers are captured and fed back into the profile update mechanism. This allows the system to learn from actual customer behavior in real-time, improving engagement quality through continuous adaptation while automating the operational complexity of monitoring and adjusting campaigns
Solution Approach 2:
The patent enables the system to automatically generate and adjust contextual offers based on updated recipient profiles without requiring manual intervention for each campaign adjustment. The system self-manages the complexity of real-time offer provision by autonomously matching profile data with appropriate offers, thereby improving engagement quality while reducing operational burden
Data Source
AI summary
A computer system may access an attributization rule and convert, based on the attributization rule, profile data into attributes for a robust recipient profile. The system may identify, based on tag logic, tags that are associated with the attributes. The tag logic may include instructions to compare the attributes with predetermined attributes associated with the tags. The system may map the identified tags to the recipient identifier. The system may perform communication with a mobile device based on the robust recipient profile and a real-time location of the mobile device. To perform the communication, the system may monitor the plurality of data channels for data comprising real-time location information for the mobile device. The system may determine the mobile device is proximate to a physical object that is associated with the tag and the system may transmit offer information to the mobile device.