Simulation-Based Marketing Channel Attribution Model Evaluation
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Solution Overview
Problem
Existing marketing platforms fail to accurately compare and evaluate the effectiveness of different marketing channel attribution models, leading to sub-optimal use of network resources and inaccurate attribution of user responses to marketing channels.
Innovation Solution
A simulation-based approach is implemented to evaluate the accuracy of marketing channel attribution models by simulating user exposures and responses, allowing for the selection of the most accurate model and reallocation of resources to optimize marketing channel usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple marketing channel attribution models are implemented in existing marketing platforms, then marketers have access to different attribution estimation approaches, but the platforms fail to compare and evaluate the accuracy of these models
Solution Approach 1:
The patent implements simulation-based evaluation that performs preliminary testing of attribution models before actual marketing campaigns. By simulating user exposures and responses in advance, the system evaluates model accuracies beforehand, allowing marketers to select the most accurate model for their specific campaign parameters without needing to test multiple models in production.
Solution Approach 2:
The patent introduces simulation data as an intermediary between theoretical attribution models and actual marketing measurements. The simulation creates synthetic user exposure and response data that serves as a test bed for evaluating model accuracy, bridging the gap between model predictions and real-world performance without requiring actual marketing spend on evaluation.
2Ease of operation
If marketers use inaccurate attribution models to manage marketing channels, then resource allocation decisions are made based on flawed data, but the underlying network resources are still consumed
Solution Approach 1:
The patent implements a feedback mechanism where simulation-based accuracy evaluations feed into model selection decisions. The system continuously evaluates which attribution model performs best for given campaign parameters and feeds this information back to marketers, enabling data-driven selection of the most accurate model and preventing waste from using inaccurate models.
Solution Approach 2:
The patent evaluates attribution model accuracy based on specific parameters including number of users, number of marketing channels, average number of exposures per user, and average time between exposures. By changing and testing different parameter combinations through simulation, the system identifies which models perform best under specific campaign conditions, allowing optimized resource allocation tailored to each campaign's characteristics.
Data Source
AI summary
This disclosure involves allocating content-delivery resources to electronic content-delivery channels based on attribution models accuracy. For instance, a simulation is executed that involves simulating user exposures, times between user exposures, and user responses. The simulation is performed based on parameters associated with simulating user exposures to electronic content-delivery channels and user responses to the user exposures. An accuracy of a channel attribution model when estimating an attribution of an electronic content-delivery channel to a user response is evaluated based on the simulation. A channel attribution model is selected based on the evaluation. An attribution of the electronic content-delivery channel is determined by applying the selected channel attribution model to actual user exposures and actual user responses. This attribution can be used to allocate content-delivery resources to the electronic content-delivery channel in accordance with the selected channel attribution model, and thereby provide interactive content via the electronic content-delivery channel.