Aggregated Starting Point Information for Targeted Advertising
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current systems lack the ability to provide aggregated starting point information for entities, such as businesses, to effectively allocate resources for targeted advertising and promotional efforts, as they do not efficiently analyze user navigation data to identify origins of customers and potential customers.
Innovation Solution
A system that identifies locations associated with entities, aggregates starting points from navigation information query logs within a predefined vicinity, and provides demographic insights to recommend budget allocation across regions based on user travel patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If navigation information query logs are analyzed to identify starting points, then insights into customer origins and travel patterns are gained, but user privacy may be compromised
Solution Approach 1:
The system extracts and analyzes only the necessary navigation information (starting points, ending points, routes) from query logs to derive aggregated customer origin data, while excluding personally identifiable information. This selective extraction enables business insights without compromising user privacy.
Solution Approach 2:
The system uses an intermediary processing layer that aggregates and anonymizes navigation data before providing insights to businesses. This intermediary layer transforms raw navigation logs into aggregated statistical information, acting as a buffer that protects individual user privacy while preserving useful patterns.
2Productivity
If aggregated starting point information is provided to entities, then resource allocation for advertising is improved, but system complexity increases
Solution Approach 1:
The system segments the data processing into distinct functional modules: navigation information collection, starting point identification, aggregation by geographic regions, and insight generation. This segmentation allows each component to be optimized independently and simplifies the overall system architecture.
Solution Approach 2:
The system provides multi-functional capabilities through a single unified platform: it analyzes navigation data, identifies customer origins, aggregates information by region, and generates advertising recommendations. This universality reduces the need for multiple separate systems while improving resource allocation efficiency.
3Loss of information
If navigation data is collected and aggregated, then customer behavior insights are obtained, but data processing time increases
Solution Approach 1:
The system performs preliminary aggregation and processing of navigation data in near-real-time as queries are received, rather than waiting for batch processing. This preliminary action ensures that customer behavior insights are available promptly for timely advertising decisions.
Solution Approach 2:
The system maintains continuous processing of navigation data streams, constantly updating aggregated statistics and customer behavior models. This continuous action ensures that insights are always current without requiring periodic interruptions for batch processing, thereby reducing overall processing time.
Data Source
AI summary
Methods, systems, and computer program products are provided for providing aggregated starting point information. One example method includes identifying a location associated with an entity, identifying, from navigation information query logs, starting points for navigation information that includes an ending point in a predefined vicinity of the location associated with the entity, aggregating information associated with the starting points, and providing aggregated starting point information to the entity.