Universal Analytics Integration for Proprietary Publisher Interfaces
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Solution Overview
Problem
Existing advertising systems lack a unified solution to effectively generate analytics or useful data across multiple publishers with proprietary interfaces and targeting criteria, leading to inefficiencies and inaccurate targeting of consumers.
Innovation Solution
A universal integration framework that integrates analytics tools into advertising partners, allowing clients to target consumers based on their habits and activity across platforms, combining first-party and third-party data for enhanced consumer interaction and conversion analytics without requiring clients to write code.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple publishers use proprietary interfaces and targeting criteria, then each publisher can maintain its own data standards, but no unified analytics solution can be generated across platforms
Solution Approach 1:
The patent implements a universal integration framework that can interface with multiple different publisher platforms through standardized connection protocols. The system uses a common data structure and communication interface that works across diverse publisher systems, eliminating the need for custom integration code for each publisher while maintaining compatibility with their proprietary interfaces.
Solution Approach 2:
The patent introduces an intermediary layer (the integration framework) that sits between the analytics system and multiple publisher platforms. This intermediary handles the complexity of interfacing with different proprietary systems, translating various publisher-specific formats into a unified internal representation, thereby shielding the core analytics engine from publisher-specific complexities.
2Ease of operation
If clients integrate analytics tools manually across multiple platforms, then customization is possible, but code writing and integration effort increase significantly
Solution Approach 1:
The patent enables clients to integrate analytics capabilities without writing integration code. The system provides self-service through pre-built connectors and automated data collection mechanisms that work out-of-the-box with major publisher platforms. Clients simply configure their analytics parameters through a user interface, and the system automatically handles the complex integration tasks.
Solution Approach 2:
The patent performs preliminary integration work by pre-establishing connection protocols and data structures with multiple publisher platforms. The integration framework is prepared in advance with ready-made adapters and templates, so when a client wants to implement analytics, the heavy lifting of integration has already been done, and they only need to activate and configure the pre-built solutions.
3Reliability
If proprietary interfaces are used by each publisher, then interface security can be maintained, but data reliability and consistency across platforms decrease
Solution Approach 1:
The patent implements homogeneity by standardizing data structures, formats, and validation rules across all publisher interfaces. The integration framework enforces a common data model that ensures consistent data representation regardless of the source publisher, thereby improving data reliability and consistency while maintaining the ability to handle proprietary interfaces through standardized translation layers.
Data Source
AI summary
A system and methods for a universal integration framework for data analytics pipelines are disclosed. According to one embodiment, a computer-implemented method maintains internal consumer data that has a consumer ID associated with a consumer based on events at a partner platform. The platform server determines target characteristics based on instructions provided by a client or the internal consumer data and generates a target consumer group associated with an internal project ID based on the target characteristics, wherein the target consumer group includes the consumer ID and internal consumer data associated with each consumer. The platform server transmits the target consumer group to the partner platform and receives partner event data indicative of updates to consumer data. The platform server generates an updated target consumer group based on the updated consumer data and transmits updates to the partner platform to improve consumer interest.