IP Address Attribution for Targeted Marketing Campaigns
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Solution Overview
Problem
Current techniques for determining physical and email addresses for targeted marketing campaigns are inefficient, as they rely on cookies, device fingerprinting, and user verification, which can be invasive and lack precision in identifying relevant users based on their search queries.
Innovation Solution
The method involves capturing IP addresses associated with specific searches and determining corresponding physical and email addresses using machine learning to assign relevant content, even to devices that haven't directly submitted searches, by analyzing request data and secondary information to identify geographic and demographic attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional techniques (cookies, device fingerprinting, user verification) are used to ascertain user information, then user identification can be achieved, but the process becomes invasive and lacks precision in identifying relevant users based on search queries
Solution Approach 1:
The patent uses IP addresses as an intermediary to identify users without directly collecting personal information. Instead of using invasive methods like cookies or device fingerprinting, the system captures IP addresses from search requests and uses them to determine physical addresses through machine learning models, thereby reducing invasiveness while maintaining identification precision
Solution Approach 2:
The patent replaces conventional mechanical identification methods (cookies, device fingerprinting, user verification) with a machine learning-based system that processes IP addresses and request data. This substitution enables more precise identification of relevant users based on search behavior patterns without the invasiveness of traditional methods
2Productivity
If machine learning is used to determine physical and email addresses from IP addresses, then campaign relevance is improved, but system complexity increases
Solution Approach 1:
The patent implements preliminary action by pre-training machine learning models with historical search data and request information before actual marketing campaigns. The system captures and processes IP addresses, device information, and search patterns in advance to build predictive models that can quickly determine physical and email addresses during campaign execution, thereby improving relevance without proportionally increasing operational complexity
Solution Approach 2:
The machine learning system performs self-service by automatically processing IP addresses and request data to determine user attributes without requiring manual intervention. The models autonomously analyze patterns in search requests, device information, and network data to predict physical addresses and email addresses, reducing the need for complex manual configuration and maintenance
Data Source
AI summary
Methods and apparatus related to determining and/or utilizing one or more attributes for an Internet Protocol (IP) address and/or other source identifier(s). In some implementations, the attributes may include a physical address and/or email address associated with the source identifier(s). Some implementations are directed to determining physical addresses for inclusion in a postal campaign and/or determining email addresses for inclusion in an email campaign. In some of those implementations, the physical addresses and/or email addresses are determined based on computing devices having source identifiers associated with those addresses having submitted searches with search content assigned to the campaign.