Cross-Channel Advertising Attribution via Identity Resolution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current online advertising systems face challenges in accurately attributing conversion events across multiple devices, leading to inaccurate accounting and ineffective ad campaign estimation due to the inability to credit advertisements consistently across different channels.
Innovation Solution
A cross-channel online advertising attribution system that utilizes identity resolution services and consolidated event stores to connect user shopping events with conversion events across various devices, employing attribution models and data processing iterations to accurately attribute ad traffic events to specific advertisements, even when devices differ.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional single-device advertising tracking is used, then device complexity is low, but measurement precision of conversion attribution deteriorates
Solution Approach 1:
The patent introduces an identity resolution service as an intermediary component that receives identifiers from multiple devices, resolves them to a common user identity, and enables cross-device attribution. This mediator layer allows the system to track conversions across devices without requiring direct complex inter-device communication, thus improving measurement precision while managing system complexity through a dedicated intermediary service.
Solution Approach 2:
The system segments the attribution process into distinct functional components: ad traffic event collection, identity resolution, conversion event tracking, and attribution modeling. By dividing the complex multi-device tracking problem into these manageable segments, each handled by specialized services, the system achieves high measurement precision without overwhelming system complexity.
2Measurement precision
If cross-device tracking is implemented, then measurement precision of conversion attribution improves, but device complexity increases
Solution Approach 1:
The patent merges data from multiple devices by resolving their identifiers to a common user identity through the identity resolution service. This combining of device-specific data into a unified user view enables accurate cross-channel attribution while simplifying data processing through centralized identity management rather than requiring complex pairwise device correlations.
Solution Approach 2:
The identity resolution service acts as a mediator that handles the complex task of matching identifiers across devices. By offloading this complex matching logic to a dedicated intermediary service, the system achieves high cross-device attribution accuracy without distributing complex processing logic across multiple components.
3Measurement precision
If multiple identifiers are correlated, then attribution accuracy across devices improves, but difficulty of detecting and measuring increases
Solution Approach 1:
The identity resolution service serves as a specialized intermediary that handles the difficult task of correlating multiple device identifiers. This mediator contains the complex matching logic and algorithms needed to match identifiers across devices, transforming an intractable identifier matching problem into a manageable service operation that improves multi-device conversion tracking accuracy.
Solution Approach 2:
The identity resolution service performs self-service by autonomously matching identifiers and resolving user identities without requiring manual intervention. This automated self-service capability handles the complex identifier correlation task efficiently, improving attribution accuracy while reducing the operational difficulty of managing multi-device tracking.
Data Source
AI summary
The systems and methods described herein enable measurement of the exposure of a user to advertising campaigns across different channels (e.g., websites accessed by web browsers of laptops, desktops, or mobile computers, electronic readers or tablets, applications on mobile devices, and the like) and credit the exposure of the user to the advertisement to a specific advertisement in the campaign along with subsequent shopping events generated by the user, such as visiting product detail pages, visiting the read all reviews page for a product, adding a product to a wish list, adding a product to a shopping cart, subscribing to a product through an online subscription service, and/or purchasing a product.