Identity Mapping Commerce Social Media Data Correlation
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Solution Overview
Problem
Traditional methods for providing personalized recommendations to customers are limited by relying solely on commerce transaction data, failing to capture up-to-date and comprehensive information about customer interests, as they do not effectively link customer identities across commerce and social media platforms.
Innovation Solution
A method that combines commerce data with social media data to map customer identities, using inferred attributes and activity correlations to estimate the probability of matching customer and social media user accounts, thereby enhancing the accuracy of identity mapping and enabling more relevant product suggestions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional recommendation methodologies use only historical transaction data to infer customer interests, then the implementation is simple and data privacy is maintained, but the coverage of customer interests is limited and recommendations are not up-to-date
Solution Approach 1:
The patent combines commerce transaction data with social media data to create a more comprehensive view of customer interests. By merging these two data sources through identity mapping, the system overcomes the limitation of using only transaction history while capturing broader and more up-to-date customer preferences.
Solution Approach 2:
The patent introduces an intermediary identity mapping system that connects commerce customer accounts with social media user accounts. This intermediary layer enables the integration of data from different platforms while maintaining system modularity and managing complexity through a structured matching process based on inferred attributes and activity correlations.
2Measurement precision
If retailers access customer social media data activities to provide personalized recommendations, then the personalization quality and product variety improve, but the difficulty of identifying and verifying links between customer and social media user increases
Solution Approach 1:
The patent employs feedback mechanisms where the identity mapping system continuously refines its matching accuracy by analyzing the correlation between inferred attributes from transaction data and actual social media activities. This feedback loop improves the precision of customer interest identification while systematically addressing the verification challenge through iterative optimization.
Solution Approach 2:
The patent replaces manual or direct verification methods with an automated computational system that uses inferred attributes and activity correlations to probabilistically match customer and social media user accounts. This substitution transforms the complex verification task into a scalable algorithmic process that maintains high precision without proportionally increasing operational difficulty.
3Adaptability or versatility
If the system maps customer accounts to social media user accounts using inferred attributes and activity correlations, then the comprehensiveness of customer understanding improves, but the computational complexity and data processing requirements increase
Solution Approach 1:
The patent segments the customer understanding process into distinct components: transaction data analysis, social media data analysis, attribute inference, and correlation matching. This segmentation allows the system to handle complex data processing tasks in manageable stages, improving customer profile completeness while controlling system complexity through modular architecture.
Data Source
AI summary
In one aspect, a computer system for evaluating the accuracy of an identity mapping method is disclosed. The system can comprise a system memory, one or more processors, and/or a computer readable medium containing compute-executable instructions representing a probability accuracy module. The probability accuracy module can be configured to query an identity map database for an identity map created using the identity mapping method, compare the identity map with additional social media data, calculate a correlation based on similarities between the social media data and the additional social media data, and/or verify the identity map based on the correlation. The identity map can be based on commerce data from a retailer and/or social media data from a first social media site. The additional social media data can be based on at least one of a second social media site different from the first social media site, a social media account expressly linked to a commerce customer account, and/or a social media database. Other embodiments are disclosed herein.